agentleFS
tethertotetherto/qvac/.agents/skills/qv-quality-reporting/SKILL.md

qv-quality-reporting

Skill697 starsChanged 18 days agoApache-2.0View on GitHub

Run the deterministic code-quality audit, turn related findings into contextual remediation groups, prepare approval-gated Asana proposals, reconcile recurring runs, or configure twice-monthly quality reporting.

We split this skill into the rules it gives an agent

8 rules. About 0 are common, 2 are distinctive, and 6 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈2

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 6

    Very specific

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

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

    Run pnpm quality:reporting from the repository root.

    line 14
  2. Distinctive:

    Stop if the command fails, any detector reports diagnostics, or resolutions are withheld.

    line 15
  3. Very specific:

    Write the final machine batch to .quality/proposals.json.

    line 39
  4. Very specific:

    After the user explicitly approves IDs, rerun the helper for only that subset without --apply and show the exact actions.

    line 56
  5. Distinctive:

    Never infer approval for proposals the user did not name.

    line 68
  6. Very specific:

    Prefer source links in chat when a concrete line is available.

    line 81
  7. Very specific:

    Use references/scheduling.md only when the user asks to create or modify the twice-monthly automation.

    line 121
  8. Very specific:

    When the user corrects ownership, importance, or group cohesion, apply that feedback to the current review.

    line 126

≈ “Common” is an estimate: at least 1 in 5 of the 308,232 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

Quality Reporting

Turn the repository's deterministic quality evidence into a short, actionable review. This skill owns contextual grouping and triage; it does not replace the underlying findings or mutate Asana without explicit approval.

Default Workflow

  1. Run pnpm quality:reporting from the repository root.
  2. Stop if the command fails, any detector reports diagnostics, or resolutions are withheld. Explain the incomplete evidence instead of proposing progress.
  3. Read .quality/triage.json, references/triage-config.json, and only the source or architecture files needed to understand the leading candidates.
  4. Form cohesive remediation groups. Start with deterministic candidates, then:
    • combine candidates only when they share one root cause and fit one focused PR;
    • split a candidate when it contains independent remediations;
    • preserve every covered finding fingerprint;
    • apply approved merge/split overrides from the config before new judgment.
  5. Assign ownership and P1-P4 priority using the config plus evidence in the triage report. Never derive priority from finding count alone.
  6. Build the review batch using references/ticket-template.md:
    • On the initial backlog review, begin with the deterministically ranked candidates.
    • On recurring runs, examine all new, worsened changed, and resolved lifecycle evidence before unchanged existing debt, regardless of severity. Skip improved-only and unchanged groups unless the user asks for backlog review.
    • Generate provisional proposals in pages, reconcile each page read-only, discard exact-existing and unchanged outcomes, and continue until ten actionable proposals remain or candidates are exhausted. Ambiguous matches count as actionable decisions. Never cap the source candidates before this backfill step. Write the final machine batch to .quality/proposals.json. Retain unreviewed candidates for later pages; do not discard them.
  7. Reconcile each provisional page read-only with:

    node .agents/skills/qv-quality-reporting/scripts/asana-quality.mjs \
      --proposals .quality/proposals.json \
      --report .quality/triage.json

    Suppress exact duplicate creations and unchanged actions, surface ambiguous matches, and show the resulting final batch in chat as a numbered, concise review. If local Asana access is unavailable, label the proposals unreconciled and do not apply them until reconciliation succeeds.

  8. End the initial run by asking the user which proposal IDs to approve. Do not use --apply, even if the user previously authorized analysis.
  9. After the user explicitly approves IDs, rerun the helper for only that subset without --apply and show the exact actions. Stop if the match is ambiguous or the result differs materially from what the user approved. Otherwise run:

    node .agents/skills/qv-quality-reporting/scripts/asana-quality.mjs \
      --proposals .quality/proposals.json \
      --report .quality/triage.json \
      --approve <comma-separated-proposal-ids> \
      --apply

    Never infer approval for proposals the user did not name.

Review Shape

For each proposal, show:

  • proposal ID, P1-P4 priority, primary team, and collaborators;
  • a two-to-four sentence explanation of what is wrong and where;
  • one focused remediation boundary;
  • compact evidence: paths, rules, severity, threshold excess, and Git activity;
  • lifecycle action: create, comment on a materially worsened group, or review an apparent resolution.

Prefer source links in chat when a concrete line is available. Keep the deterministic finding list in .quality/report.md as the evidence trail.

Priority Judgment

  • P1: evidenced current correctness, initialization, security, or release risk on a critical path. A high-severity smell alone is not P1.
  • P2: material maintainability risk in important or frequently changed production code, especially when several findings describe one root cause.
  • P3: bounded, credible debt worth scheduling without urgent operational risk.
  • P4: opportunistic cleanup, low-churn auxiliary code, or weak evidence.

State the evidence that justifies the band. If importance or ownership is uncertain, say so instead of inventing certainty.

Recurring Runs

pnpm quality:reporting compares the current findings with the previous successful run in .quality/previous-run-baseline.json. When no snapshot exists, the first run uses the committed audit baseline. The command advances the local snapshot only after complete analysis and successful triage. Do not delete it between recurring runs.

Reconcile by stable group marker before proposing work:

  • new actionable group with no match: propose ticket creation;
  • materially worse existing group: use changes[].direction and the retained before/after values to justify a proposed comment on its existing ticket;
  • improved-only drift: do not describe it as a regression;
  • apparently resolved group: show a review notice, never complete a task;
  • unchanged group: stay silent;
  • ambiguous match: request a decision and do not mutate Asana.

The helper records only the group action and deterministic evidence hash in .quality/reporting-state.json. This ignored local checkpoint prevents the same ticket creation, regression comment, or resolution notice from being proposed repeatedly. It contains no Asana IDs or private links. Do not delete it between recurring runs.

Use references/scheduling.md only when the user asks to create or modify the twice-monthly automation.

Feedback and Configuration

When the user corrects ownership, importance, or group cohesion, apply that feedback to the current review. Offer a minimal update to references/triage-config.json only when it expresses a reusable repository rule. Do not store task IDs, private Asana links, people, tokens, or transient ticket state in repository files.

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