Public report — FFlow, published 3 Aug 2026.
Concrete security findings (CVE IDs, secret matches, dependency versions) are hidden in this version;
ask the repo owner for the full report.
89findings with an exact file:lineof 113 — the remainder are repo-wide signals (a dimension-level measurement, not a single line); open any file:line and verify
59/98dimensions across the health lenses10013 LoC · 19 projects — wide & deep
Executive summary
Read through the Production lens — the standard calibration. *Green* means good enough to run in production. The score is absolute and comparable across repos.
thiagomvas/FFlow is in a workable but fragile state (56%). It is not in crisis, but it carries material risk that makes change slower and incidents harder to contain if left unaddressed.
The area that most needs attention is Readiness (50%) — operating, monitoring and recovering the system safely is harder. Performance (56%) is the next concern — it raises ongoing delivery and operational cost.
Leadership focus, highest impact first: Extend structured logging across the projects you operate (Observability); SAST step to CI running what this repository's stack ships (Security & performance tooling); readiness/liveness probes and a rolling-update (or blue/green)… (Deployment & Rollback).
For scale: Small (~10,013 production lines); rebuilding it from scratch would take roughly ~0.1 person-years (~1 engineer). Approximate, ±~30%.
How the score is built — each lens's share of the headlineWidth is the lens's weight in the worst-heaviest fold (the weakest area pulls hardest); colour is that lens's own band. A lens fixes the score in proportion to its width.
A full-fidelity diff against the previous run's complete recorded findings — line-move tolerant: a finding that only shifted line counts as unchanged, only genuinely new titles/files surface here.
This codebase represents roughly ~0.1 person-years of build effort (about ~€18,000 to rebuild). Its weakest lens is Readiness at 50% — the part of that asset most exposed by the findings below.
How we model this: boilerplate at a scaffolding rate + logic × domain Standard (×1.1) — service/app × a 0.8× quality factor, at €60–95/h; indicative, ±~30%. Indicative only — most sensitive to the hourly rate and the domain tier (both tunable in config).
Top priorities
The highest-leverage moves; the full ranked list is in the Roadmap below.
1
Extend structured logging across the projects you operate, and give the library ones a diagnostics seam instead — an `EventSource`/`ActivitySource` the host can subscribe to, or an optional logger on your options object — rather than taking a logging dependency on your consumers' behalf.
Add a SAST step to CI running what this repository's stack ships: CodeQL's csharp pack (it analyses VB.NET too), or a security analyzer package — or `semgrep --config=auto`, which runs on any language — so a security regression fails the build instead of landing.
Value concentrated against a weak lens · Medium · Value at risk
This is a Small asset (~0.1 person-years to rebuild), and its weakest lens is Readiness at 50%. The operational and business risk on an asset this size concentrates there — that's where remediation buys the most protection.
→ Direct remediation budget at Readiness first — highest risk-reduction per euro on an asset this size.
Highest-leverage move · Medium · Leverage
Of everything flagged, the best return on effort is: Extend structured logging across the projects you operate, and give the library ones a diagnostics seam instead — an `EventSource`/`ActivitySource` the host can subscribe to, or an optional logger on your options object — rather than taking a logging dependency on your consumers' behalf. The rest can wait behind it.
Evidence: priority ranking: top of 5 ranked by impact/effort
→ Extend structured logging across the projects you operate, and give the library ones a diagnostics seam instead — an `EventSource`/`ActivitySource` the host can subscribe to, or an optional logger on your options object — rather than taking a logging dependency on your consumers' behalf.
Architecture — module dependency graph
Project dependencies, layered top-to-bottom; arrows show direction. Any dashed red edge points upward or sideways — a layering smell or cycle. A clean layered graph has none.
Architecture — module dependency matrix
23 modules, 18 dependencies — every dependency points down the layering, so there are no cycles. Rows and columns are the same modules, ordered so that a module only depends on ones above it. A cell means the row depends on the column, and its number is how many type pairs create that dependency. Read one thing: is anything above the diagonal? A mark there is a dependency cycle. (A cycle is all this shows — an unusual but cycle-free dependency sits below the diagonal like any other.)
Findings mapped to OWASP categories; the specific CVEs/secrets are in the Security dimension cards below and findings.md (redacted only on the public version of this report).
OWASP category
Findings
Severity
A03:2021 — Injection
7
High / Critical
Roadmap
First, extend structured logging across all projects and provide a diagnostics seam for libraries to avoid tight coupling. Second, integrate a static analysis tool into the CI pipeline to automatically fail the build on security regressions. Third, implement readiness and liveness probes with automated rollback strategies to catch bad releases. Fourth, restrict the public API by making types internal by default to protect consumers from internal changes. Finally, ensure the entire call chain is fully asynchronous to prevent blocking on tasks.
Ranked by impact ÷ effort. "Helps" is the estimated gain on the 0–100 health score.
Do this
Helps
Effort
Dimension
Extend structured logging across the projects you operate, and give the library ones a diagnostics seam instead — an `EventSource`/`ActivitySource` the host can subscribe to, or an optional logger on your options object — rather than taking a logging dependency on your consumers' behalf.
Add a SAST step to CI running what this repository's stack ships: CodeQL's csharp pack (it analyses VB.NET too), or a security analyzer package — or `semgrep --config=auto`, which runs on any language — so a security regression fails the build instead of landing.
Add a benchmarking harness for the hot paths and run it in CI to catch regressions (for .NET, a BenchmarkDotNet project with [MemoryDiagnoser] to track allocations).
Watchdog is a deep, periodic assessment — run each sprint, monthly, or quarterly, taking the time to go wider and deeper than a quick check and surfacing in one coherent report what you'd otherwise piece together from a dozen separate tools. It scores deterministically: the same commit yields the same score, every run. 56 of 59 evaluated dimensions are computed purely by tools and static analysis (confidence 1.0); 3 documentation/naming judgement(s) are LLM-assisted and labelled advisory. Overall confidence is 0.7 — the weighted average across measured dimensions; it falls as more of the score leans on LLM-assisted judgement and rises when it's fully tool-backed.
Every figure here is one of three kinds, and we label which: ✓ Measured — a deterministic fact (LoC, complexity, coverage); ~ Modeled — an estimate from a stated model (cost, effort, value-at-risk), always a range with its assumptions, never a precise fact; ◐ Advisory — an LLM prose judgement. We never present a modelled estimate as if it were measured. Perfect or absent scores carry their provenance too (ADR-0011): ✓ Tool-verified means the property itself was measured across the surface; ○ Nothing flagged means the probes came back clean — a claim bounded by what a repository can show; ⊘ Not evidenced means a working control (a tested restore, an automated rollback) showed no positive evidence — absence of evidence is not evidence of a control, so it's excluded from the score rather than awarded a spurious 10; ◐ Sampled · advisory marks an LLM verdict over a bounded sample — advisory, never a deterministic measurement.
What we checked — 59 dimensions across the health lenses
Each chip is a dimension scored from real signals across architecture, testing, dependencies, security & compliance, documentation, git-history and code quality — in one coherent pass. A surface report typically covers a handful.
How to trust any code-health report — three questions
Can you open the finding? Real findings cite a repo-relative file and line you can open at the cited line — never an absolute scratch path. Here, 89 of 113 do; the remainder are repo-wide signals — a dimension-level measurement, not a single line. (Every path in this report is repo-relative by construction: paths are normalized at the producer and the report is rejected if any rooted path leaks through.)
Is there a tool behind the number? Every score below names the method that produced it — Roslyn, git, a scanner, or (for a handful of documentation/naming dimensions) an LLM labelled sampled · advisory — not a narrative.
Does re-running give the same result? Run it again on the same commit and the score — and this report, byte for byte — is identical. A report whose numbers move between runs is describing the run, not the code.
This report answers yes to all three. That's the bar to hold any assessment to.
Tools & methods
The actual versions used this run (captured at analysis time) — re-run on the same commit for the identical score.
Method
Backs
Version
Evaluator
Roslyn static analysis
Complexity, cohesion, coupling, dead code, API surface, layering
A clean run — every tool resolved and ran, and every applicable dimension was measured at full confidence. No scanner was unavailable, no analysis timed out or crashed, and nothing fell back to a degraded estimate.
When something does degrade — a missing scanner, a shallow clone, an LLM hiccup — it is named here explicitly and its exact cause recorded in diagnostics.md, never absorbed silently into the score.
Repo exclusion declarations (.gitattributes linguist-generated/vendored, .editorconfig generated_code): none declared — every source file was scored.
Limitations & what we did not check
Watchdog assesses the repository exactly as committed, and only the repository. By design it does not reach outside the source tree: the live cloud account, the running CI/CD pipeline, the host's branch-protection and approval rules, the production configuration, or a restore actually exercised against a backup are all out of scope. That boundary is a feature, not a gap — a repo-relative, deterministic scan re-runs identically on any commit and every finding opens at a real file and line, where a live audit can neither be reproduced nor traced. The visible consequence is that controls which leave no in-repo evidence are reported as "not evidenced" and excluded from the score rather than awarded a number a static scan cannot justify.
Per-dimension blind spots
For each dimension that was measured, what a static, repo-only scan structurally cannot see — the honest edge of the measurement, not a failure of it.
D1 Cyclomatic Complexity: Cyclomatic complexity counts branches statically — it cannot tell an essential decision tree from accidental tangle, nor see complexity that lives in data or configuration (large switch-case token tables, DSL lexers/parsers, data-as-code rule tables) rather than control flow: a tokenizer's many single-character cases read as high complexity though each branch is trivial.
D2 Cognitive Complexity: Cognitive-complexity heuristics approximate how hard code is to follow; genuine domain difficulty and well-named intent that eases reading are not captured.
D3 God Classes: "God class" is sized by members and responsibilities visible in the type — a deliberately broad facade over a coherent subsystem can read the same as an accidental grab-bag. For front-end JS the file-length check is cohesion-aware (a single-responsibility module — one class/IIFE — earns a 3× threshold), but cohesion is approximated from top-level declarations, not true dependency structure.
D4 Code Duplication: Duplication is token-similarity (jscpd) — it finds copy-paste, not semantic duplication expressed differently. Committed machine-written code (scaffolded migrations, designer/codegen output, protobuf/OpenAPI stubs, model snapshots) is EXCLUDED — its repetition is the tool's, not the team's — so the score reflects hand-written duplication only.
