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mspec-review

self-review step of mspec workflow — sanity-check all artifacts via subagent

The English summary is being prepared. Showing the original description.

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Files included (1)

  • SKILL.md2.3 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

<!-- @mspec-delta 2026-05-15-063805-fix-command-name-consistency/specs/claude-integration/spec.md --> <!-- Requirements implemented: FR-017 --> <!-- Change: fix-command-name-consistency -->

Procedure

  1. Run mspec status --change <change-dir> --json first.
  2. Run mspec continue --change <change-dir> --json to fetch subagent_prompt.
  3. Read all requires (checklist.md, design.md, architecture-overview.md, quickstart.md).
  4. Invoke mspec-self-reviewer subagent (Task tool) with subagent_prompt.
  5. Append the subagent's review notes as a ## Self-Review section to design.md (no new files; produces: []).
  6. Update Constitution Check tables across artifacts where the reviewer flagged gaps.
  7. Run mspec validate --change <change-dir>.
  8. block: true — stop and ask the user to run /mspec:continue.
<!-- @mspec-delta 2026-05-25-131216-agent-experience-manifest/specs/skill-observability/spec.md --> <!-- Requirements implemented: FR-001, FR-002 --> <!-- Change: agent-experience-manifest -->

Observation (Agent Experience Log)

After the subagent completes (step 4), count [blocker] lines in the review output, then record the run:

mspec agent-run record self-review \
  --change <change-name> \
  --bytes <sum-of-input-artifact-bytes> \
  --artifacts <space-separated-artifact-paths> \
  --edits <count-of-[blocker]-lines>

Example: mspec agent-run record self-review --change 2026-05-25-my-feature --bytes 22180 --artifacts checklist.md design.md tasks.md --edits 2

This appends one JSONL entry to changes/<change>/.agent-runs.jsonl. Do NOT include prompt text or file contents.

Verification (C2)

  • mspec validate --change <change> — アーティファクト整合性チェック
  • mspec anchor check --change <change> — アンカー解決確認
  • self-review の [blocker] 指摘がゼロになっているか確認

Learning (C3)

このスキルの実行で発生した学習候補を記録する:

<!-- LEARNING: <パターン説明> | source: <FR-ID> | confidence: low|medium|high -->

mspec learn コマンドが archive 済み changes からこれらを収集してpost-condition候補をproposeする。

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