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Agent Skill · 待分类

wtf.reflect(wtf 反映)

wtf.reflect 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。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。

wtf.reflect 是待分类类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为只读;许可证信息还不明确,暂无第三方扫描结果,按安装量在待分类类的 11,209 个 Skill 里排第 4,610。

总安装 710周安装 29GitHub Stars 3下载 230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:wtf.reflect(wtf 反映)
来源仓库:https://github.com/xiduzo/wtf
仓库路径:skills/wtf.reflect
安装命令:
npx skills add https://github.com/xiduzo/wtf --skill wtf.reflect
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/xiduzo/wtf --skill wtf.reflect

这个 Skill 是做什么的

这个 Skill 的分类还没最终确定,用法以来源仓库的说明为准。

wtf.reflect 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息。它适合在 Codex、Claude、Cursor、Gemini CLI 中围绕仓库状态、代码变更或协作事项进行整理。

通过 npx skills add 命令从 GitHub 仓库安装,具体用法需结合原始 README 进一步确认。安装前请核实权限范围、维护状态,并注意是否涉及联网、命令执行或文件读写操作。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/wtf.reflect

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/xiduzo/wtf --skill wtf.reflect;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

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

wtf.reflect 怎么安装?

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

wtf.reflect 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。

wtf.reflect 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

wtf.reflect 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。

wtf.reflect 用的人多吗?

公开数据是累计安装 710 次,近一周安装 29 次,下载 230 次,GitHub 3 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。

wtf.reflect 安全吗?

没有查到第三方扫描结果,安全性无法从公开资料判断,安装前请自行审查源码、依赖和命令行为。

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。
  • 标注为只读权限,试用阶段不容易误改本地文件。

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。
  • 没有第三方扫描结果,安全性只能靠自己读源码判断。
  • 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。
  • 需要处理待分类类任务、又不想每次都手写提示词的人。
  • 只想先试试效果、不希望它改动本地文件的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 要求有安全扫描结论才肯安装的团队。
  • 需要厂商级技术支持和 SLA 的生产系统。

待分类类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
infsh-cli

infsh CLI · Codex、Claude

4,374,576382权限未标注未明确未收录
ai-video-generation

AI 视频生成 · Codex、Claude

4,313,376382调用外部服务未明确有提醒
lark-openapi-explorer

云雀 OpenAPI 浏览器 · Codex、Claude

2,064,1209,011需要联网未明确有提醒
lark-workflow-standup-report

Lark 工作流程站立报告 · Codex、Claude

2,041,6328,978需要联网未明确通过
use-my-browser

使用我的浏览器 · Codex、Claude

1,848,49140操作浏览器未明确未通过
wtf.reflect

wtf 反映 · 本页

7103只读未明确未收录

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

WTF Reflect

Capture learnings from this session and route them into the right steering document. Every hard-won insight — especially about where the AI went wrong or where implementation was harder than expected — belongs in a steering doc so it guides future work automatically.

Intervention tracker: The hooks/track-interventions.sh hook runs automatically on every UserPromptSubmit event and increments /tmp/wtf.interventions-$(whoami)-$(basename "$(git rev-parse --show-toplevel 2>/dev/null)") when it detects correction or frustration language (e.g. "no,", "wrong", "actually", "stop that"). When the counter reaches 3, the hook prints a reminder at the end of the session to run wtf.reflect. Step 6 of this skill resets the counter to zero. No manual tracking is needed — the hook handles it.

Process

1. Check which steering docs exist

ls docs/steering/ 2>/dev/null

Build a map of which of the four docs are present: TECH.md, QA.md, DESIGN.md, VISION.md.

If none exist, call AskUserQuestion with:

  • question: "No steering docs found. Would you like to create them first?"
  • header: "No steering docs"
  • options: [{label: "Create them now", description: "Run the steer-* skills to set up the docs"}, {label: "Skip — just capture notes", description: "Save all learnings to docs/steering/LEARNINGS.md instead"}]

If Create them now → invoke wtf.steer-tech. Note that wtf.steer-tech will offer to chain to the other steer-* skills at the end — let the user complete that flow, then return here. When control returns, re-run the ls check to see which docs now exist. If Skip → set all four doc paths to the fallback: docs/steering/LEARNINGS.md.