D5 Coupling: Coupling is measured between projects/assemblies — runtime coupling through DI, reflection, messaging or shared databases is invisible to a static reference graph.
D6 Cohesion (LCOM4): LCOM4 cohesion is syntactic — it infers connectivity from which methods touch which fields/methods by name, not from real runtime behaviour or intent.
D8 Code Coverage: Coverage is measured by building and running the test suite inside Watchdog's isolated image — the target repo is never modified, and nothing on your systems runs. So coverage exists only when the suite builds and runs within the inline time budget; one that needs external services, can't build, or exceeds the budget yields no coverage (D8 then degrades to not-measured, not a low score). Line coverage also says nothing about assertion quality.
D9 Test Distribution: The test-pyramid shape is inferred from project/folder naming and references, with a single test host bucketed per-file by its path tier and content signals — a suite that names tiers unconventionally and gives no per-file signal can still be mis-bucketed.
D10 Test Quality: Assertion density is structural — it cannot tell a meaningful behavioural assertion from a trivial one, only that an assertion is present.
D11 Test Reliability: Flakiness is inferred from history/markers — Watchdog runs the suite once (for coverage), not the repeated runs under varied conditions that reveal nondeterminism, so a flaky test never recorded as failing is invisible here.
D12 Dependency Hygiene: Dependency health reads manifests and lockfiles — a vulnerability in a vendored/copied dependency, or risk from how a dependency is actually used, is outside this view.
D13 Secret Scanning: Secret detection is signature- and entropy-based on the current tree — a secret that does not match a known pattern, or one already rotated, will not be flagged (a clean scan is "nothing matched", not "no secrets exist").
D14 License Compliance: License compatibility is checked against declared package metadata and a policy — mislabelled or missing license metadata, and obligations that depend on how you distribute, are not resolved here.
D15 Churn × Complexity Hotspots: Churn hotspots come from git history — a freshly imported or squashed repository has no churn signal, and recent rewrites can mask a historically risky file.
D16 Bus Factor: Bus-factor is a time-decayed model of commit attribution (who has recently, repeatedly worked a file), not comprehension — pairing, review and reading-without-committing spread knowledge it can't see; bot commits and shared accounts still distort it.
D17 Explicit Debt: Acknowledged-debt signals (TODO/FIXME, suppressions, dead code) are textual — undocumented debt that nobody marked, and debt that lives in design rather than annotations, is invisible. Committed machine-written code (scaffolded migrations, designer/codegen output, generated stubs) is excluded — it is never the team's dead code to delete.
D18 Solution Shape: Build integrity reflects whether the solution compiled in this environment — a build that needs a private feed, a specific SDK, or a generated file absent from the repo can read as broken when it is merely unreproducible here.
D19 Documentation Quality: Documentation quality is judged by an LLM over a bounded sample of docs — it reads what is written, not whether the docs match the running system, and it is advisory, not a measurement.
D20 ADR Quality: ADR quality is an LLM read of the decision records present — it cannot know about decisions made and never recorded, and its verdict is sampled and advisory.
D21 Naming Consistency: Naming quality is an LLM judgement over a bounded sample — it assesses clarity/consistency of the names it sees, not domain-correctness, and is advisory.
D24 Comment Value: Comment value (WHY vs WHAT) is an LLM judgement over a bounded sample — it is advisory and cannot weigh a comment against the precise code change it was written to explain.
D26 Project Cohesion: Project focus is sized from members/namespaces per project — a project that is broad by deliberate design reads the same as one that has sprawled.
D27 Navigability: Indirection/navigability is structural — it measures hops to follow a call, not whether that indirection buys real flexibility or just ceremony.
D28 Secrets (history): Secret-history scanning sweeps the git log for known patterns — a secret that predates the available history, or never matched a signature, is not found (clean means "nothing matched in the history we can see").
D29 Static Analysis (SAST): SAST findings are pattern-based (semgrep) — it finds classes of bug it has rules for; logic flaws, auth/authorization gaps and issues needing runtime context are out of reach (and clean means "no rule matched").
D30 Dependency Vulnerabilities: CVE matching depends on accurate package/version metadata and the advisory database — a vulnerability with no published advisory, or in code not declared as a dependency, is not seen.
D34 Knowledge Freshness: Freshness is decayed commit RECENCY, not comprehension — code read often but rarely committed reads as orphaned, and stable code that genuinely needs no changes is penalised the same as forgotten code; bot/squash commits distort it like the bus factor.
D35 Change Coupling: Change coupling is co-change in COMMITS — files split across separate commits, or coupled only through a shared config/build step, read as uncoupled, and a sweeping commit (rename/format) is excluded so it doesn't couple everything. It shows that files change together, not WHY: a high coupling can be a healthy cohesive pair as readily as a hidden leak.
AX10 Code composition: Role is inferred from namespace/folder convention, not semantics — a domain concept living in a folder named "Services" reads as application, and the split is lines-of-code, not business value. The business-logic-share score is a SOFT, FLOORED signal: it contributes to the Architecture lens but is floored at the Critical gate, so an infrastructure-heavy design (a gateway, an ETL, a driver) is legitimately low without being nuked to zero.
M4 Documentation accuracy: Onboarding quality is an LLM read of the docs/setup present — it cannot run the onboarding or measure how long a real new joiner takes; the verdict is sampled and advisory.
P4 Deployment & Rollback: Approval/branch-protection rules live in repository settings the scan cannot see — only their in-repo evidence (config files, workflows) is checked, so a control enforced purely in the host's settings reads as "not evidenced".
P6 Release Hygiene: Rollback/observability controls are inferred from repo artefacts (pipelines, dashboards-as-code) — controls configured in external tooling, with no in-repo trace, cannot be credited.
The LLM boundary
LLM-set scores this run (5): D19, D20, D21, D24, M4 (model: Local LLM). For these, a model reads a bounded sample and sets the numeric score (documentation, ADR quality, naming, comment value, onboarding) — D25 sets the ADR-conformance fraction over sampled code, D22 judges API accuracy over a sample. These are sampled and advisory by design: they vary at the margins between runs and are never a deterministic measurement. Every other score in this report is tool-computed at confidence 1.0.
What it measures: How tangled the control flow is — methods with many branches are hard to test and change.
Method: Cyclomatic complexity per method (1 + decision points), computed exhaustively across production source; test projects separated by convention. Deterministic.
+ 5 more group(s) — more in Appendix A; the complete list is findings.md.
What to do
Resolve the 1 DotnetTestStep.BuildCommand (cyclomatic 32) finding(s) in Cyclomatic Complexity — start with DotnetTestStep.cs. — One of this dimension's main actionable groups (1 warning-level).
Resolve the 1 DotnetPublishStep.BuildCommand (cyclomatic 24) finding(s) in Cyclomatic Complexity — start with DotnetPublishStep.cs. — One of this dimension's main actionable groups (1 warning-level).
Resolve the 1 DotnetBuildStep.BuildCommand (cyclomatic 23) finding(s) in Cyclomatic Complexity — start with DotnetBuildStep.cs. — One of this dimension's main actionable groups (1 warning-level).
Enforce Cyclomatic Complexity in CI to reach Verified (currently Documented). — Hardens enforcement from Documented toward Prevented — provenance only; does not change the score.
Detailed fixes: d1_recommendation.md · top locations in Appendix A, every location in findings.md.
What it measures: How hard the code is for a person to follow, beyond raw branching.
Method: Cognitive complexity per method (Sonar-style nesting-penalized score), computed exhaustively over production code, excluding test projects. Deterministic.
+ 8 more group(s) — more in Appendix A; the complete list is findings.md.
What to do
Resolve the 1 DotnetTestStep.BuildCommand (cognitive 31) finding(s) in Cognitive Complexity — start with DotnetTestStep.cs. — One of this dimension's main actionable groups (1 warning-level).
Resolve the 1 Workflow.RunAsync (cognitive 29) finding(s) in Cognitive Complexity — start with Workflow.cs. — One of this dimension's main actionable groups (1 warning-level).
Resolve the 1 RunCommand.Execute (cognitive 27) finding(s) in Cognitive Complexity — start with RunCommand.cs. — One of this dimension's main actionable groups (1 warning-level).
Enforce Cognitive Complexity in CI to reach Verified (currently Documented). — Hardens enforcement from Documented toward Prevented — provenance only; does not change the score.
Detailed fixes: d2_recommendation.md · top locations in Appendix A, every location in findings.md.
Do you agree with this assessment?
D3 · God Classes10.0 / 10Exemplary✓ Tool-verified
What it measures: Over-large classes that try to do too much ("god classes").
Method: God-class detection by line and method-count thresholds per logical type (partial classes unified), filtered for generated code and registration/contract false positives. Deterministic.
What it measures: Copy-pasted code that should be shared instead.
Method: Code duplication via token-stream sliding windows with type-aware normalization (locals masked, type names preserved), density-scored per KLoC of production code. Deterministic.
+ 1 more group(s) — more in Appendix A; the complete list is findings.md.
✓ On the Gold path — maintain.
Detailed fixes: d4_recommendation.md · top locations in Appendix A, every location in findings.md.
Do you agree with this assessment?
D5 · Coupling10.0 / 10Exemplary✓ Tool-verified
What it measures: Whether volatile projects sit underneath others that depend on them (so their churn ripples upward), and whether project dependencies form cycles. A widely-depended-on but stable shared/kernel project is healthy, not penalised.
Method: Dependency cycles via elementary-DFS over real .csproj references, plus Martin instability (afferent/efferent) per project. Exhaustive over the reference graph, deterministic.
Coverage: Exhaustive · type-level: afferent/efferent coupling + cycles computed over every production type — the population is all types, not a name convention.
What it measures: Whether a class's methods are focused on a single responsibility.
Method: LCOM4 cohesion per production class with at least two methods: connected components of methods sharing state or calls, computed syntactically. Deterministic, not a proxy.
Coverage: Exhaustive · type-level: LCOM4 cohesion computed over every production class — the population is all types, not a name convention.
What it measures: How much of the code is actually exercised by tests.
Method: Coverage from coverlet runs or committed reports (Cobertura/OpenCover/lcov), computed per-file with structured exclusions for generated, trivial, and glue code. When the suite can't be built/run in-image AND no report is committed, coverage is reported NOT-MEASURED (excluded from the score) with the precondition to make it measurable — never a LoC-ratio proxy folded in as if measured. Deterministic.
