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normalize-skill-for-claudenormalize 技能 FOR Claude

Agent Skill

normalize-skill-for-claude 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

549

周安装

22

GitHub Stars

公开资料未说明

下载量

178
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:normalize-skill-for-claude(normalize 技能 FOR Claude)
来源仓库:https://github.com/ulpi-io/skills
仓库路径:skills/normalize-skill-for-claude
安装命令:
npx skills add https://github.com/ulpi-io/skills --skill normalize-skill-for-claude
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/ulpi-io/skills --skill normalize-skill-for-claude

简介

normalize-skill-for-claude 用于查找、检索和筛选相关信息,适合技能标准化支持场景。

  • 适用于 Codex、Claude、Cursor 和 Gemini CLI,支持基于线索快速定位相关内容。
  • 可通过 GitHub 仓库和原始文档继续核验具体用法。
  • 安装前应确认是否会触发外部操作,评估安全风险。
  • 建议在受控环境中测试后再集成到技能管理中。

SKILL.md

Non-negotiable rules:

  1. Read references/claude-skill-runtime.md before planning or rewriting.
  2. Default to --mode plan unless the user explicitly asks to rewrite now.
  3. Treat frontmatter as the highest-leverage surface. Claude routes and budgets skills from metadata first.
  4. Keep SKILL.md focused on workflow. Move bulky examples, framework variants, and edge-case catalogs into references/ or scripts/.
  5. Do not add context: fork, paths:, or user-invocable: false without a concrete runtime reason.
  6. Never add agent-only frontmatter to a skill. tools, disallowedTools, skills, initialPrompt, permissionMode, maxTurns, background, memory, isolation, color, and mcpServers belong to agents, not skills.

Normalize Skill For Claude

Inputs

  • $target: Skill directory or direct path to SKILL.md
  • $mode: Optional. plan or rewrite. Default: plan

Goal

Produce a Claude Code optimized skill that is easier to auto-invoke, cheaper to keep in prompt budget, and safer to execute. Always start by creating a per-skill DAG plan unless the user explicitly asks for direct rewrite.

Step 1: Resolve the target

  1. Accept either a skill directory or a direct SKILL.md path.
  2. Normalize to the skill root and confirm SKILL.md exists.
  3. Determine mode:

- --mode rewrite means plan first, then rewrite in the same run - missing mode means plan

  1. Inventory the current skill:

- line count of SKILL.md - existing frontmatter fields - whether references/, scripts/, or assets/ already exist - whether the skill appears internal-only or user-invocable

Success criteria: You know the exact skill root, target mode, current file shape, and likely scope of the rewrite.

Step 2: Load the Claude Code skill runtime anchors

Read references/claude-skill-runtime.md fully before making any recommendation.

Extract these constraints from the reference:

  • Claude budgets skill discovery from frontmatter and short descriptions first.
  • Full skill bodies are loaded on invocation, not for listing.
  • paths: activates conditional skills when matching files are touched.
  • context: fork runs the skill in a forked subagent and should be rare.
  • allowed-tools should be the minimum needed permission surface.
  • Skill rewrites must use skill-native frontmatter only, not agent-native headers.

If this repository contains claude-code-source/, use the exact source files named in the reference to verify edge cases before rewriting unusual frontmatter.

Success criteria: Every planned change can be tied to a specific Claude runtime behavior.

Step 3: Audit the current skill against Claude's runtime

Evaluate the target skill using this checklist:

  1. Description and trigger quality

- Does description say what the skill does, when to use it, and example trigger phrases? - Is when_to_use missing or weak?

  1. Frontmatter completeness

- Would allowed-tools, arguments, argument-hint, user-invocable, paths, context, or agent improve runtime behavior? - Are there any agent-only headers that must be removed or explicitly avoided?

  1. Body size and shape

- Is the body carrying reference material instead of core workflow? - Are there giant examples, duplicated checklists, or framework-specific sections that belong in references/? - Structural content audit: Does the skill contain routing tables (task→reference mappings), personality/expertise definitions, numbered rule sets, or gate classifications? These are high-signal inline content, NOT bulk examples. Tag each as PRESERVE-INLINE or EXTRACT-WITH-MANDATORY-LOAD.

  1. Invocation type

- Is this a public slash command, an internal router, or a conditional path-scoped helper?

