skill-authoring
- Repo stars 1,017
- Author updated Live
- Author repo CloudBase-MCP
- Domain
- Security
- Compatible agents
-
- Claude Code
- Cursor
- Cline
- Codex
- Windsurf
- Gemini CLI
- +20
- Trust score
- 88 / 100 · community maintained
- Author / version / license
- @TencentCloudBase · no license declared
- Token usage
- Lean
- Setup complexity
- Plug-and-play
- External API key
- Not required
- Operating systems
- Unspecified (assume cross-platform)
- Runtime requirements
- No special requirements
- Permissions
-
- Read-only
- Write / modify
- Network behavior
- Local-only
- Install commands
- 26 variants
Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.
Heads up: 未限定 allowed-tools,默认拥有全部工具权限。
---
name: skill-authoring
description: Design, improve, and evaluate reusable agent skills with high-quality SKILL.md files, precise tr…
category: security
runtime: no special runtime
---
# skill-authoring output preview
## PART A: Task fit
- Use case: 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..
- Inputs: target material, constraints, expected output, and acceptance criteria.
- Evidence boundary: follow “When to use this skill / Repo-managed CloudBase skill review / How to use this skill (for a coding agent)” and do not present inference as author intent.
## PART B: Execution result
- **01** The card summarizes the use case; runtime output centers on “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.”.
- **02** When the source has headings, the agent prioritizes “When to use this skill / Repo-managed CloudBase skill review / How to use this skill (for a coding agent)” so the result follows the author’s structure.
- **03** Typical output includes task judgment, concrete steps, required commands or file edits, validation, and follow-up options.
- **04** Risk context follows the fingerprint: read files, write/modify files; mostly runs locally; usually needs no extra API key.
## Running Rules
- read files, write/modify files; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding scope.
- Return the result, validation criteria, and next iteration options. The source does not require a stable slash command. After installation, invoke the skill by name and describe the task.
Name target files or source material, expected output, forbidden changes, and whether network or shell access is allowed. Permission fingerprint: read files, write/modify files.
Start with a small task and check whether the result follows “When to use this skill / Repo-managed CloudBase skill review / How to use this skill (for a coding agent)”. Inspect diffs, logs, previews, or tests before expanding scope.
Confirm the final output includes a concrete result, evidence, and next action. If it stays generic, tighten inputs, boundaries, and acceptance criteria.
---
name: skill-authoring
description: Design, improve, and evaluate reusable agent skills with high-quality SKILL.md files, precise tr…
category: security
source: TencentCloudBase/CloudBase-MCP
---
# skill-authoring
## When to use
- Design, improve, and evaluate reusable agent skills with high-quality SKILL.md files, precise trigger descriptions, pr…
- Use it when the task has clear inputs, repeatable steps, and validation criteria.
## What to provide
- Target material, scope, expected result, and forbidden changes.
- Whether network, commands, file writes, or external services are allowed.
## Execution rules
- Organize steps around “When to use this skill / Repo-managed CloudBase skill review / How to use this skill (for a coding agent)” and keep inference separate from source facts.
- read files, write/modify files; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding the task.
## Output requirements
- Return the deliverable, key evidence, validation method, and next action.
- Mark missing information as unknown; do not invent commands, platforms, or dependencies. The author source anchors workflow facts; repository files anchor sources and commands; Fluxly only adds fit, limitations, and quality judgment.
skill "skill-authoring" {
input -> user goal + target files + boundaries + acceptance criteria
context -> When to use this skill / Repo-managed CloudBase skill review / How to use this skill (for a coding agent)
rules -> SKILL.md triggers / order / output contract
runtime -> no special runtime | read files, write/modify files | mostly runs locally
guardrails -> usually needs no extra API key + small-sample validation + diff/log review
output -> copyable result + checklist + next iteration
} 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
nameordescription - Review whether a skill is too broad, too narrow, or poorly structured
- Audit a local skill collection such as
config/source/skillsfor redundancy, trigger overlap, or weak boundaries - Split a large skill into
SKILL.mdplusreferences/,assets/, orscripts/ - 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 infer public CNB / OpenClaw / ClawHub paths from the source tree; verify the actual published structure before writing fallback links or marketplace-facing URLs
- If a skill mentions raw URLs, blob URLs, or marketplace-consumed paths, check live reachability before finalizing the text
- Put standalone-install fallback guidance where the user needs it: keep the top-level note short, and place sibling-skill fallback links next to the actual cross-skill reference
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)
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
Optimize the trigger surface early
- Draft
nameand especiallydescriptionbefore expanding the body - Put realistic trigger language into
description, not only into the body
- Draft
Design behavior, not just documentation
- Make the main
SKILL.mdtell the agent what to do after the skill triggers - Use references for deeper guidance, not as a substitute for behavioral rules
- Make the main
Load supporting materials only when needed
- Use the routing table to decide which reference file to read
- Avoid loading every reference file by default
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
- When reviewing
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
| Task | Read |
|---|---|
Write or improve name and description |
references/frontmatter-patterns.md |
| Design skill anatomy and progressive disclosure | references/structure-patterns.md |
| Draft a new skill or review an existing one | references/templates.md |
Audit config/source/skills for quality, redundancy, and overlap |
references/repo-skill-review.md |
| Review repo-managed CloudBase source skills | references/cloudbase-skill-review.md |
| Build evaluation prompts and review outcomes | references/evaluation.md |
| Compare good examples, weak examples, and rewrites | references/examples.md |
Quick workflow
- Identify the skill's job, boundary, and closest neighboring skills.
- Draft
nameanddescriptionwith realistic trigger language. - If the task targets
config/source/skills, readreferences/repo-skill-review.md, then loadreferences/cloudbase-skill-review.mdfor CloudBase-specific standards before proposing rewrites. - If the skill text will mention published URLs or fallback paths, verify the public structure and at least one real URL before writing.
- Write the main
SKILL.mdso it changes agent behavior after trigger. - Move deep detail into
references/,assets/, orscripts/as needed. - Run evaluation prompts and revise until trigger quality and behavior are stable.
Minimum self-check
- Is the
nameshort, intentional, and stable? - Does the
descriptionexplain both capability and trigger conditions? - Does the main
SKILL.mdchange agent behavior after trigger? - Are non-applicable scenarios explicit?
- Does routing point to the right reference file for each task?
- If the skill references public URLs or standalone-install fallback paths, were those URLs verified against the actual published surface instead of guessed from local directories?
- 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?
Decide Fit First
Design Intent
How To Use It
Boundaries And Review