Detailed fixes: d8_recommendation.md · top locations in Appendix A, every location in findings.md.
Do you agree with this assessment?
D9 · Test Distribution10.0 / 10Exemplary✓ Tool-verified
What it measures: Whether the test suite has a healthy mix of unit / integration / end-to-end tests.
Method: Test projects classified (Unit/Integration/BDD/E2E) from compiled metadata; test methods counted exhaustively across projects with placement-agnostic disk fallback. Deterministic.
73 test methods: 73 unit, 0 integration, 0 BDD, 0 e2e.
✓ On the Gold path — maintain.
Detailed fixes: d9_recommendation.md.
Do you agree with this assessment?
D10 · Test Quality10.0 / 10Exemplary✓ Tool-verified
What it measures: Whether the tests truly assert behaviour rather than just running the code.
Method: Per-test assertions, skips, and mock references analyzed via Roslyn; structured skip-reason tags (BUG:/ENV:) separate documented deferrals from debt. Deterministic.
0 skipped, 0 zero-assertion, no mocking-framework packages referenced (hand-written doubles or no mocking) across 73 tests.
✓ On the Gold path — maintain.
Detailed fixes: d10_recommendation.md.
Do you agree with this assessment?
D11 · Test Reliability10.0 / 10Exemplary✓ Tool-verified
What it measures: Whether the tests pass reliably, with no flakiness.
Method: Suite re-run N times within tiered wall-clock budgets (unit to e2e); tests failing non-deterministically across runs flagged; guarded tests retried when #if guards detected.
What it measures: Whether dependencies are current, secure, and not bloated.
Method: Manifest scan via dotnet list package across all projects; worst-signal-per-package deduction (saturating for vulnerabilities, capped-linear for deprecation/outdated) per KLoC. Exhaustive, deterministic.
What it measures: Whether any secrets (keys, tokens, passwords) have leaked into the code.
Method: In-process native secret scanner (entropy plus signature patterns) across all tracked files; no external tool. A clean result is a measured 10, not no-data zero. Deterministic.
What it measures: Whether the licenses of third-party packages are compatible with your policy.
Method: Third-party package licenses resolved from declared package metadata and checked against the configured policy (allow/deny/copyleft). Deterministic; clean = no incompatible license found at metadata depth.
What it measures: Files that change often and are also complex — the riskiest hotspots.
Method: Per production file churn times cyclomatic complexity over a rolling window, computed from git and Roslyn/JS/Razor analysis. Exhaustive, deterministic per commit date.
What it measures: Whether knowledge is concentrated in too few people (the "bus factor").
Method: Living knowledge per author via time-decayed commit attribution (6-month half-life, focus weighting) across largest source files. Deterministic, avoids blame's mechanical-refactor false positives.
39 source file(s) have their living knowledge concentrated in one author (≥90% of recent, decayed contribution). The largest is src/FFlow/FFlowBuilderExtensions.cs.
Small-team knowledge concentration
What to do
Resolve the 1 Small-team knowledge concentration finding(s) in Bus Factor. — One of this dimension's main actionable groups (1 recommendation-level).
Detailed fixes: d16_recommendation.md · top locations in Appendix A, every location in findings.md.
Do you agree with this assessment?
D17 · Explicit Debt7.4 / 10Strong✓ Tool-verified
What it measures: Acknowledged debt left in the code — TODOs, dead code, suppressed warnings.
Method: Roslyn syntactic debt markers (suppressions/TODO/FIXME/HACK/empty-catch/commented-code/Obsolete) plus SymbolFinder dead-code analysis; weighted-debt-per-KLoC density deducted 2.0x per unit. Deterministic, exhaustive.
Resolve the 1 NoWarnInCsproj repeated across 13 files finding(s) in Explicit Debt — start with FFlow.csproj. — One of this dimension's main actionable groups (1 issue-level).
Resolve the 4 Dead code finding(s) in Explicit Debt — start with Internals.cs (3), PipelineLoggerEventListener.cs. — One of this dimension's main actionable groups (4 warning-level).
Resolve the 3 ObsoleteWithCallers finding(s) in Explicit Debt — start with FFlowBuilderExtensions.cs (3). — One of this dimension's main actionable groups (3 warning-level).
Enforce Explicit Debt in CI to reach Verified (currently Documented). — Hardens enforcement from Documented toward Prevented — provenance only; does not change the score.
Detailed fixes: d17_recommendation.md · top locations in Appendix A, every location in findings.md.
What it measures: Whether the solution is laid out in a sensible, conventional structure.
Method: Solution structure: project count, decomposition, shell-project detection, build success (confirmed failures cap the score); traced to actual .sln files and binaries. Deterministic.
What it measures: Whether the project's documentation is clear, complete, and useful.
Method: Judged by language model at low temperature (0.0-0.1) on a deterministic doc sample (READMEs plus first 25 architecture docs), with two-pass stability filtering. Advisory, sampled.
The documentation is clear, complete, and well-structured across a strong README plus an overview.md that covers installation, terminology, how it works, and GitHub Actions integration. The document outline (Installation; Quickstart; Features at a glance; Why it exists) is fully present in the visible content with no missing sections to flag as absent.
The README's Table of Contents lists 'Features at a glance' and 'Why it exists', but neither section appears in the visible text (only Installation, Quickstart, Features at a glance is shown).README.md
The GitHub Actions example uses .NET 10 file-based apps and references the official repository, but there is no link to the main getting-started.html.docs/overview/github-actions.md
Resolve the 1 The README's Table of Contents lists 'Features at a glance' and 'Why it… finding(s) in Documentation Quality — start with README.md. — One of this dimension's main actionable groups (1 recommendation-level).
Resolve the 1 The GitHub Actions example uses .NET 10 file-based apps and references… finding(s) in Documentation Quality — start with github-actions.md. — One of this dimension's main actionable groups (1 recommendation-level).
Detailed fixes: d19_recommendation.md · top locations in Appendix A, every location in findings.md.
What it measures: Whether architecture decisions are recorded well (context, decision, consequences).
Method: Per-ADR judgment by language model at low temperature with two-pass stability; confidence is share of ADRs evaluated; enforcement-field presence detected deterministically. Advisory.
What it measures: Whether names — types, methods, variables — are clear and consistent.
Method: Judged by language model at low temperature (0.0-0.1) on a deterministic random symbol sample (fixed size, not exhaustive), with disclosed confidence band. Advisory, sampled.
0 naming inconsistencies across 200 sampled symbols.
✓ On the Gold path — maintain.
Detailed fixes: d21_recommendation.md.
Do you agree with this assessment?
D24 · Comment Value / 10Strong◐ Sampled · advisory
What it measures: Whether comments are worth it — explaining WHY (valuable) rather than WHAT (redundant).
Method: Judged by language model at low temperature (0.0-0.1) on deterministically sampled inline comments with surrounding code; findings verified back to sampled comments by substring match. Advisory, sampled.
16 valuable / 1 redundant across 52 sampled comments; 1 shown with locations.
redundant commentsrc/FFlow/Steps/IfStep.cs:74
What to do
Resolve the 1 redundant comment finding(s) in Comment Value — start with IfStep.cs. — One of this dimension's main actionable groups (1 recommendation-level).
Detailed fixes: d24_recommendation.md · top locations in Appendix A, every location in findings.md.
0 of 19 projects flagged as possibly oversized/incoherent.
✓ On the Gold path — maintain.
Detailed fixes: d26_recommendation.md.
Do you agree with this assessment?
D27 · Navigability8.1 / 10Strong✓ Tool-verified
What it measures: How far you must trace to follow a call — low indirection and co-located slices read easier.
Method: Call indirection (interface hops, cross-namespace calls, slice-locality scaled) over a sampled set of method invocations, size-aware baseline. Sampled; confidence discounted by symbol-resolution gaps.
Coverage: Slice locality from the first namespace segments, SAMPLED (≤400 methods) — not exhaustive.
93 % of calls cross a namespace and 14 % go through an interface, but 95 % of collaborators are co-located — so a call's collaborators sit together and tracing stays easy. Baseline: medium — clean/modular boundaries expected.
What to do
Improve Navigability — currently 8.1/10. — 93 % of calls cross a namespace and 14 % go through an interface, but 95 % of collaborators are co-located — so a call's collaborators sit together and tracing stays easy. Baseline: medium — clean/modular boundaries expected.
What it measures: Whether any secrets were ever committed — scanned across the full git history, not just now.
Method: Git-history secret scan via gitleaks detect over full history in an isolated checkout; each match flagged High. Exhaustive; degrades cleanly when tool absent.
What it measures: Real static-analysis (SAST) findings — likely security bugs in the code, any language.
Method: Polyglot static analysis via semgrep across the repo using the pinned, image-baked p/security-audit + p/owasp-top-ten rulesets (no scan-time registry fetch); severity rules (ERROR/WARNING/INFO) map to a full-band severity-weighted score. Exhaustive, deterministic; degrades on parse failure.
Coverage: semgrep pattern rules over all files — exhaustive for the rule set, blind to classes of bug without a rule (clean = no rule matched).
High: github-actions-mutable-action-tag · ×7.github/workflows/cicd.yml:18detected by semgrep finding
What to do
Resolve the 7 High finding(s) in Static Analysis (SAST) — start with docs.yml (4), cicd.yml (3). — One of this dimension's main actionable groups (7 issue-level).
Detailed fixes: d29_recommendation.md · top locations in Appendix A, every location in findings.md.
What it measures: Whether any dependencies have known published vulnerabilities (CVEs), direct or transitive.
Method: NuGet CVE scan via dotnet list package --vulnerable including transitive; severity tally (Critical/High/Medium/Low) to 0-10 tight normalizer. Exhaustive, deterministic; degrades when absent.
What it measures: Whether anyone still has living knowledge of each file, or it has been orphaned — last understood long ago by someone now gone quiet. The sibling of the bus factor: D16 asks who owns it, D34 asks whether anyone still knows it.
Method: File orphaning as total living-knowledge decay below one focused-commit's worth within a year, computed per-file from the D16 decay model. Exhaustive, deterministic over fixed history.
12 of 57 significant source file(s) are orphaned — their living knowledge has decayed to nothing, so no one currently understands them. The largest is src/FFlow.Cli/Commands/DoctorCommand.cs.
Further orphaned files (smaller)
What to do
Resolve the 1 Further orphaned files (smaller) finding(s) in Knowledge Freshness. — One of this dimension's main actionable groups (1 recommendation-level).
