agentleFS
Will-SW74Will-SW74/passdown-os/.claude/skills/spectra-analyze/SKILL.md

spectra-analyze

Skill0 starsChanged 4 months agoMITView on GitHub

Analyze artifact consistency for a change

4 other projects use a version of this, 1 of them edited.

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Most recently taken up by

The file

We split this skill into the rules it gives an agent

10 rules. About 0 are common, 6 are distinctive, and 4 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈6

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 4

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    If not provided, infer from context or run spectra list --json to auto-select.

    line 33
  2. Distinctive:

    Add any additional findings to the report.

    line 71
  3. Distinctive:

    If CRITICAL findings: "Found N issue(s) worth addressing.

    line 74
  4. Very specific:

    If only warnings/suggestions: Note them briefly, then recommend proceeding with /spectra-apply

    line 75
  5. Very specific:

    If clean: "Artifacts look consistent" and suggest /spectra-apply

    line 76
  6. Very specific:

    When spectra status --change "<name>" --json shows isComplete: true, run this analysis automatically before recommending /spectra-apply.

    line 80
  7. Distinctive:

    Read-only: NEVER modify files

    line 84
  8. Distinctive:

    Do NOT prompt for change selection if it can be inferred

    line 85
  9. Distinctive:

    Keep output concise - this runs inline, not as a separate workflow

    line 86
  10. Distinctive:

    If AskUserQuestion tool is not available, ask the same questions as plain text and wait for the user's response

    line 87

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Claude fork context

This generated Claude Code skill runs with context: fork. The rules in this section take precedence over the shared analyze body below.

When no change name is provided, run spectra list --json. Auto-select only when there is exactly one active change. If there are zero active changes or more than one active change, return the candidate list or empty-state message and ask the main thread to rerun /spectra-analyze <change-name>. Do NOT ask an interactive selection question inside the fork.


Analyze artifact consistency for a change. Can be invoked directly or triggered automatically when all artifacts are complete.

Input: Optionally specify a change name (e.g., /spectra-analyze add-auth). If omitted, infer from conversation context or auto-select if only one active change exists.

Prerequisites: This skill requires the spectra CLI. If any spectra command fails with "command not found" or similar, report the error and STOP.

Steps

  1. Determine change name

    If not provided, infer from context or run spectra list --json to auto-select.

  2. Run programmatic analysis

    spectra analyze <change-name> --json

    This returns structured JSON with:

    • dimensions: Array of { dimension, status, finding_count } for Coverage, Consistency, Ambiguity, Gaps
    • findings: Array of { id, dimension, severity, location, summary, recommendation }
    • artifacts_analyzed / artifacts_missing: Which artifacts were available
  3. Present results

    Format the JSON output as a readable summary:

    ## Artifact Analysis: <change-name>
    
    | Dimension     | Status                   |
    |---------------|--------------------------|
    | Coverage      | <status>                 |
    | Consistency   | <status>                 |
    | Ambiguity     | <status>                 |
    | Gaps          | <status>                 |

    Group findings by severity (Critical > Warning > Suggestion) with locations and recommendations.

  4. Supplement with AI semantic analysis (optional)

    The programmatic analyzer catches structural issues. For deeper semantic analysis, also read the artifacts and check for:

    • Design decisions that contradict spec requirements
    • Tasks referencing work outside proposal scope
    • Risks in design without corresponding spec coverage
    • Logical inconsistencies between artifacts

    Add any additional findings to the report.

  5. Recommend next steps
    • If CRITICAL findings: "Found N issue(s) worth addressing. Want to fix these before implementing?"
    • If only warnings/suggestions: Note them briefly, then recommend proceeding with /spectra-apply
    • If clean: "Artifacts look consistent" and suggest /spectra-apply

Passive Trigger

When spectra status --change "<name>" --json shows isComplete: true, run this analysis automatically before recommending /spectra-apply.

Guardrails

  • Read-only: NEVER modify files
  • Do NOT prompt for change selection if it can be inferred
  • Keep output concise - this runs inline, not as a separate workflow
  • If AskUserQuestion tool is not available, ask the same questions as plain text and wait for the user's response

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