跳到正文
cccskills
免费在 GitHub 公开

hooks-explainer

Documents the hook enforcement system, bypass mechanisms, and common failure patterns to help agents avoid getting stuck on protected path writes

中文简介正在准备中。当前显示原文说明。

查看安装方法

包含的文件(10)

  • SKILL.md2.5 KB
  • commands/hooks-explainer.md400 B
  • hooks/post-execute.cjs245 B
  • hooks/pre-execute.cjs250 B
  • references/research-requirements.md516 B
  • rules/hooks-explainer.md558 B
  • schemas/input.schema.json443 B
  • schemas/output.schema.json894 B
  • scripts/main.cjs5.2 KB
  • templates/implementation-template.md494 B

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Hooks Explainer

<identity> Hooks Explainer Skill - Documents the hook enforcement system, bypass mechanisms, and common failure patterns to help agents avoid getting stuck on protected path writes </identity> <capabilities> - Hooks Explainer primary function - Integration with agent ecosystem - Standardized output generation </capabilities> <instructions> <execution_process>

Step 1: Gather Context

Read relevant files and understand requirements

Step 2: Execute

Perform the skill's main function using available tools

Step 3: Output

Return results and save artifacts if applicable

</execution_process>

<best_practices>

  1. Follow existing project patterns: Follow this practice for best results
  2. Document all outputs clearly: Follow this practice for best results
  3. Handle errors gracefully: Follow this practice for best results

</best_practices> </instructions>

<examples> <usage_example> **Example Commands**:
# Invoke this skill
/hooks-explainer [arguments]

# Or run the script directly
node .claude/skills/hooks-explainer/scripts/main.cjs --help

</usage_example> </examples>

Search Protocol

For code discovery and search tasks, follow this priority order:

  1. `pnpm search:code "<query>"` (Primary intent-based search).
  2. `ripgrep` (for exact keyword/regex matches).
  3. semantic/structural search via code tools if available.

Memory Protocol (MANDATORY)

Before starting: ```bash cat .claude/context/memory/learnings.md cat .claude/context/memory/decisions.md ```

After completing:

  • New pattern -> `.claude/context/memory/learnings.md`
  • Issue found -> `.claude/context/memory/issues.md`
  • Decision made -> `.claude/context/memory/decisions.md`

ASSUME INTERRUPTION: Your context may reset. If it's not in memory, it didn't happen.

评价

还没有评价。欢迎分享你的使用感受。

评论

无需登录即可发表。欢迎分享使用感受、提问,或说明在哪些环境下无法运行。

还没有评论。来写第一条吧。

提交后会立即公开。请勿填写邮箱、电话等个人信息。URL 最多 2 个。

0 / 1000 字

此表单受 reCAPTCHA 保护,适用 Google 的隐私权政策和服务条款。

同一仓库的技能

Ensure accessibility in UI components including semantic HTML, ARIA attributes, keyboard navigation, and WCAG 2.2 AA compliance.

中文简介正在准备中。当前显示原文说明。

oimiragieo/agent-studio422026年7月14日 更新

Use when you want to improve response quality through meta-cognitive reasoning. Applies 15+ reasoning methods to reconsider and refine initial outputs.

中文简介正在准备中。当前显示原文说明。

oimiragieo/agent-studio422026年7月14日 更新

N-round opposing-stance debates for trade-off analysis. Assigns pro/con roles to agents, runs structured debate rounds with quality scoring, and produces a moderator synthesis with confidence-rated recommendation. Generalizable to architecture, technology, security, and design decisions.

中文简介正在准备中。当前显示原文说明。

oimiragieo/agent-studio422026年7月14日 更新

Force adversarial code review stance that eliminates confirmation bias — reviewer must find issues or re-analyze

中文简介正在准备中。当前显示原文说明。

oimiragieo/agent-studio422026年7月14日 更新

Creates specialized AI agents on-demand when no existing agent matches a request. Use when the Router cannot find a suitable agent for a task. Enables self-evolution by generating persistent agents.

中文简介正在准备中。当前显示原文说明。

oimiragieo/agent-studio422026年7月14日 更新

LLM-as-judge evaluation framework with 5-dimension rubric (accuracy, groundedness, coherence, completeness, helpfulness) for scoring AI-generated content quality with weighted composite scores and evidence citations

中文简介正在准备中。当前显示原文说明。

oimiragieo/agent-studio422026年7月14日 更新

查看 oimiragieo 的全部技能

报告此技能的问题