Detailed fixes: d34_recommendation.md · top locations in Appendix A, every location in findings.md.
What it measures: Whether files that change together actually belong together — pairs that repeatedly co-change in git history despite having no explicit code dependency, surfacing the hidden/logical coupling (and boundaries in the wrong place) a static scan can't see.
Method: Pairwise co-occurrence over the per-commit file sets in git history (production source only — tests and generated dropped): Degree-of-Coupling = shared ÷ min individual revisions, reported above noise floors (each file ≥10 revisions, ≥5 shared commits, ≥50% strength); sweeping commits excluded. Deterministic over fixed history.
Coverage: Population: PRODUCTION source files only — test and generated files are dropped before pairing, so a class co-changing with its own test (trivially ~100%) can't drown the real production↔production coupling. Pairs ranked by Degree-of-Coupling; coupling through a build step, config, or non-source file isn't seen.
What it measures: Whether the build pipeline provides supply-chain integrity — generated provenance/attestation, signed artifacts (cosign/sigstore), an SBOM, and pinned build actions. Presence of the configuration, not a runtime guarantee.
Method: Supply-chain provenance/signing read deterministically from CI/build config (.github/workflows, .gitlab-ci.yml, azure-pipelines, Jenkinsfile, .circleci) + the release surface: four signals — generated provenance/attestation (SLSA/in-toto/actions-attest), artifact signing (cosign/sigstore/gitsign), an SBOM (syft/sbom-action/*.spdx.json/*.cdx.json), and SHA-pinned build actions — scored 10·present/denom. NotApplicable without a build pipeline. Detects configuration presence, not runtime enforcement.
Resolve the 1 Unpinned build actions finding(s) in Supply-chain Provenance & Signing. — One of this dimension's main actionable groups (1 warning-level).
Resolve the 1 PR-triggered workflow without a permissions block finding(s) in Supply-chain Provenance & Signing. — One of this dimension's main actionable groups (1 warning-level).
Resolve the 1 No build provenance finding(s) in Supply-chain Provenance & Signing. — One of this dimension's main actionable groups (1 recommendation-level).
Detailed fixes: d36_recommendation.md · top locations in Appendix A, every location in findings.md.
Do you agree with this assessment?
D39 · IL Efficiency9.7 / 10Exemplary✓ Tool-verified
Method: IL instruction count per method, read from the BUILT first-party assemblies via Mono.Cecil (the target is compiled on a deep run); scored on the fraction of methods whose emitted IL body exceeds the size threshold. Sees compiler-generated bloat source can't; not-applicable when the target fails to build. Deterministic.
Other · Architecture — Whether any singleton service captures a scoped/transient dependency — a silent lifetime/threading bug.
Method: Roslyn scan: DI registrations parsed from AddSingleton/Scoped/Transient; each singleton checked for captured shorter-lifetime dependencies. Exhaustive, deterministic.
Other · Architecture — How the codebase splits by code ROLE — domain, application, infrastructure, test, generated. The significance map behind the knowledge/coupling weighting, and a DDD signal in its own right: a thin domain core under fat infrastructure is the anemic-domain smell, quantified.
Method: Roslyn line-count by code ROLE: every source file classified Domain/Application/Infrastructure/Test/Generated by namespace + path convention (the shared CodeRoleClassifier), then significant lines summed per role. Deterministic; the advisory score is the business-logic (domain+application) share of production code.
Coverage: Population: ALL source files, each bucketed into ONE of five roles (Domain/Application/Infrastructure/Test/Generated) by namespace + path convention — a file whose layer isn't named in the convention falls to Application (the neutral default), and the split is line-count, not semantic depth or business value.
What to do
The domain core is a small share of production code — check that business logic isn't leaking into the application/infrastructure layers (a thin domain is the anemic-domain smell).
Other · Architecture — Whether singleton services avoid mutable shared instance state that concurrent callers would race on.
Method: Roslyn scan: singleton field mutations unguarded by lock or Interlocked, per type; syntax-based guard detection. Deterministic, traceable per field.
`InMemoryFlowScheduleStore` is a singleton (one shared instance) but mutates instance state outside any lock (_scheduledWorkflows; e.g. `_scheduledWorkflows` at line 15). — InMemoryFlowScheduleStore.cs:7
What to do
Keep singletons stateless or back their state with thread-safe types (Concurrent*/Immutable*); otherwise concurrent callers race.
Other · Architecture — Whether the project-reference graph is acyclic (cycles block independent build/deploy and signal eroding boundaries).
Method: Project reference cycles via elementary-DFS over real .csproj references, using the engine shared with D5/D7; cyclic versus acyclic. Exhaustive, deterministic.
Other · Architecture — Whether dependencies point inward (Domain ← Application ← Infrastructure/Web) — the clean-architecture dependency rule, checked across the project graph.
Method: Layer violations by name-segment inference (Domain/Core to Application to Infrastructure/Web) over the project-reference graph. Exhaustive over all projects, deterministic.
Other · Architecture — Whether the codebase has a recognisable, scale-appropriate structure (a named architectural style, or modular enough for its size) rather than being an ad-hoc ball of mud.
Method: Roslyn plus csproj analysis: architecture style detection (DDD, clean, vertical-slice, CQRS) and structure fitness for repo size. Deterministic.
Other · Architecture — Whether interfaces stay focused rather than fat — the Interface-Segregation principle (SOLID 'I').
Method: Roslyn scan: public interface member counts; fat-interface threshold (over 15 members) flagged per type. Deterministic, type-level.
Do you agree with this assessment?
AX8 · Test isolation10.0 / 10Exemplary✓ Tool-verified
Other · Architecture — Whether production projects stay free of references to test projects — tests may depend on production, never the reverse.
Method: Csproj graph: each production project checked for references to test projects (identified by test-framework presence, not name). Zero violations is clean. Deterministic.
Other · Code Health — Unreviewed-generation residue: shipped members still throwing NotImplementedException, and placeholder string literals left in non-test, non-generated code. Scored as a quality signature, never as a claim about authorship.
Method: Roslyn syntax scan: NotImplementedException throws and placeholder string literals in non-test, non-generated shipped code. Deterministic, code-shape signature.
Other · Code Health — Unfinished work detected by code SHAPE, not keywords: members that only throw a "not implemented" exception, methods that take inputs and return a constant, async methods that never await, dead `if (false)` / `#if false` branches, and skeleton types most of whose members are holes. A real, objective slice of technical debt.
Maturity · Maturity — Whether the repo and its projects have a README, and whether it's substantive and current.
Method: Filesystem scan: README presence, word count, and headings for depth; git history for staleness. Exhaustive across root and project dirs, deterministic.
What to do
Add an 'Architecture' / 'How it works' section to the root README — the high-level shape.
Add a README to the 19 of 19 project(s) that lack one — worth up to 2 pts.
Maturity · Maturity — Whether key decisions (ADRs) and the high-level shape (C4/diagrams) are written down.
Method: Filesystem scan: ADR folder/naming conventions or content, plus Mermaid/PlantUML/C4/architecture.md discovery. Exhaustive, deterministic.
No Architecture Decision Records found — no conventional ADR directory, no `NNNN-title.md` documents and nothing ADR-shaped by content. Design rationale recorded elsewhere (a design-notes tree, a mailing list, pull-request discussion) is not visible to this check and is not re-findable per decision, so a future maintainer cannot ask why one choice was made and get an answer.
What to do
Record significant decisions one document per decision — dated, stating the context, the decision and its consequences — and keep them together wherever your design docs already live (a conventional `docs/adr/` tree with `NNNN-title.md` names is the most discoverable form).
Maturity · Maturity — Whether the README actually describes the code that exists (LLM-judged, advisory).
Method: Judged by language model at low temperature: README accuracy versus actual projects, within a disclosed tolerance. Advisory, not a measured number.
Readiness · Readiness — Whether an automated pipeline builds and tests every change.
Method: Filesystem scan: CI workflow files (.github/workflows, .gitlab-ci.yml, etc.) for build and test stages. Exhaustive, deterministic.
Do you agree with this assessment?
P10 · Library API & versioning6.0 / 10Adequate✓ Tool-verified
Readiness · Readiness — For a library: a deliberate (small) public API surface and explicit semantic versioning so consumers can depend on it safely.
Method: Roslyn scan: public API surface area and semantic-versioning markers (SemVer attributes, changelog entries) for libraries. Exhaustive, deterministic.
157/187 types (84%) are public. For a library, every public type is a stability contract — make internal-by-default and expose only the intended API.
What to do
Make types internal by default; expose only the deliberate public API so internals can change without breaking consumers.
Do you agree with this assessment?
P2 · Observability4.4 / 10Weak✓ Tool-verified
Readiness · Readiness — Whether the code is diagnosable in production — structured logging, tracing/metrics, health checks.
Only 1/7 service-like projects use logging (pure contract/DTO projects are excluded — they have nothing to log). Of those 7, 0 ship a process this repository operates; the rest are libraries their consumer hosts, where the logging decision belongs to the host.
What to do
Extend structured logging across the projects you operate, and give the library ones a diagnostics seam instead — an `EventSource`/`ActivitySource` the host can subscribe to, or an optional logger on your options object — rather than taking a logging dependency on your consumers' behalf.
Consider OpenTelemetry tracing/metrics and a health-check endpoint for operability.
Readiness · Readiness — Whether SAST, secret/dependency scanning and performance benchmarking are wired in (presence, not runtime).
Method: Filesystem scan: SAST configuration, dependency-update automation, secret scanning, and a benchmark harness or benchmark step — in this repository's own ecosystem. Exhaustive, deterministic.
No static application security testing detected. For this repository's stack, add CodeQL's csharp pack (it analyses VB.NET too), or a security analyzer package (or `semgrep --config=auto`, which runs on any language) as a CI step.
What to do
Add a SAST step to CI running what this repository's stack ships: CodeQL's csharp pack (it analyses VB.NET too), or a security analyzer package — or `semgrep --config=auto`, which runs on any language — so a security regression fails the build instead of landing.
Enable Dependabot/Renovate or a dependency-review gate.
Add gitleaks/trufflehog in CI to block PRs that introduce committed secrets.
Readiness · Readiness — Whether releases are automated and safely reversible (probes, rolling updates, approval gates) — from manifests/pipeline files, not the live environment.
