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Jamie-BitFlightJamie-BitFlight/claude_skills/.claude/skills/evaluate-sdlc-layers/SKILL.md

evaluate-sdlc-layers

Skill67 starsChanged 52 days agoMITView on GitHub

Validate and iterate on the SDLC Layer Separation Architecture implementation across the check categories defined in its Evaluation Checklist — cross-references, doc completeness, knowledge-explorer layer filters, research entry metadata, integration points, and plan consistency. Produces a structured findings report and optionally applies safe fixes. Use when validating a first-pass implementation, before claiming layer work complete, auditing layer docs or schema, or running --dry-run to preview findings without changes.

The file

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2 rules. About 0 are common, 2 are distinctive, and 0 are very specific to this project.

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    Common · estimate

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  • ≈2

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    This author's own choices. Worth a look.

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  • Distinctive
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  1. Distinctive:

    Run each check and record PASS / FAIL / SKIP with evidence.

    line 22
  2. Distinctive:

    Re-run: After fixes, re-run evaluation to confirm improvements.

    line 122

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Files
SKILL.md

Evaluate SDLC Layers

Systematically evaluate the SDLC Layer Separation Architecture implementation and support iterative improvement. Treats the implementation as first-pass until validated.

Arguments

  • --dry-run — Run all checks, produce report only. Do not apply fixes.
  • --fix — After evaluation, apply safe fixes for broken references, missing metadata, or obvious gaps. Report what was changed.
  • (no args) — Evaluate and produce report; offer to fix or delegate fixes.

Evaluation Checklist

Run each check and record PASS / FAIL / SKIP with evidence.

1. Cross-Reference Validation

For each linked path in plugins/development-harness/docs/sdlc-layers/ and related docs:

  • sam-definition.md — exists at plugins/development-harness/skills/work-backlog-item/references/sam-definition.md
  • plugins/development-harness/CLAUDE.md — exists
  • stateless-agent-methodology/research/arl/PROVENANCE.md — exists (sibling repo or configured path)
  • Layer 0 docs → TASK_FILE_FORMAT.md — exists at plugins/development-harness/docs/TASK_FILE_FORMAT.md
  • Layer 1 → role-resolution-protocol.md — exists in development-harness
  • Layer-0 redirect stubs (artifact-conventions.md, task-file-format.md, sam-pipeline.md, arl-touchpoints.md) contain redirect pointers to canonical locations. Validate each redirect target exists.

Evidence: List each path checked and result (exists / 404 / wrong content).


2. Doc Completeness

  • Layer 0 content files (6): README, rt-ica-gate, verification-protocol, evidence-discipline, orchestrator-discipline, context-fit-complexity
  • Layer 0 redirect stubs (4): sam-pipeline, arl-touchpoints, artifact-conventions, task-file-format — each must contain a redirect pointing to its canonical skill reference location
  • Layer 1: All 5 docs present (README, layer-1-overview, linting-discovery-protocol, workflow-pattern-taxonomy, harness-role-mapping)
  • ARL: arl-meta-layer.md, arl-human-probing-design.md

Evidence: Glob or Read results for each expected file.


3. Knowledge-Explorer Layer Filter

  • uv run research/knowledge-explorer.py list --layer 0 — returns entries with layer: "0"
  • uv run research/knowledge-explorer.py list --layer 1 — returns entries with layer: "1"
  • Entries without layer metadata are excluded when --layer is used (expected)

Evidence: Paste command output for each.


4. Research Entry Layer Metadata

  • evaluation-testing/harness-engineering-openai.md — has layer: "0"
  • developer-tools/copier-astral.md — has layer: "1"
  • research/README.md — has "Layer Mapping" section

Evidence: Grep for layer: in frontmatter of each.


5. Integration Points

  • work-backlog-item SKILL, groom subcommand (references/workflows/groom/start.md) — documents ARL human-probing integration; references arl-human-probing-design
  • role-resolution-protocol.md — has "Layer 0 gates apply before role resolution"
  • plugins/development-harness/CLAUDE.md — references layer model

Evidence: Grep or Read for key phrases.


6. Consistency with Plan

  • Plan deliverables (from attached plan) — compare File and Directory Changes table to actual files
  • Dependency order — Layer 0 → Layer 1 → Research → SAM/ARL → ARL probing → work-backlog-item

Evidence: List any plan items not yet implemented or diverged.


Output Format

Produce a structured report:

## SDLC Layer Evaluation Report
Date: {YYYY-MM-DD}

### Summary
- Cross-Reference: {PASS|FAIL|PARTIAL} — {brief}
- Doc Completeness: {PASS|FAIL|PARTIAL}
- Knowledge-Explorer: {PASS|FAIL|PARTIAL}
- Research Metadata: {PASS|FAIL|PARTIAL}
- Integration Points: {PASS|FAIL|PARTIAL}
- Plan Consistency: {PASS|FAIL|PARTIAL}

### Findings
1. [Category] {finding} — {suggested fix}
2. ...

### Recommended Actions
- [ ] {action 1}
- [ ] {action 2}

Iteration

After evaluation:

  1. If --fix: Apply safe fixes (broken paths, missing frontmatter fields, obvious typos). Report each change.
  2. If no --fix: Present findings; offer to create backlog items or apply fixes.
  3. Re-run: After fixes, re-run evaluation to confirm improvements.

Experiments

Flow experiments and learnings live in sam-flow-experiments. Clone via SSH: git clone git@github.com:Jamie-BitFlight/sam-flow-experiments.git. When iterating, consider running experiments against concept fixtures to validate changes.


References

  • SDLC Layers
  • verify-done — evidence discipline
  • work-backlog-item — orchestration pattern (groom subcommand: references/workflows/groom/start.md)

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