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Agent Skill · 研究检索

ck-help(CK 帮助)

ck-help 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。

ck-help 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描有未通过项,按安装量在研究检索类的 73,675 个 Skill 里排第 45,958。

总安装 816周安装 34GitHub Stars 6下载 272核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

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:ck-help(CK 帮助)
来源仓库:https://github.com/duc01226/easyplatform
仓库路径:skills/ck-help
安装命令:
npx skills add https://github.com/duc01226/easyplatform --skill ck-help
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/duc01226/easyplatform --skill ck-help

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于查找、检索和筛选相关信息,支持基于关键词或任务场景快速定位结果。适用于 Codex、Claude、Cursor、Gemini CLI 中需要结构化检索信息的场景。可结合来源仓库和原始 README 进一步核验具体功能和操作流程。安装前建议确认权限范围和维护状态,避免触发不必要的联网或文件操作。

ck-help 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/ck-help

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/duc01226/easyplatform --skill ck-help;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

ck-help 怎么安装?

在终端执行 npx skills add https://github.com/duc01226/easyplatform --skill ck-help。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

ck-help 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

ck-help 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

ck-help 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

ck-help 用的人多吗?

公开数据是累计安装 816 次,近一周安装 34 次,下载 272 次,GitHub 6 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

ck-help 安全吗?

第三方扫描有未通过项,风险较高。除非你确认过源码,否则不建议直接安装到常用环境。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
ck-help

CK 帮助 · 本页

8166需要联网未明确未通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

[IMPORTANT] Use TaskCreate to break ALL work into small tasks BEFORE starting — including tasks for each file read. This prevents context loss from long files. For simple tasks, AI MUST ATTENTION ask user whether to skip.
Critical Thinking Mindset — Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence >80% to act. Anti-hallucination: Never present guess as fact — cite sources for every claim, admit uncertainty freely, self-check output for errors, cross-reference independently, stay skeptical of own confidence — certainty without evidence root of all hallucination.
AI Mistake Prevention — Failure modes to avoid on every task: - Check downstream references before deleting. Deleting components causes documentation and code staleness cascades. Map all referencing files before removal. - Verify AI-generated content against actual code. AI hallucinates APIs, class names, and method signatures. Always grep to confirm existence before documenting or referencing. - Trace full dependency chain after edits. Changing a definition misses downstream variables and consumers derived from it. Always trace the full chain. - Trace ALL code paths when verifying correctness. Confirming code exists is not confirming it executes. Always trace early exits, error branches, and conditional skips — not just happy path. - When debugging, ask "whose responsibility?" before fixing. Trace whether bug is in caller (wrong data) or callee (wrong handling). Fix at responsible layer — never patch symptom site. - Assume existing values are intentional — ask WHY before changing. Before changing any constant, limit, flag, or pattern: read comments, check git blame, examine surrounding code. - Verify ALL affected outputs, not just the first. Changes touching multiple stacks require verifying EVERY output. One green check is not all green checks. - Holistic-first debugging — resist nearest-attention trap. When investigating any failure, list EVERY precondition first (config, env vars, DB names, endpoints, DI registrations, data preconditions), then verify each against evidence before forming any code-layer hypothesis. - Surgical changes — apply the diff test. Bug fix: every changed line must trace directly to the bug. Don't restyle or improve adjacent code. Enhancement task: implement improvements AND announce them explicitly. - Surface ambiguity before coding — don't pick silently. If request has multiple interpretations, present each with effort estimate and ask. Never assume all-records, file-based, or more complex path.

Quick Summary

Goal: Provide ClaudeKit usage guidance by running the help script and presenting results based on output type.

Workflow:

  1. Translate — Convert user arguments to English if needed
  2. Execute — Run python.claude/scripts/ck-help.py "$ARGUMENTS"
  3. Detect Type — Read @CK_OUTPUT_TYPE marker (comprehensive-docs, category-guide, command-details, search-results, task-recommendations)
  4. Present — Show COMPLETE script output verbatim, then add practical context and examples

Key Rules:

  • Never replace or summarize script output; always show it fully then enhance
  • /plan then /code is the correct flow; NEVER suggest /plan then /cook
  • /cook is standalone (has its own planning)

Be skeptical. Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence percentages (Idea should be more than 80%).