Method: Filesystem scan: deployment manifests/IaC (K8s YAML, Helm, Terraform) for rolling updates, probes, approval gates, migration hooks. Exhaustive, deterministic.
Deployment automation exists but no readiness/liveness probes, rolling-update strategy, lifecycle hooks or migration job were evidenced — a bad release is harder to detect and reverse.
What to do
Add readiness/liveness probes and a rolling-update (or blue/green) strategy so a bad release is caught and rolled back automatically.
The pipeline declares a deployment environment, but whether required reviewers / protection rules are attached to it lives in repository settings we cannot read — confirm the gate is enforced before production promotion.
Readiness · Performance — Whether the library protects its performance with benchmarks — a benchmark suite, allocation/memory measurement, and (ideally) a CI gate. Presence is credited as a bonus, never a deduction.
Method: Repo + source scan: BenchmarkDotNet referenced (csproj/source), [Benchmark]/[MemoryDiagnoser] attribute counts, and a benchmark step in CI — scored as a bonus ladder (absence is neutral, never a deduction). Deterministic, presence detection.
No benchmark suite was found. Where code is performance-sensitive, a benchmark guards against silent regressions — but it's a bonus here, not a deduction.
What to do
Add a benchmarking harness for the hot paths and run it in CI to catch regressions (for .NET, a BenchmarkDotNet project with [MemoryDiagnoser] to track allocations).
Readiness · Performance — Whether the code is written to minimise allocations so it doesn't pressure its host's memory manager — buffer/slice views over copies, object pooling, stack or value-type allocation, and buffer writers. Reward-only: credited where present, never penalised where a simpler style is fine.
No Span/Memory, pooling (ArrayPool/ObjectPool), stackalloc, ValueTask or buffer-writer usage was found. If this library sits on a hot path, these reduce the GC pressure it puts on its host — a bonus, not a requirement.
What to do
On hot paths, prefer Span<T>/ReadOnlySpan<T>, ArrayPool<T>, stackalloc and ValueTask to cut allocations a consumer would otherwise inherit.
Readiness · Performance — Whether asynchronous code keeps its host responsive — a library awaits with ConfigureAwait(false) (so it never captures and stalls the host's context) and avoids sync-over-async blocking (.Wait()/.GetAwaiter().GetResult()) that wastes threads and risks deadlock.
Method: Production-source scan: sync-over-async blocking (.Wait()/.GetAwaiter().GetResult()) counted everywhere, and — for a library with ≥5 awaits — the share of awaits using ConfigureAwait(false). Deterministic, syntax/text detection.
3 blocking call(s) on async work (.Wait()/.GetAwaiter().GetResult()) — these waste a thread and can deadlock in a consumer with a synchronization context.
Only 52/68 awaits use ConfigureAwait(false). A library that captures the caller's context can stall or deadlock its host — the classic way a dependency drags an app down.
What to do
Make the call chain async end-to-end and await it — never block on a Task with .Wait()/.GetAwaiter().GetResult() in library code.
In library code, append .ConfigureAwait(false) to every await (or set <ConfigureAwait>false</ConfigureAwait> / use the analyzer CA2007) so the library never captures the host's context.
Other · Code Health — Whether the code avoids sync-over-async (deadlock-prone blocking on tasks) and async void.
Method: Roslyn syntax scan: async methods scanned for .Wait()/.GetAwaiter().GetResult() and async-void outside event handlers. Deterministic, hard fact per invocation.
Blocking on a Task with `.Wait()`/`.GetAwaiter().GetResult()` can deadlock (and wastes a thread). Prefer awaiting it: make the caller `async` and `await` instead. Where a synchronous entry point must stay — a public sync API you cannot break, or a process entry point that must not return until the work finishes — the block belongs in ONE documented bridge and never inside code that is already async; and where it already is that bridge, give the wait a TIMEOUT so a hung task fails the call instead of hanging the process. (×3) — FlowScheduledWorkflowBuilder.cs:20, FlowScheduledWorkflowBuilder.cs:26, FlowScheduledWorkflowBuilder.cs:32
Other · Code Health — Whether async methods accept a CancellationToken so work can be cancelled (adoption curve).
Method: Roslyn scan: every async method (excluding framework-fixed overrides/Blazor handlers) checked for CancellationToken parameter presence. Deterministic, adoption percentage.
Only 35/37 async methods accept a CancellationToken, so in-flight work can't be stopped early when the caller gives up — whatever ends it in your host (shutdown signal, timeout, abandoned request, user cancel). Thread a token through the call chain and honour it at each await and loop; where a method genuinely cannot be interrupted, omitting it is a deliberate choice — judge against your hosting model.
No CancellationToken parameter — this work can't be stopped early once started. (×2) — FileFlowScheduleStore.cs:29, FileFlowScheduleStore.cs:53
What to do
Thread a CancellationToken through async methods so work stops promptly on cancellation.
Other · Code Health — Whether exceptions are handled rather than silently swallowed or rethrown with lost stack traces.
Method: Roslyn syntax scan: every catch clause counted; empty catches and bare rethrows flagged. Population is all catch clauses, not estimated. Deterministic, hard fact.
Other · Code Health — Whether log calls use message templates (queryable) rather than interpolated strings.
Method: Roslyn syntax scan: every log call-site counted; interpolated-string first-argument violations flagged. Population is all log calls, not estimated. Deterministic.
Other · Code Health — Whether nullable reference types are enabled and not undermined by heavy `!` suppression.
Method: Roslyn compiler-options scan: NullableContextOptions per project; null-forgiving (!) suppression density per 1k syntax nodes. Deterministic, adoption plus suppression penalty.
~0.4 `!` suppressions per 1k syntax nodes — 17 suppression(s) across the 41451 syntax node(s) in code where nullable warnings are ENABLED, which is the only code a `!` can suppress anything in (a `!` under `#nullable disable` is inert and is not counted, and its file's nodes are not in the denominator). Each one tells the compiler to trust you about null, suppressing the very safety NRTs provide.
What to do
Enable <Nullable>enable</Nullable> across all projects and resolve warnings rather than suppressing with `!`.
Do you agree with this assessment?
Reference — by lens
The score is the rank-weighted fold of these lenses (worst-heaviest), each including its meta-dimensions; a lens with a Critical contributor is capped at Fair (its band reads "gated by …") and is never the strongest area however high its average.
Not included — 39 check(s) not relevant to this codebase
These checks had nothing to measure here (no tests, no git history, the codebase is small, or the architecture style doesn't apply), so they're omitted above rather than scored low.
AC1 Text alternatives — No web markup found — accessibility is not applicable to this repository.
AC2 Forms & labels — No web markup found — accessibility is not applicable to this repository.
AC3 Page structure — No web markup found — accessibility is not applicable to this repository.
AC4 Keyboard semantics — No web markup found — accessibility is not applicable to this repository.
AC5 ARIA correctness — No web markup found — accessibility is not applicable to this repository.
AC6 Visual & motion safety — No web markup found — accessibility is not applicable to this repository.
AC7 A11y enforcement — No web markup found — accessibility is not applicable to this repository.
AX7 Slice cohesion — not applicable — not a vertical-slice architecture
AX9 CQS / query purity — no CQRS query handlers detected — query purity is not applicable to this codebase
AXB2 Runtime readiness — Advisory — this card reports evidence and never carries a score, so there is nothing missing here.
C1 Data Protection — No personal data detected in the analyzed source — no PII-typed entity/column names (Email, FirstName, DateOfBirth, …), no ASP.NET Identity / user-account model, and no stored user credentials. GDPR data-protection controls are therefore N/A here. If this is intentional, record the no-PII posture in an ADR; if the app does process personal data, name those fields conventionally so this dimension activates.
C2 Access Controls — No access-control surface detected in the analyzed source — no web/app surface to authorize (no HTTP API or web-UI project) and no authorization code at all (no [Authorize]/policies, no imperative guard methods). Access control is therefore N/A here — this is a library/CLI, which is authorized by its CALLER, not by itself. If this codebase grows request handlers, the dimension reactivates and a default-deny posture is expected then.
C3 Audit Trail — No personal data detected in the analyzed source — no PII-typed entity/column names (Email, FirstName, DateOfBirth, …), no ASP.NET Identity / user-account model, and no stored user credentials. GDPR data-protection controls are therefore N/A here. If this is intentional, record the no-PII posture in an ADR; if the app does process personal data, name those fields conventionally so this dimension activates.
C4 Data Retention — No personal data detected in the analyzed source — no PII-typed entity/column names (Email, FirstName, DateOfBirth, …), no ASP.NET Identity / user-account model, and no stored user credentials. GDPR data-protection controls are therefore N/A here. If this is intentional, record the no-PII posture in an ADR; if the app does process personal data, name those fields conventionally so this dimension activates.
C5 Data-Subject Rights — No personal data detected in the analyzed source — no PII-typed entity/column names (Email, FirstName, DateOfBirth, …), no ASP.NET Identity / user-account model, and no stored user credentials. GDPR data-protection controls are therefore N/A here. If this is intentional, record the no-PII posture in an ADR; if the app does process personal data, name those fields conventionally so this dimension activates.
D22 Internal API Consistency — No exposed public API
D23 Boundary Type-Coupling — Bounded contexts not declared
D25 ADR Conformance — no ADRs to check
D31 IaC & Container Security — No Infrastructure-as-Code or container manifests found (Dockerfile, Terraform, Kubernetes/Helm, CloudFormation); nothing to scan.
D32 Data Compliance (PII/GDPR) — No PII/GDPR-handling patterns detected (p/gdpr ruleset) — no data-compliance surface to assess.
D33 JS/npm Dependency Vulnerabilities — No JS/npm manifest or lockfile found outside build output (package.json, package-lock.json, yarn.lock, pnpm-lock.yaml, bun.lockb); no JS dependencies to scan.
D37 Vulnerability-disclosure Policy — No vulnerability-disclosure policy file found (SECURITY.md/.markdown/.rst/.txt at root or under .github/.forgejo/.gitea/docs, .well-known/security.txt). A coordinated-disclosure policy may live off-repo, so this is not evidenced rather than failed.
D38 OSV Dependency Vulnerabilities — No supported non-.NET dependency lockfile found outside build output (npm package-lock/yarn/pnpm/bun, Go go.mod, Rust Cargo.lock, Maven pom.xml, Gradle lockfiles, Python requirements.txt/poetry.lock/Pipfile.lock/pdm.lock, PHP composer.lock, Ruby Gemfile.lock, Elixir mix.lock, Dart pubspec.lock, Swift Package.resolved); nothing for OSV to scan. A NuGet-only repo stays NotApplicable — .NET CVEs are D30's domain.
