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Merge pull request #440 from TencentCloudBase/fix/pipeline-failures-20250627
Add repo skill review guidance to skill-authoring
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skills/skill-authoring/SKILL.md

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name: skill-authoring
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description: Design, improve, and evaluate reusable agent skills with high-quality SKILL.md files, precise trigger descriptions, progressive disclosure, and testable behavior. This skill should be used when users ask to create a new skill, rewrite or review an existing skill, improve skill trigger quality, organize skill references, or evaluate whether a skill should trigger and behave correctly.
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description: Design, improve, and evaluate reusable agent skills with high-quality SKILL.md files, precise trigger descriptions, progressive disclosure, and testable behavior. This skill should be used when users ask to create a new skill, rewrite or review an existing skill, audit a skill collection such as `config/source/skills` for redundancy or overlap, improve skill trigger quality, organize skill references, or evaluate whether a skill should trigger and behave correctly.
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alwaysApply: false
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- Create a new `SKILL.md`
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- Improve an existing skill's `name` or `description`
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- Review whether a skill is too broad, too narrow, or poorly structured
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- Audit a local skill collection such as `config/source/skills` for redundancy, trigger overlap, or weak boundaries
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- Split a large skill into `SKILL.md` plus `references/`, `assets/`, or `scripts/`
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- Design evaluation prompts and review whether a skill triggers and behaves correctly
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- Use the routing table to decide which reference file to read
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- Avoid loading every reference file by default
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5. **Evaluate before considering the skill complete**
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5. **Use collection-level review when the request is about many skills**
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- When reviewing `config/source/skills`, check overlap, duplication, trigger boundaries, and progressive disclosure across neighboring skills
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- Prefer evidence-based findings with concrete file references and rewrite guidance
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6. **Evaluate before considering the skill complete**
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- Create should-trigger and should-not-trigger prompts
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- Run them, review the results, and iterate on the skill
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| Write or improve `name` and `description` | `references/frontmatter-patterns.md` |
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| Design skill anatomy and progressive disclosure | `references/structure-patterns.md` |
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| Draft a new skill or review an existing one | `references/templates.md` |
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| Audit `config/source/skills` for quality, redundancy, and overlap | `references/repo-skill-review.md` |
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| Build evaluation prompts and review outcomes | `references/evaluation.md` |
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| Compare good examples, weak examples, and rewrites | `references/examples.md` |
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## Quick workflow
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1. Identify the skill's job, boundary, and closest neighboring skills.
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2. Draft `name` and `description` with realistic trigger language.
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3. Write the main `SKILL.md` so it changes agent behavior after trigger.
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4. Move deep detail into `references/`, `assets/`, or `scripts/` as needed.
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5. Run evaluation prompts and revise until trigger quality and behavior are stable.
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3. If the task targets `config/source/skills`, read `references/repo-skill-review.md` and review neighboring skills before proposing rewrites.
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4. Write the main `SKILL.md` so it changes agent behavior after trigger.
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5. Move deep detail into `references/`, `assets/`, or `scripts/` as needed.
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6. Run evaluation prompts and revise until trigger quality and behavior are stable.
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## Minimum self-check
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- Does routing point to the right reference file for each task?
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- Are evaluation prompts present for both should-trigger and should-not-trigger cases?
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- Can you explain why this skill stays distinct from its nearest neighbors?
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- If reviewing a skill collection, can you point to redundancy, overlap, and missing boundaries with concrete evidence?
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# Repo Skill Review
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## Purpose
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Use this reference when the task is to review a repository-managed skill collection such as `config/source/skills/` for quality, redundancy, trigger overlap, structure issues, or weak behavioral guidance.
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This review mode is based on:
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- Claude skill best practices: [Skill authoring best practices](https://platform.claude.com/docs/en/agents-and-tools/agent-skills/best-practices)
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- Datawhale skill write-up: [如何写出好的 Skill](https://github.com/datawhalechina/hello-agents/blob/main/Extra-Chapter/Extra08-%E5%A6%82%E4%BD%95%E5%86%99%E5%87%BA%E5%A5%BD%E7%9A%84Skill.md)
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- Trae guide: [如何写好一个 Skill:从创建到迭代的最佳实践](https://docs.trae.cn/ide/best-practice-for-how-to-write-a-good-skill)
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## When to use this reference
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Use it when the user asks to:
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- check the quality of `config/source/skills`
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- find redundant or overlapping skills
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- review whether skill descriptions are too broad or vague
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- inspect whether `SKILL.md` files are too heavy and should be split
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- evaluate whether repo-managed skills follow good authoring practice
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## Review Scope
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Treat the audit as four linked checks:
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1. Trigger quality
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2. Boundary clarity
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3. Structure and progressive disclosure
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4. Collection hygiene
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Do not stop at "this skill feels weak." The output should identify which dimension failed and what to rewrite.
