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skill-authoring

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.

中文简介正在准备中。当前显示原文说明。

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包含的文件(8)

  • SKILL.md6.4 KB
  • references/cloudbase-skill-review.md6.3 KB
  • references/evaluation.md3.8 KB
  • references/examples.md2.2 KB
  • references/frontmatter-patterns.md3.0 KB
  • references/repo-skill-review.md6.6 KB
  • references/structure-patterns.md4.6 KB
  • references/templates.md4.6 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Skill Authoring

Create and refine reusable agent skills with better trigger quality, cleaner structure, stronger behavioral guidance, and more reliable evaluation.

When to use this skill

Use this skill when you need to:

  • Create a new SKILL.md
  • Improve an existing skill's name or description
  • Review whether a skill is too broad, too narrow, or poorly structured
  • Audit a local skill collection such as config/source/skills for redundancy, trigger overlap, or weak boundaries
  • Split a large skill into SKILL.md plus references/, assets/, or scripts/
  • Design evaluation prompts and review whether a skill triggers and behaves correctly

Repo-managed CloudBase skill review

When the task targets config/source/skills, apply these guardrails in addition to the normal skill-authoring workflow:

This section is the repo-managed CloudBase skill review baseline for this repository.

  • Keep frontmatter complete and normalized, including version
  • Keep examples inside the skill's declared platform and scope
  • Keep shared operational rules in one canonical source instead of copying large blocks across neighboring skills
  • If the skill claims a rule is mandatory, show that rule in at least one example
  • When giving a recommended default, also explain the tradeoff behind it
  • Do not add agent-directed remote skill-fetch URLs (for example cnb.cool/.../git/raw/... skill bodies or (standalone fallback: ...) raw links). Marketplace reviewers treat those as injection / session-hijack risk.
  • Prefer local relative sibling paths (../other-skill/SKILL.md). If a sibling is missing, tell the agent to ask the user to install the full CloudBase plugin or skills pack — never to HTTP-fetch remote skill markdown into context.
  • Human documentation URLs (docs.cloudbase.net, console pages) remain allowed when they are not skill-body fetch instructions.
  • Do not infer public CNB / OpenClaw / ClawHub paths from the source tree when writing marketplace-facing install docs; verify the actual published structure first.

Do NOT use for:

  • General documentation writing that is not about skills
  • README polish or marketing copy
  • Prompt tweaks that do not affect skill structure or behavior
  • Rule files unrelated to SKILL.md

How to use this skill (for a coding agent)

  1. Identify the task class first

    • Determine whether the request is about creating a new skill, reviewing an existing skill, or improving trigger quality, structure, or evaluation
  2. Optimize the trigger surface early

    • Draft name and especially description before expanding the body
    • Put realistic trigger language into description, not only into the body
  3. Design behavior, not just documentation

    • Make the main SKILL.md tell the agent what to do after the skill triggers
    • Use references for deeper guidance, not as a substitute for behavioral rules
  4. Load supporting materials only when needed

    • Use the routing table to decide which reference file to read
    • Avoid loading every reference file by default
  5. Use collection-level review when the request is about many skills

    • When reviewing config/source/skills, check overlap, duplication, trigger boundaries, and progressive disclosure across neighboring skills
    • Prefer evidence-based findings with concrete file references and rewrite guidance
    • Treat source layout, published skills-repo layout, and marketplace-consumed layout as different surfaces until you verify they are the same
  6. Evaluate before considering the skill complete

    • Create should-trigger and should-not-trigger prompts
    • Run them, review the results, and iterate on the skill

Routing

TaskRead
Write or improve name and descriptionreferences/frontmatter-patterns.md
Design skill anatomy and progressive disclosurereferences/structure-patterns.md
Draft a new skill or review an existing onereferences/templates.md
Audit config/source/skills for quality, redundancy, and overlapreferences/repo-skill-review.md
Review repo-managed CloudBase source skillsreferences/cloudbase-skill-review.md
Build evaluation prompts and review outcomesreferences/evaluation.md
Compare good examples, weak examples, and rewritesreferences/examples.md

Quick workflow

  1. Identify the skill's job, boundary, and closest neighboring skills.
  2. Draft name and description with realistic trigger language.
  3. If the task targets config/source/skills, read references/repo-skill-review.md, then load references/cloudbase-skill-review.md for CloudBase-specific standards before proposing rewrites.
  4. Keep sibling routing local-only; do not add remote skill-fetch URLs.
  5. Write the main SKILL.md so it changes agent behavior after trigger.
  6. Move deep detail into references/, assets/, or scripts/ as needed.
  7. If the skill ships in plugin/cloudbase, also write plugin/cloudbase/skill-metadata.json (see references/templates.md landing checklist) and run npm run build:skill-manifest.
  8. Run evaluation prompts and revise until trigger quality and behavior are stable.

Minimum self-check

  • Is the name short, intentional, and stable?
  • Does the description explain both capability and trigger conditions?
  • Does the main SKILL.md change agent behavior after trigger?
  • Are non-applicable scenarios explicit?
  • Does routing point to the right reference file for each task?
  • Does the skill avoid agent-directed remote skill-fetch URLs and keep sibling routing local-only?
  • Are evaluation prompts present for both should-trigger and should-not-trigger cases?
  • Can you explain why this skill stays distinct from its nearest neighbors?
  • If reviewing a skill collection, can you point to redundancy, overlap, and missing boundaries with concrete evidence?
  • If this is a plugin skill, does plugin/cloudbase/skill-metadata.json include the new dir with non-empty promptSignals.phrases?

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中文简介正在准备中。当前显示原文说明。

TencentCloudBase/CloudBase-AI-Toolkit11402026年10月18日 更新

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