D40 Network Egress Confinement — No Kubernetes/orchestration workloads found in the repository manifests; network egress policy is a cluster-native control that may live at the platform/firewall layer, so there is nothing to assess here.
D41 Kernel & Syscall Confinement — No Kubernetes/orchestration workloads found in the repository manifests; seccomp/AppArmor/SELinux confinement is a workload-level control, so there is nothing to assess here.
D42 Runtime Threat Enforcement — No Kubernetes/orchestration workloads found in the repository manifests; runtime threat-detection and admission-control policy are cluster-level controls, so there is nothing to assess here.
D7 Architectural Integrity — no checkable ADRs and no dependency cycles — architectural integrity not assessed
DM1 Domain Modelling — not scored — this repository shows none of the 3 signals this check looks for
ED1 Event-Driven — not scored — this repository shows only 1 of the 3 signals this check looks for (1 event handler(s))
ED5 Idempotency — no mutating command handlers or message consumers detected — idempotency check not applicable
ES1 Event Sourcing — not scored — this repository shows none of the 3 signals this check looks for
P12 CI test-gate honesty — Reported, not scored — and nothing was matched here. The coverage check applies to any stack, but the checks for excluded tests, skipped tests and sleep-based synchronisation currently recognise only some ecosystems' test-runner idioms, so on a repository built with another stack the zeros below mean 'not checked', not 'clean'.
P5 DR & Backup — not evidenced — repo shows no backup/RTO/RPO controls; absence of evidence is not evidence of a working control
P8 Schema migrations — no EF Core usage detected
P9 Domain vs controller coverage — coverage data present but no domain-layer files were identified (no /Domain//Aggregates/ paths)
S1 Web-Security Posture — No web surface detected in the analyzed source — no HTTP API or web-UI project (no controllers/minimal-API endpoints, no Razor/Blazor views) and no web middleware (HTTPS redirection, HSTS, security headers, cookies). Transport security, security headers, secure cookies, CSRF/input-validation and middleware-order controls are therefore N/A here — this is a library/CLI/worker, not a web app. Crypto hygiene was still checked and found nothing to flag. If this codebase becomes web-facing, the dimension reactivates automatically.
SC1 Supply-chain hygiene — Advisory — this card reports evidence and never carries a score, so there is nothing missing here.
X6 Hand-rolled structured-format parsing — Reported, not scored — this card publishes what it found rather than grading it. Its content is the findings and the key metric above.
X7 Silent fallback defaults — Reported, not scored — this card publishes what it found rather than grading it. Its content is the findings and the key metric above.
Appendix A — Findings (grouped)
The findings behind the scores, grouped by severity, then by dimension and kind. The high-severity issues are enumerated in full below; items per group are capped at 25 with any overflow stated explicitly per group, never silently truncated. The complete machine-readable list of every finding (all severities) is the companion findings.md in this report's bundle.
High: github-actions-mutable-action-tag .github/workflows/cicd.yml:18— GitHub Actions step uses a mutable tag or branch reference. Tags and branch names can be silently repointed by the action owner, enabling supply-chain attacks — as seen in the trivy-action and kics-github-action compromises. Pin the reference to a full 40-character commit SHA instead, e.g. `uses: actions/checkout@<40-character SHA>`. This step references `actions/checkout@v3`; resolve the SHA it points at today with `gh api repos/actions/checkout/commits/v3 --jq .sha`.
High: github-actions-mutable-action-tag .github/workflows/cicd.yml:21— GitHub Actions step uses a mutable tag or branch reference. Tags and branch names can be silently repointed by the action owner, enabling supply-chain attacks — as seen in the trivy-action and kics-github-action compromises. Pin the reference to a full 40-character commit SHA instead, e.g. `uses: actions/setup-dotnet@<40-character SHA>`. This step references `actions/setup-dotnet@v4`; resolve the SHA it points at today with `gh api repos/actions/setup-dotnet/commits/v4 --jq .sha`.
High: github-actions-mutable-action-tag .github/workflows/cicd.yml:26— GitHub Actions step uses a mutable tag or branch reference. Tags and branch names can be silently repointed by the action owner, enabling supply-chain attacks — as seen in the trivy-action and kics-github-action compromises. Pin the reference to a full 40-character commit SHA instead, e.g. `uses: actions/setup-dotnet@<40-character SHA>`. This step references `actions/setup-dotnet@v4`; resolve the SHA it points at today with `gh api repos/actions/setup-dotnet/commits/v4 --jq .sha`.
High: github-actions-mutable-action-tag .github/workflows/docs.yml:28— GitHub Actions step uses a mutable tag or branch reference. Tags and branch names can be silently repointed by the action owner, enabling supply-chain attacks — as seen in the trivy-action and kics-github-action compromises. Pin the reference to a full 40-character commit SHA instead, e.g. `uses: actions/checkout@<40-character SHA>`. This step references `actions/checkout@v3`; resolve the SHA it points at today with `gh api repos/actions/checkout/commits/v3 --jq .sha`.
High: github-actions-mutable-action-tag .github/workflows/docs.yml:30— GitHub Actions step uses a mutable tag or branch reference. Tags and branch names can be silently repointed by the action owner, enabling supply-chain attacks — as seen in the trivy-action and kics-github-action compromises. Pin the reference to a full 40-character commit SHA instead, e.g. `uses: actions/setup-dotnet@<40-character SHA>`. This step references `actions/setup-dotnet@v3`; resolve the SHA it points at today with `gh api repos/actions/setup-dotnet/commits/v3 --jq .sha`.
High: github-actions-mutable-action-tag .github/workflows/docs.yml:41— GitHub Actions step uses a mutable tag or branch reference. Tags and branch names can be silently repointed by the action owner, enabling supply-chain attacks — as seen in the trivy-action and kics-github-action compromises. Pin the reference to a full 40-character commit SHA instead, e.g. `uses: actions/upload-pages-artifact@<40-character SHA>`. This step references `actions/upload-pages-artifact@v3`; resolve the SHA it points at today with `gh api repos/actions/upload-pages-artifact/commits/v3 --jq .sha`.
High: github-actions-mutable-action-tag .github/workflows/docs.yml:46— GitHub Actions step uses a mutable tag or branch reference. Tags and branch names can be silently repointed by the action owner, enabling supply-chain attacks — as seen in the trivy-action and kics-github-action compromises. Pin the reference to a full 40-character commit SHA instead, e.g. `uses: actions/deploy-pages@<40-character SHA>`. This step references `actions/deploy-pages@v4`; resolve the SHA it points at today with `gh api repos/actions/deploy-pages/commits/v4 --jq .sha`.
NoWarnInCsproj repeated across 13 files src/FFlow/FFlow.csproj:13— The identical NoWarnInCsproj (`1591`) appears in 13 files (13 occurrences) — a single repo-wide policy (e.g. a Directory.Build.props decision or an idiomatic suppression), not 13 independent debts. Decide it once centrally rather than file-by-file. (Every occurrence still counts toward the score and metrics.)
Change coupling: HelloWorkflow.cs ↔ Program.cs src/FFlow.Demo/HelloWorkflow.cs— `src/FFlow.Demo/HelloWorkflow.cs` and `src/FFlow.Demo/Program.cs` change together 80% of the time (8 of the 10 commits that touched the less-changed of the two, renames followed). They sit in the same directory, and in this ecosystem sibling files there normally share one namespace/package — so a direct reference between them needs no import and this pass cannot see whether one exists. Read the pair before acting: if one file only DECLARES what the other consumes (a constants/types file beside its user), the co-change is definitional and the question is whether the split earns its keep; if they duplicate structure, extract the common part into a shared function or type they both call; if neither holds, the coupling is hidden and worth breaking.
Change coupling: HelloStep.cs ↔ Program.cs src/FFlow.Demo/HelloStep.cs— `src/FFlow.Demo/HelloStep.cs` and `src/FFlow.Demo/Program.cs` change together 64% of the time (7 of the 11 commits that touched the less-changed of the two, renames followed). They sit in the same directory, and in this ecosystem sibling files there normally share one namespace/package — so a direct reference between them needs no import and this pass cannot see whether one exists. Read the pair before acting: if one file only DECLARES what the other consumes (a constants/types file beside its user), the co-change is definitional and the question is whether the split earns its keep; if they duplicate structure, extract the common part into a shared function or type they both call; if neither holds, the coupling is hidden and worth breaking.
Duplicated block (15 lines × 2) src/FFlow/FFlowBuilderStepConfigurationExtensions.cs:11— src/FFlow/FFlowBuilderStepConfigurationExtensions.cs:11-25 | src/FFlow/FFlowBuilderStepConfigurationExtensions.cs:46-60 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited.
Duplicated block (15 lines × 2) src/FFlow.Steps.DotNet/Internals.cs:64— src/FFlow.Steps.DotNet/Internals.cs:64-78 | src/FFlow.Steps.Shell/Internals.cs:26-40 — the copies span different directories, so extracting a shared function means choosing where it lives: put it somewhere both call sites can already reach — a location they all depend on today, or a new shared one if there is none — and call it from each site; until then, every change has to be made twice. Read the line range as the matched WINDOW rather than a finished unit: at `src/FFlow.Steps.DotNet/Internals.cs:64` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that. The matched lines also transfer control out of the body holding them, which cannot survive a move into a called unit unchanged: have the extracted unit return that decision and let each site act on it.
Duplicated block (6 lines × 2) src/FFlow.Steps.DotNet/DotnetBuildStep.cs:132— src/FFlow.Steps.DotNet/DotnetBuildStep.cs:132-137 | src/FFlow.Steps.DotNet/DotnetPublishStep.cs:132-137 — the copies sit in sibling files of one directory: extract the block into a single shared function in that directory and call it from each site, so a change lands once. Read the line range as the matched WINDOW rather than a finished unit: at `src/FFlow.Steps.DotNet/DotnetBuildStep.cs:132` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that. The matched lines also transfer control out of the body holding them, which cannot survive a move into a called unit unchanged: have the extracted unit return that decision and let each site act on it.