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## Core Principles
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### 1. Description is the trigger surface
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`description` should explain both:
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- what the skill does
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- when it should be used
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For collection reviews, this means checking whether neighboring skills use distinguishable trigger language.
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Smells:
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- descriptions like "helps with X"
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- missing task or context cues
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- broad verbs shared across too many skills
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- synonyms stuffed into one skill without a clear boundary
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### 2. Write for the agent, not for humans
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Review `SKILL.md` for operational behavior, not team-facing prose.
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Smells:
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- background history
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- version history / changelog notes
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- README-style onboarding text
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- values or principles without actionable behavior
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Prefer instructions that change what the agent does after trigger.
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### 3. Keep only high-value context in the main file
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The main `SKILL.md` should stay concise and behavior-first.
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Check for:
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- repeated explanations the model likely already knows
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- long tutorials in the main file
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- deep detail that belongs in `references/`
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- repeated manual procedures that should become `scripts/`
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### 4. Progressive disclosure should be explicit
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`SKILL.md` should route the agent to the right reference file at the right time.
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Smells:
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- many reference files with no reading order
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- nested references that require reading references from references
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- no scenario-to-reference routing
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- heavy context loading by default
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### 5. Neighboring skills must stay distinct
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For repo-level audits, always compare the target skill against its nearest neighbors.
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Typical overlap patterns in `config/source/skills`:
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- platform vs domain skill overlap
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- auth entry skill vs platform-specific auth skill overlap
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- web vs mini program vs nodejs database skill overlap
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- "design/spec/review" skills that all claim broad planning or evaluation verbs
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If two skills share the same likely prompts, the review should explain whether to:
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- tighten one description
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- add non-applicable cases
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- move shared detail into a reference
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- merge the skills
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- split one skill by platform or mode
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## Repo Audit Workflow
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### Step 1: Build the inventory
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1. List all candidate skills under `config/source/skills/`
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2. Read the target `SKILL.md` files first
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3. Group nearby skills by domain, platform, or user intent
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Useful groupings:
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- auth
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- database
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- frontend / UI
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- deployment / runtime
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- planning / review
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- AI model usage
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### Step 2: Check frontmatter quality
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For each skill, ask:
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- Is the `name` short, stable, and specific?
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- Does the `description` describe both capability and trigger condition?
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- Would the description still be understandable without reading the body?
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- Is the wording in third-person / neutral instruction style rather than "I can help..."?
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- Does it overclaim scenarios already covered by a neighbor?
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### Step 3: Check body quality
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Ask:
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- Does the main file tell the agent what to do first?
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- Are non-applicable scenarios explicit?
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- Is the routing table present and useful?
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- Is behavior specific enough for fragile tasks?
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- Is the file acting like an execution guide rather than a general article?
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### Step 4: Check structure quality
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Ask:
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- Should some sections move into `references/`?
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- Are there scripts that would make fragile or repeated operations safer?
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- Are references one level deep from `SKILL.md`?
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- Do long reference files need a table of contents?
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### Step 5: Check overlap and redundancy
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Compare neighboring skills for:
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- same nouns + same verbs in `description`
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- duplicated workflow steps in `SKILL.md`
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- repeated examples that could live in one place
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- multiple skills routing to the same scenario without differentiation
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Mark each overlap as one of:
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- acceptable overlap
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- mild redundancy
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- trigger conflict
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- merge candidate
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- split candidate
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### Step 6: Design evaluation prompts
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For any skill that may be too broad or too narrow, create:
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- at least 3 should-trigger prompts
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- at least 3 should-not-trigger prompts
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- 1 closest-neighbor comparison
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Collection audits should include cross-skill prompts such as:
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- "Should this trigger `auth-tool` or `auth-web`?"
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- "Should this trigger `web-development` or `ui-design`?"
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- "Should this trigger `http-api` or `cloud-functions`?"
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## Findings Format
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When reporting the audit, prefer review-style findings ordered by severity.
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For each finding, include:
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- affected skill file(s)
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- issue type: trigger / boundary / structure / redundancy
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- why it matters
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- the smallest useful rewrite direction
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Example labels:
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- `[P1] Trigger wording overlaps with sibling skill`
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- `[P2] Main SKILL.md contains reference-grade detail`
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- `[P2] Missing non-applicable cases causes false positives`
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- `[P3] Duplicate examples should move to shared reference`
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## Rewrite Guidance
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Use these rewrite moves first:
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1. Tighten `description`
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2. Add "Do NOT use for" cases
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3. Make routing scenario-based
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4. Move detail from `SKILL.md` to `references/`
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5. Replace repeated manual instructions with `scripts/`
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6. Split by platform or mode only when boundary tightening is not enough
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## Collection Pass Criteria
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A repo skill collection is in good shape when:
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- each skill has a distinct job and nearest-neighbor boundary
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- descriptions are specific enough to drive correct triggering
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- `SKILL.md` files are concise and behavior-first
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- reference loading is explicit and shallow
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- repeated logic is minimized
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- audit findings can be explained with concrete file evidence

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