Think harder. All-in-one ClaudeKit guide. Run the script and present output based on type markers.

Pre-Processing

IMPORTANT: Always translate $ARGUMENTS to English before passing to script.

The Python script only understands English keywords. If $ARGUMENTS is in another language:

  1. Translate $ARGUMENTS to English
  2. Pass the translated English string to the script

Execution

python .claude/scripts/ck-help.py "$ARGUMENTS"

Output Type Detection

The script outputs a type marker on the first line: @CK_OUTPUT_TYPE:<type>

Read this marker and adjust your presentation accordingly:

@CK_OUTPUT_TYPE:comprehensive-docs

Full documentation (config, schema, setup guides).

Presentation:

  1. Show the COMPLETE script output verbatim - every section, every code block
  2. THEN ADD helpful context:

- Real-world usage examples ("For example, if you're working on multiple projects...") - Common gotchas and tips ("Watch out for:...") - Practical scenarios ("This is useful when...")

  1. End with a specific follow-up question

Example enhancement after showing full output:

## Additional Tips

**When to use global vs local config:**
- Use global (~/.claude/.ck.json) for personal preferences like language, issue prefix style
- Use local (./.claude/.ck.json) for project-specific paths, naming conventions

**Common setup for teams:**
Each team member sets their locale globally, but projects share local config via git.

Need help setting up a specific configuration?

@CK_OUTPUT_TYPE:category-guide

Workflow guides for command categories (fix, plan, cook, etc.).

Presentation:

  1. Show the complete workflow and command list
  2. ADD practical context:

- When to use this workflow vs alternatives - Real example: "If you encounter a bug in authentication, start with..." - Transition tips between commands

  1. Offer to help with a specific task

@CK_OUTPUT_TYPE:command-details

Single command documentation.

Presentation:

  1. Show full command info from script
  2. ADD:

- Concrete usage example with realistic input - When this command shines vs alternatives - Common flags or variations

  1. Offer to run the command for them

@CK_OUTPUT_TYPE:search-results

Search matches for a keyword.

Presentation:

  1. Show all matches from script
  2. HELP user navigate:

- Group by relevance if many results - Suggest most likely match based on context - Offer to explain any specific command

  1. Ask what they're trying to accomplish

@CK_OUTPUT_TYPE:task-recommendations

Task-based command suggestions.

Presentation:

  1. Show recommended commands from script
  2. EXPLAIN the reasoning:

- Why these commands fit the task - Suggested order of execution - What each step accomplishes

  1. Offer to start with the first recommended command

Key Principle

Script output = foundation. Your additions = value-add.

Never replace or summarize the script output. Always show it fully, then enhance with your knowledge and context.

Important: Correct Workflows

  • /plan → /code: Plan first, then execute the plan
  • /cook: Standalone - plans internally, no separate /plan needed
  • NEVER suggest /plan → /cook (cook has its own planning)

Closing Reminders

  • IMPORTANT MUST ATTENTION break work into small todo tasks using TaskCreate BEFORE starting
  • IMPORTANT MUST ATTENTION search codebase for 3+ similar patterns before creating new code
  • IMPORTANT MUST ATTENTION cite file:line evidence for every claim (confidence >80% to act)
  • IMPORTANT MUST ATTENTION add a final review todo task to verify work quality
  • MUST ATTENTION apply critical thinking — every claim needs traced proof, confidence >80% to act. Anti-hallucination: never present guess as fact.
  • MUST ATTENTION apply AI mistake prevention — holistic-first debugging, fix at responsible layer, surface ambiguity before coding, re-read files after compaction.

[TASK-PLANNING] Before acting, analyze task scope and systematically break it into small todo tasks and sub-tasks using TaskCreate.

平台分布

Codex

35.49%
按下载量换算97

Claude

32.94%
按下载量换算90

Cursor

19.13%
按下载量换算52

Gemini CLI

10.26%
按下载量换算28

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

未通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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