<Skill Name>
Free<What this skill does>
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Design a new Claude Code skill from a concrete use case and produce a repo-ready skill package. Use when the user asks to create a new skill, define a skill's responsibility, draft SKILL.md, choose frontmatter, design supporting files, or prepare eval criteria for a new skill. Also trigger on "スキルを作りたい", "スキルを作って", "スキルを追加して", "新しいスキル", "SKILL.md生成".
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See how to installReview the instructions the agent will receive before you install.
Primary pattern: Pipeline Secondary patterns: Inversion Why: skill creation requires strict phase order (requirements → pattern selection → structure → review) with an upfront question-gathering gate.
Create a new skill only after the use case is concrete enough.
Your job is to:
SKILL.mdWrite output files only to .claude/skills/ unless the user explicitly specifies a different path.
Do not modify existing skills without user confirmation.
Note: this skill does not set disable-model-invocation: true because file creation is its primary purpose, not an incidental side effect. The settings.json deny list and user confirmation prompts provide sufficient guardrails.
Do not create a broad or fuzzy skill.
Prefer:
If the requested scope is too broad, split it into multiple skills.
Before drafting, confirm:
If any item is unclear:
Do not draft the full skill until the gate passes.
Choose the primary design pattern before drafting the skill.
Available patterns:
Selection rules:
Do not continue until the pattern choice is explicit.
Produce a short working summary with:
Reject designs that combine unrelated workflows.
Choose frontmatter intentionally.
Defaults:
namedescriptionUse:
disable-model-invocation: true for side-effecting, sensitive, or timing-dependent workflowsallowed-tools only when safe pre-approval is clearly usefulmodel only when there is a concrete reason to override the defaultFor every chosen field, state why it is needed.
Draft the skill with this order:
Keep the main file compact.
Move heavy references, examples, and templates into separate files.
For River Review Agent Skills, keep activation, responsibility, routing, hard guards, and the output contract in SKILL.md; move optional examples, troubleshooting, rationale, and provider-specific detail to references/. Treat the repository's 12 KiB / 250-line context-health threshold as an advisory review signal, never as a reason to remove safety or verification.
Use ${CLAUDE_SKILL_ROOT}/assets/basic-skill-template.md as the starting skeleton.
The generated SKILL.md must include a Pattern declaration section at the top with primary pattern, secondary patterns, and Why fields matching the choice from Phase 0.5.
Create an initial eval plan with:
Include at least:
Use ${CLAUDE_SKILL_ROOT}/assets/eval-rubric-template.md as the rubric structure.
Check the draft against:
${CLAUDE_SKILL_ROOT}/references/review-default.md${CLAUDE_SKILL_ROOT}/references/design-principles.mdFix any issue before finalizing.
After the skill files are written:
name field in frontmatterdescription is under 1024 characters and includes trigger keywordsSKILL.md entrypoint size and review whether optional knowledge should move to supporting filesnpm run agent-skills:validate and inspect any context-health advisory; exceeding 12 KiB / 250 lines is warning-only and requires judgment, not blind trimming${CLAUDE_SKILL_ROOT}/ references point to existing filesReturn exactly these sections:
Do not:
If the request is too broad:
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<What this skill does>
The English summary is being prepared. Showing the original description.
画像・ボタン・フォーム要素に適切なアクセシブルネームがあるか確認する。
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Ensure ADRs capture context, decision, alternatives, tradeoffs, and follow-ups in a way that prevents future drift.
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敵対的分析手法を統合したレビューの entry skill。認知バイアス対策の3手法 (Pre-mortem / War Game / Logic Torturing)と、宣言・主張と実態の乖離を突く claim-vs-actual 検出3パターン(Self-Contradiction / Refactor-Claim Audit / Cross-File Leakage)へルーティングし、通常のレビューでは見えない設計の盲点・ 防御の穴・論理の弱点・宣言と実装のズレを可視化する。
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Review changes to the Agent Skills import/export bridge for path safety, round-trip fidelity, and validation correctness.
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Checks whether AI-assisted work defines review criteria, accessible context, explicit review loop, human judgment boundary, and feedback capture before delegating to an agent.
The English summary is being prepared. Showing the original description.