If some exist but not all → continue. In step 4, route learnings for a missing doc to docs/steering/LEARNINGS.md as a per-doc fallback (create the file if needed).

2. Orient to the session

Briefly scan context to understand what was worked on:

  • Recent git commits: git log --oneline -10
  • Any failing/passing tests, PRs, or issues mentioned in conversation
  • Do NOT dump this at the user — use it only to pre-fill questions.

3. Gather learnings — one question at a time

Use AskUserQuestion for each question. Only ask questions that aren't already answered by context.

Q1 — What was harder than expected?

  • question: "What was harder or more painful than it should have been in this session?"
  • header: "Session friction"
  • options: pre-fill with 2–3 inferred options based on what was worked on (e.g. "Debugging X took too long", "Claude kept misunderstanding Y"), plus {label: "Something else", description: "I'll type it"} and {label: "Nothing — skip", description: "Session went smoothly"}

If Nothing — skip → skip to step 6 (reset counter) and exit with: "Great session — nothing to capture."

Q2 — Did Claude make a recurring mistake?

  • question: "Did Claude keep making the same mistake you had to correct?"
  • header: "AI mistakes"
  • options: [{label: "Yes — describe it", description: "I'll tell you what it kept doing"}, {label: "No recurring mistakes", description: "One-off issues only"}]

If Yes → call AskUserQuestion with:

  • question: "Describe the mistake briefly. What rule would prevent it next time?"
  • header: "AI mistake — the rule"
  • options: [{label: "I'll type the rule", description: "Free text"}, {label: "Skip", description: "Hard to articulate right now"}]

Q3 — What is the one rule this session taught you?

  • question: "If you had to write one rule that would have prevented the most wasted time today, what would it be?"
  • header: "The lesson"
  • options: pre-fill with 1–2 rules inferred from the session, plus {label: "I'll write it", description: "Free text"} and {label: "Skip this one", description: "Nothing to add"}

4. Route each learning to the right steering doc

For each learning gathered, determine where it belongs:

Learning typeTarget doc
Architecture pattern, implementation gotcha, AI coding mistakeTECH.md
Test failure pattern, flaky test cause, QA gapQA.md
Design inconsistency, component misuse, style mistakeDESIGN.md
Scope confusion, priority conflict, domain language driftVISION.md
Doesn't clearly fit one docTECH.md (default)

For each target doc:

  1. If the target doc does not exist (from the map built in step 1) → use docs/steering/LEARNINGS.md instead. Create it with a # Overflow Learnings heading if it doesn't exist yet.
  2. Read the current file.
  3. Look for a ## Hard-Won Lessons section.
  4. If it exists → append the new bullet(s) under it.
  5. If it does not exist → append the section at the end of the file, inserting it before the <!-- MANUAL ADDITIONS START --> marker if present.

Bullet format:

- **[Short label]** — [Concrete rule or observation]. *Learned [YYYY-MM-DD].*

Example:

- **Don't mock the auth middleware in tests** — Three tests passed with mocks but failed in CI against the real service. Always integrate against real dependencies. *Learned 2026-03-24.*

5. Write the updated steering docs

Write each modified doc. Then commit using today's date:

git add docs/steering/
git commit -m "docs(steering): add hard-won lessons from $(date +%Y-%m-%d) session"

6. Reset the intervention counter

echo "0" > /tmp/wtf.interventions-$(whoami)-$(basename "$(git rev-parse --show-toplevel 2>/dev/null)")

7. Close the loop

Print a brief summary:

  • Which docs were updated
  • How many learnings were captured
  • Remind the user: "These rules will guide every future session automatically."

平台分布

Codex

35.89%
按下载量换算83

Claude

28.5%
按下载量换算66

Cursor

20.34%
按下载量换算47

Gemini CLI

10.49%
按下载量换算24

安全审计

暂无安全审计结果可展示。

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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。目前只有一个公开来源,建议同时核对源仓库。

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