  1. Execution model

- Would context: fork help, or would it fragment work and require mid-flow user interaction?

  1. Determinism opportunities

- Are there repeated shell snippets or fragile transformations that belong in scripts/?

Classify each issue:

  • ROUTING: metadata is too weak for auto-invocation
  • PROMPT: body is too large or redundant
  • SAFETY: tool scope or execution mode is too broad
  • STRUCTURE: references or scripts should be extracted

Success criteria: You have a concrete, source-backed audit of what must change and why.

Step 4: Write the per-skill DAG plan

Create both of these artifacts:

  • .ulpi/plans/skills/<skill-name>-normalize-for-claude.md
  • .ulpi/plans/skills/<skill-name>-normalize-for-claude.json

The plan must include:

  1. Current state

- line count - existing frontmatter - current folders - largest bloat areas

  1. Claude runtime findings

- each finding mapped to source references from references/claude-skill-runtime.md

  1. Target state

- final frontmatter shape - files to keep, rewrite, create, or split

  1. DAG tasks

- frontmatter rewrite - body trim - reference extraction - optional script extraction - validation

  1. Guardrails

- what must not be changed - what must not be over-automated

  1. Validation

- concrete commands or checks to confirm the skill is structurally sound

Each DAG task should include:

  • id
  • title
  • rationale
  • filesToModify
  • filesToCreate
  • dependencies
  • validation

Success criteria: The markdown and JSON plans describe the same work and can be executed safely.

Step 5: Rewrite only if requested

If mode is plan, stop after writing the DAG artifacts.

If mode is rewrite:

  1. Rewrite the frontmatter first.
  2. Keep the body focused on:

- inputs - goal - workflow steps - guardrails - output contract

  1. Move bulky material into references/, but respect content classification:

- Bulk (move to references): giant examples, framework variants, edge-case catalogs, verbose checklists, before/after code samples - Structural (keep inline OR extract with mandatory load directive): routing tables (task→reference mappings), numbered guardrail rules in EXTREMELY-IMPORTANT, gate classifications (BLOCK/CONCERN/OBSERVATION), personality/expertise sections - Routing tables that map task types to reference files MUST stay inline — they are the skill's primary navigation surface. - Concrete guardrail lists (numbered rules, always/never) MUST either stay in the EXTREMELY-IMPORTANT block or get a mandatory load directive in the step that needs them — not a soft "see references" suggestion. - When extracting personality/expertise to a reference file, add a mandatory load directive at session start, not just a "When To Load References" entry.

  1. Create scripts/ only when deterministic repeated logic is clearly justified.
  2. Keep the resulting SKILL.md lean enough that future edits remain easy.

Preferred rewrite outcomes:

  • description and when_to_use become trigger-oriented
  • internal router skills become user-invocable: false
  • domain skills gain paths: only when file-touch activation clearly helps
  • context: fork appears only for self-contained analysis/research workflows
  • no agent-only headers are introduced into the rewritten skill

Success criteria: The rewritten skill is structurally smaller, clearer to route, and justified by Claude runtime behavior.

Step 6: Validate the result

After planning or rewriting:

  1. Re-read the final SKILL.md.
  2. Confirm the body does not duplicate reference files.
  3. Confirm frontmatter fields are intentionally chosen, not cargo-culted.
  4. Confirm no agent-only headers were introduced.
  5. Confirm every references/ file is directly linked from SKILL.md.
  6. Confirm no routing tables, numbered guardrail rules, or gate classifications were stripped without replacement.
  7. Confirm the plan or rewrite summary names the Claude source anchors that drove the major decisions.

Success criteria: The output is usable immediately by a human or follow-on agent without guessing.

Output Contract

Always report:

  1. Skill: target path and normalized root
  2. Mode: plan or rewrite
  3. Top runtime issues: the highest-value Claude mismatches
  4. Artifacts: exact plan or rewritten file paths
  5. Guardrails applied: 3 to 5 bullets tied to Claude runtime behavior

If rewrite mode was used, also report:

  • which sections moved to references/
  • which frontmatter fields were added, removed, or intentionally omitted

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

38.34%
按下载量换算68

Claude

29.83%
按下载量换算53

Cursor

19.21%
按下载量换算34

Gemini CLI

9.25%
按下载量换算16

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/ulpi-io/skills --skill normalize-skill-for-claude 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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