Duplicated block (6 lines × 2) src/FFlow.Steps.DotNet/DotnetPackStep.cs:102— src/FFlow.Steps.DotNet/DotnetPackStep.cs:102-107 | src/FFlow.Steps.DotNet/DotnetPublishStep.cs:120-125 — the copies sit in sibling files of one directory: extract the block into a single shared function in that directory and call it from each site, so a change lands once.
CRAP 42: ForEachStep.ExecuteAsync src/FFlow/Steps/ForEachStep.cs:29— Cyclomatic 6 with 0.0% file coverage — too complex for how untested it is (CRAP = CC²·(1−cov)³ + CC; ≥30 needs tests or simplification).
CRAP 42: ForEachStep.Describe src/FFlow/Steps/ForEachStep.cs:54— Cyclomatic 6 with 0.0% file coverage — too complex for how untested it is (CRAP = CC²·(1−cov)³ + CC; ≥30 needs tests or simplification).
DotnetTestStep.BuildCommand (cyclomatic 32) src/FFlow.Steps.DotNet/DotnetTestStep.cs:159— DotnetTestStep.BuildCommand has cyclomatic complexity 32 (threshold 15). To reduce it, split the body: these branches sit side by side rather than nested inside one another, so extracting each one on its own would leave a function per branch. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.
DotnetPublishStep.BuildCommand (cyclomatic 24) src/FFlow.Steps.DotNet/DotnetPublishStep.cs:108— DotnetPublishStep.BuildCommand has cyclomatic complexity 24 (threshold 15). To reduce it, split the body: these branches sit side by side rather than nested inside one another, so extracting each one on its own would leave a function per branch. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.
DotnetBuildStep.BuildCommand (cyclomatic 23) src/FFlow.Steps.DotNet/DotnetBuildStep.cs:108— DotnetBuildStep.BuildCommand has cyclomatic complexity 23 (threshold 15). To reduce it, split the body: these branches sit side by side rather than nested inside one another, so extracting each one on its own would leave a function per branch. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.
DotnetRestoreStep.BuildCommand (cyclomatic 22) src/FFlow.Steps.DotNet/DotnetRestoreStep.cs:107— DotnetRestoreStep.BuildCommand has cyclomatic complexity 22 (threshold 15). To reduce it, split the body: these branches sit side by side rather than nested inside one another, so extracting each one on its own would leave a function per branch. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.
RunCommand.Execute (cyclomatic 20) src/FFlow.Cli/Commands/RunCommand.cs:17— RunCommand.Execute has cyclomatic complexity 20 (threshold 15). Of this number, 15 points are the body's own statements and 5 belong to one function literal inside it that branches. To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.
Workflow.RunAsync (cyclomatic 18) src/FFlow/Workflow.cs:68— Workflow.RunAsync has cyclomatic complexity 18 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.
DotnetPackStep.BuildCommand (cyclomatic 18) src/FFlow.Steps.DotNet/DotnetPackStep.cs:92— DotnetPackStep.BuildCommand has cyclomatic complexity 18 (threshold 15). To reduce it, split the body: these branches sit side by side rather than nested inside one another, so extracting each one on its own would leave a function per branch. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.
DotnetRunStep.BuildCommand (cyclomatic 18) src/FFlow.Steps.DotNet/DotnetRunStep.cs:89— DotnetRunStep.BuildCommand has cyclomatic complexity 18 (threshold 15). To reduce it, split the body: these branches sit side by side rather than nested inside one another, so extracting each one on its own would leave a function per branch. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.
HttpRequestStep.ExecuteAsync (cyclomatic 17) src/FFlow.Steps.Http/HttpRequestStep.cs:88— HttpRequestStep.ExecuteAsync has cyclomatic complexity 17 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.
CommandDispatcher.Dispatch (cyclomatic 16) src/FFlow.Cli/CommandDispatcher.cs:12— CommandDispatcher.Dispatch has cyclomatic complexity 16 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.
Monorepo: only 1 of 2 solutions was scored — This repository contains 2 .NET solutions, but a scan analyzes ONE. Every score, lens, and finding here reflects only `FFlow.sln` — the other 1 (`samples/FFlow.Samples.BasicServer/FFlow.Samples.BasicServer.sln`) were not analyzed and are not represented in the headline. To cover them, scan each solution as its own target and group them in a Solution or Product for a portfolio roll-up. If a secondary solution is an archived or vendored tree, declare it — `.gitattributes` (`path/** linguist-vendored`) or `.editorconfig` (`[path/**] generated_code = true`) — to exclude it from discovery the same way generated code is.
DotnetTestStep.BuildCommand (cognitive 31) src/FFlow.Steps.DotNet/DotnetTestStep.cs:159— DotnetTestStep.BuildCommand has cognitive complexity 31 (threshold 15). To reduce it, split the body: this score is breadth rather than depth — many checks laid out side by side rather than nested inside one another, so inverting conditions into early returns has nothing left to flatten. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.
Workflow.RunAsync (cognitive 29) src/FFlow/Workflow.cs:68— Workflow.RunAsync has cognitive complexity 29 (threshold 15). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
RunCommand.Execute (cognitive 27) src/FFlow.Cli/Commands/RunCommand.cs:17— RunCommand.Execute has cognitive complexity 27 (threshold 15). Of this number, 20 points are the body's own statements and 7 belong to one function literal inside it that branches. To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
FFlowScheduleRunner.ExecuteAsync (cognitive 25) src/FFlow.Scheduling/FFlowScheduleRunner.cs:28— FFlowScheduleRunner.ExecuteAsync has cognitive complexity 25 (threshold 15). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
HttpRequestStep.ExecuteAsync (cognitive 24) src/FFlow.Steps.Http/HttpRequestStep.cs:88— HttpRequestStep.ExecuteAsync has cognitive complexity 24 (threshold 15). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
DotnetBuildStep.BuildCommand (cognitive 23) src/FFlow.Steps.DotNet/DotnetBuildStep.cs:108— DotnetBuildStep.BuildCommand has cognitive complexity 23 (threshold 15). To reduce it, split the body: this score is breadth rather than depth — many checks laid out side by side rather than nested inside one another, so inverting conditions into early returns has nothing left to flatten. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.
DotnetPublishStep.BuildCommand (cognitive 23) src/FFlow.Steps.DotNet/DotnetPublishStep.cs:108— DotnetPublishStep.BuildCommand has cognitive complexity 23 (threshold 15). To reduce it, split the body: this score is breadth rather than depth — many checks laid out side by side rather than nested inside one another, so inverting conditions into early returns has nothing left to flatten. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.
CommandDispatcher.Dispatch (cognitive 23) src/FFlow.Cli/CommandDispatcher.cs:12— CommandDispatcher.Dispatch has cognitive complexity 23 (threshold 15). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
DotnetRunStep.BuildCommand (cognitive 22) src/FFlow.Steps.DotNet/DotnetRunStep.cs:89— DotnetRunStep.BuildCommand has cognitive complexity 22 (threshold 15). To reduce it, split the body: this score is breadth rather than depth — many checks laid out side by side rather than nested inside one another, so inverting conditions into early returns has nothing left to flatten. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.
DotnetRestoreStep.BuildCommand (cognitive 21) src/FFlow.Steps.DotNet/DotnetRestoreStep.cs:107— DotnetRestoreStep.BuildCommand has cognitive complexity 21 (threshold 15). To reduce it, split the body: this score is breadth rather than depth — many checks laid out side by side rather than nested inside one another, so inverting conditions into early returns has nothing left to flatten. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.
IWorkflowBuilderVisualizationExtensions.Describe (cognitive 17) src/FFlow/Visualization/IWorkflowBuilderVisualizationExtensions.cs:18— IWorkflowBuilderVisualizationExtensions.Describe has cognitive complexity 17 (threshold 15). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
DotnetPackStep.BuildCommand (cognitive 17) src/FFlow.Steps.DotNet/DotnetPackStep.cs:92— DotnetPackStep.BuildCommand has cognitive complexity 17 (threshold 15). To reduce it, split the body: this score is breadth rather than depth — many checks laid out side by side rather than nested inside one another, so inverting conditions into early returns has nothing left to flatten. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.
ForkStep.Describe (cognitive 16) src/FFlow/Steps/ForkStep.cs:53— ForkStep.Describe has cognitive complexity 16 (threshold 15). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
Change coupling clique: DotnetBuildStep.cs, DotnetRestoreStep.cs, DotnetTestStep.cs src/FFlow.Steps.DotNet/DotnetBuildStep.cs— 3 files — `src/FFlow.Steps.DotNet/DotnetBuildStep.cs`, `src/FFlow.Steps.DotNet/DotnetRestoreStep.cs`, `src/FFlow.Steps.DotNet/DotnetTestStep.cs` — all change together with no explicit dependency: a fully-connected co-change clique, not 3 separate couplings. They share one concern (thin parallel siblings over a common abstraction), so extract the shared part into ONE unit and the whole clique's coupling clears at once — you do not need to break each pair individually.
Unpinned build actions — CI references GitHub Actions by a floating ref (@main / @tag) rather than a pinned commit SHA, weakening build integrity. 10 floating ref(s) across 3 workflow file(s). Each floating ref is itemized at file:line by the SAST (D29) lens.
D36 · Supply-chain Provenance & Signing· PR-triggered workflow without a permissions block · ×1
PR-triggered workflow without a permissions block — 1 workflow(s) triggered by pull_request declare no `permissions:` block (ci-tests.yml) and so run with the repository's default GITHUB_TOKEN scope, while 1 sibling workflow in the same repository is already scoped. Pull-request runs build the least-trusted code in the repository; give each of these workflows its own least-privilege block — `permissions: {contents: read}` at the top of the workflow, widened per job only where a job genuinely writes.
Duplicated block (23 lines × 2) src/FFlow.Steps.Shell/RunCommandStep.cs:32— src/FFlow.Steps.Shell/RunCommandStep.cs:32-54 | src/FFlow.Steps.Shell/RunScriptRawStep.cs:49-71 — the copies sit in sibling files of one directory: extract the block into a single shared function in that directory and call it from each site, so a change lands once. Read the line range as the matched WINDOW rather than a finished unit: at `src/FFlow.Steps.Shell/RunCommandStep.cs:32` it does not close everything it opens, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (13 lines × 2) src/FFlow.Cli/Commands/RunCommand.cs:120— src/FFlow.Cli/Commands/RunCommand.cs:120-132 | src/FFlow.Cli/Commands/RunCommand.cs:137-149 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `src/FFlow.Cli/Commands/RunCommand.cs:120` it does not close everything it opens, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (10 lines × 2) src/FFlow.Steps.DotNet.SourceGenerators/IFlowContextExtensionGenerator.cs:32— src/FFlow.Steps.DotNet.SourceGenerators/IFlowContextExtensionGenerator.cs:32-41 | src/FFlow.Steps.DotNet.SourceGenerators/WorkflowBuilderExtensionGenerator.cs:34-43 — the copies sit in sibling files of one directory: extract the block into a single shared function in that directory and call it from each site, so a change lands once. Read the line range as the matched WINDOW rather than a finished unit: at `src/FFlow.Steps.DotNet.SourceGenerators/IFlowContextExtensionGenerator.cs:32` it does not close everything it opens, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (5 lines × 2) src/FFlow.Steps.DotNet/DotnetBuildStep.cs:109— src/FFlow.Steps.DotNet/DotnetBuildStep.cs:109-113 | src/FFlow.Steps.DotNet/DotnetPublishStep.cs:110-114 — the copies sit in sibling files of one directory: extract the block into a single shared function in that directory and call it from each site, so a change lands once.
CRAP 30: NotEmptyAttribute.NotEmptyAttribute.ctor src/FFlow.Validation/Annotations/NotEmptyAttribute.cs:10— Cyclomatic 5 with 0.0% file coverage — too complex for how untested it is (CRAP = CC²·(1−cov)³ + CC; ≥30 needs tests or simplification).
Recommendation — 11 finding(s)
D16 · Bus Factor· Small-team knowledge concentration · ×1
Small-team knowledge concentration — 39 file(s) are concentrated to one author — the ambient state with 2 active author(s), not 39 separate risks. The signal becomes meaningful as ownership spreads; no per-file action implied now.
D19 · Documentation Quality· The README's Table of Contents lists 'Features at a glance' and 'Why it exists', but neither section appears in the visible text (only Installation, Quickstart, Features at a glance is shown). · ×1
The README's Table of Contents lists 'Features at a glance' and 'Why it exists', but neither section appears in the visible text (only Installation, Quickstart, Features at a glance is shown). README.md— Verify that the unshown sections are present or add them if they were clipped.
D19 · Documentation Quality· The GitHub Actions example uses .NET 10 file-based apps and references the official repository, but there is no link to the main getting-started.html. · ×1
The GitHub Actions example uses .NET 10 file-based apps and references the official repository, but there is no link to the main getting-started.html. docs/overview/github-actions.md— Add a link from this doc to ./getting-started.html so readers can follow up on the quickstart.
No ADRs found — No ADRs found at common paths; consider documenting architectural decisions in Docs/ADL/ or similar.
D23 · Boundary Type-Coupling· Bounded contexts not declared · ×1
Bounded contexts not declared — At 10k LoC across 19 projects the codebase is large and multi-module, so explicit bounded contexts are needed. Name this codebase's bounded contexts (≥2 module groups, e.g. per subsystem) so cross-boundary type coupling can be assessed. Declare them in `.codehealth/config.yaml` at the repository root (create it if absent), mapping each context name to the module-path or namespace prefixes that belong to it — e.g. `architecture:` → `contexts:` → `Billing: ["src/billing", "Acme.Billing"]`, `Catalog: ["src/catalog", "Acme.Catalog"]`.
redundant comment src/FFlow/Steps/IfStep.cs:74— "TRUE BRANCH" — delete - restates the branch label; remove from code comments
D34 · Knowledge Freshness· Further orphaned files (smaller) · ×1
Further orphaned files (smaller) — 12 of 57 analysed file(s) have no living knowledge left — their last meaningful change has decayed away, so if one breaks, no one currently understands it (counted over production source files of roughly 100 lines or more, excluding tests, vendored, generated and example/demo trees, largest first). None is large enough to earn a read-through of its own, so this row stands in for the per-file rows rather than raising one each — largest first: src/FFlow.Cli/Commands/DoctorCommand.cs, src/FFlow.Cli/Commands/InitCommand.cs, src/FFlow/RetryPolicies/RetryPolicies.cs (and 9 more). Attach the read to the next change that touches one of them: have a second person review that change, and leave behind a short comment or test recording what the file is for, so the knowledge comes back at the cost of a change you were making anyway.
No build provenance — No SLSA provenance generation or build attestation found in CI — nothing binds a released artifact to the build that produced it, so a consumer cannot tell your artifact from a substituted one. On GitHub Actions, `actions/attest-build-provenance` (or slsa-github-generator) emits one from the job's own OIDC identity; elsewhere, run `cosign attest` over the released artifact from the release pipeline and publish the attestation beside it.
No artifact signing — No artifact signing found in CI — sign your released artifacts with whatever your ecosystem ships (a GPG/minisign detached signature — or `cosign sign-blob` — over the release archives, or over a checksum file published alongside them, Authenticode via signtool, or `dotnet nuget sign` for packages) so consumers can verify what you built.
D36 · Supply-chain Provenance & Signing· No SBOM · ×1
No SBOM — No SBOM generation or committed SBOM found — produce one with what your ecosystem ships (`sbom-tool generate` (install it with `dotnet tool install --global Microsoft.Sbom.DotNetTool`) or `dotnet CycloneDX` over the solution, `syft` (or `anchore/sbom-action` in CI) over the source tree or released image). Publish it as a release asset (`*.spdx.json` / `*.cdx.json`) so consumers can see what they are installing.
IL efficiency: 8 authored method(s) exceed the IL budget src/FFlow.Steps.DotNet/DotnetTestStep.cs:161— 8 of 632 first-party methods compile to oversized IL bodies (> 250 instructions); worst: FFlow.Steps.DotNet.DotnetTestStep.BuildCommand @ src/FFlow.Steps.DotNet/DotnetTestStep.cs:161, 589 IL instructions; large bodies don't JIT-inline, which pulled this dimension to 9.7/10; splitting the hottest bodies recovers the most.
Outdated: Microsoft.Extensions.DependencyInjection — Microsoft.Extensions.DependencyInjection 9.0.6 → 10.0.10 available (referenced by FFlow.Demo).
Outdated: coverlet.collector — coverlet.collector 6.0.2 → 10.0.1 available (referenced by FFlow.Tests).
Outdated: Microsoft.Extensions.DependencyInjection.Abstractions — Microsoft.Extensions.DependencyInjection.Abstractions 9.0.5 → 10.0.10 available (referenced by FFlow.Tests).
Outdated: Microsoft.NET.Test.Sdk — Microsoft.NET.Test.Sdk 17.12.0 → 18.8.1 available (referenced by FFlow.Tests).
Outdated: NUnit — NUnit 4.2.2 → 4.6.1 available (referenced by FFlow.Tests).
Outdated: NUnit.Analyzers — NUnit.Analyzers 4.4.0 → 4.14.0 available (referenced by FFlow.Tests).
Outdated: NUnit3TestAdapter — NUnit3TestAdapter 4.6.0 → 6.2.0 available (referenced by FFlow.Tests).
Outdated: Microsoft.Extensions.Hosting — Microsoft.Extensions.Hosting 9.0.6 → 10.0.10 available (referenced by FFlow.Scheduling).
Outdated: NCrontab — NCrontab 3.3.3 → 3.4.0 available (referenced by FFlow.Scheduling).
Outdated: Spectre.Console — Spectre.Console 0.50.0 → 0.57.2 available (referenced by FFlow.Cli).
Outdated: SSH.NET — SSH.NET 2025.0.0 → 2025.1.0 available (referenced by FFlow.Steps.SFTP).
Outdated: Microsoft.CodeAnalysis.Analyzers — Microsoft.CodeAnalysis.Analyzers 3.3.2 → 5.6.0 available (referenced by FFlow.Steps.DotNet.SourceGenerators).
Outdated: Microsoft.CodeAnalysis.CSharp — Microsoft.CodeAnalysis.CSharp 4.0.1 → 5.6.0 available (referenced by FFlow.Steps.DotNet.SourceGenerators).
D22 · Internal API Consistency· No exposed public API · ×1
No exposed public API — No intentionally-exposed types (IsPackable or .Contracts) to evaluate.
Appendix B — Reproduction & audit trail
Every external tool invocation behind a deep-scan dimension — the tool, its captured version, the exact command, how many findings it yielded, and a link to the retained raw output. To reproduce any finding: check out the same commit and run the command shown (repo-relative — never an absolute scratch path). The complete raw scanner output is retained verbatim under artifacts/raw/ (indexed in artifacts/raw/index.json); per-invocation exit codes and wall-clock durations are in sidecar.json — kept out of this table so the rendered report stays byte-identical across runs of the same commit.
trivy: not applicable — No Infrastructure-as-Code or container manifests found (Dockerfile, Terraform, Kubernetes/Helm, CloudFormation); nothing to scan.
trivy: not applicable — No JS/npm manifest or lockfile found outside build output (package.json, package-lock.json, yarn.lock, pnpm-lock.yaml, bun.lockb); no JS dependencies to scan.
disclosure: not applicable — No vulnerability-disclosure policy file found (SECURITY.md/.markdown/.rst/.txt at root or under .github/.forgejo/.gitea/docs, .well-known/security.txt). A coordinated-disclosure policy may live off-repo, so this is not evidenced rather than failed.
runtime-hardening: not applicable — No Kubernetes/orchestration workloads found in the repository manifests; network egress policy is a cluster-native control that may live at the platform/firewall layer, so there is nothing to assess here.
runtime-hardening: not applicable — No Kubernetes/orchestration workloads found in the repository manifests; seccomp/AppArmor/SELinux confinement is a workload-level control, so there is nothing to assess here.
runtime-hardening: not applicable — No Kubernetes/orchestration workloads found in the repository manifests; runtime threat-detection and admission-control policy are cluster-level controls, so there is nothing to assess here.
0
—
Run 019fc887-890b-7711-af73-61c41963dafc · every finding is also locatable in findings.md, and the complete scoring record (with exit codes + durations) in sidecar.json.
Issues: 8 · Warnings: 66 · Recommendations: 11 · Info: 28 — Appendix A · all findings · full markdown report.
Generated by Watchdog — deterministic code-health analysis. 03-08-2026 @ 16:49 UTC.
Downloadable artifacts
Machine-readable and reproducible from this commit + frozen rubric — drop them straight into a contract appendix, a CRA dossier, or a downstream SCA / VEX tool.