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Agent Skill · 研究检索

tracer-dev(追踪器开发)

tracer-dev 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。

tracer-dev 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,权限为调用外部服务;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 62,606。

总安装 329周安装 14GitHub Stars 23下载 115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:tracer-dev(追踪器开发)
来源仓库:https://github.com/ajoslin/dot
仓库路径:skills/tracer-dev
安装命令:
npx skills add https://github.com/ajoslin/dot --skill tracer-dev
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/ajoslin/dot --skill tracer-dev

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。适合在需要快速定位关键词或任务场景时使用。可结合来源仓库和原始 README 继续核验具体用法。安装命令:npx skills add https://github.com/ajoslin/dot --skill tracer-dev 建议确认权限范围和是否执行命令后再使用

来源仓库内路径:skills/tracer-dev

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/ajoslin/dot --skill tracer-dev;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

    它需要调用外部服务,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

tracer-dev 怎么安装?

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

tracer-dev 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。

tracer-dev 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

tracer-dev 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。

tracer-dev 用的人多吗?

公开数据是累计安装 329 次,近一周安装 14 次,下载 115 次,GitHub 23 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。

tracer-dev 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
tracer-dev

追踪器开发 · 本页

32923调用外部服务未明确未通过

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

Tracer Development

Execute the build-validate-review cycle for tracer bullet development.

Locate State Files

Before any flow, find the plan files:

  • Search docs/tracers/**/state.json
  • If multiple matches, list them and use the ask question tool to ask questions about which feature to work on
  • If none, STOP: "Run spec-planner to create docs/specs//SPEC.md, then run /overseer-plan to create executable tasks"

Two files per feature:

  • state.json - Machine state (task passes, commits, current tracer)
  • PROGRESS.md - Human-readable plan and learnings

All state updates go to state.json. Learnings are appended to PROGRESS.md.

Decision Tree

Check state.json:
│
├─ No state.json found
│  └─ STOP: "Run spec-planner then /overseer-plan first to create a plan"
│
├─ Current tracer has tasks with passes: false
│  └─ → NEXT-TASK FLOW
│
├─ All tasks pass, tracer status != "complete"
│  └─ → REVIEW-TRACER FLOW
│
├─ Tracer complete, more tracers remain
│  └─ Advance currentTracer → NEXT-TASK FLOW
│
└─ All tracers status: "complete"
   └─ DONE: "Feature complete!"

NEXT-TASK FLOW

Precondition Check

Is lastReviewedTracer == currentTracer - 1?
├─ No → "Complete tracer review first"
└─ Yes → Continue

If feature status is planning, update it to in_progress in state.json before starting work.

Proceed immediately to Step 1 without asking for confirmation once preconditions are satisfied.

Step 1: Select Task

Read state.json and find first task with passes: false in the current tracer.

Also read the context block for patterns and key files to guide exploration.

Step 2: Write Micro-Plan

Before ANY code, produce a brief plan:

## Micro-Plan: Task X.Y - <name>

**Goal**: <one sentence>

**Implementation** (minimal):
1. <step>
2. <step>
...

**Validation**:
- <how we prove this works>

**Not doing** (explicit scope):
- <what we're deferring>

Step 3: Implement

Key principles:

  • Use EXISTING abstractions before creating new ones
  • Minimal code that satisfies the task
  • Production bar: types + error handling
  • No speculative features

Step 4: Validate

Run ALL verification steps from the task's steps array. Also run project validation (typecheck, tests, lint).

  • Detect project scripts (package.json, Makefile) or use the ask question tool to ask questions if unclear
  • If a step cannot run, mark SKIPPED with reason
  • All steps must pass before proceeding

Step 5: Code Review Gate (BLOCKING)

afplay /System/Library/Sounds/Ping.aiff

Present to user:

## Code Review: Task X.Y

Files changed:
- <file> (+X, -Y)

Verification steps:
- <step 1>: PASS
- <step 2>: PASS

Project validation:
- Typecheck: PASS or SKIPPED (reason)
- Tests: PASS or SKIPPED (reason)
- Lint: PASS or SKIPPED (reason)

Request approval inline (do not open question mode): reply **"lgtm"** to approve, or provide feedback.

WAIT FOR USER RESPONSE

  • "lgtm" (exactly) → Continue to commit
  • Any other response → Treat as feedback, revise, re-request review

Loop until user says "lgtm".

After "lgtm", proceed immediately to commit, mark the task complete, and start the next task without asking for confirmation.

Step 6: Commit + State Update (Background Agent)

After approval, always commit the task. This ensures the next task's review only shows new changes.

Run the commit and state.json update using a background agent with openrouter/z-ai/glm-4.7-flash.

git add -A && git commit -m "feat(<scope>): <task description>"

Step 7: Mark Task Complete

Update state.json for the task (handled by the background agent):

{
  "passes": true,
  "commit": "<commit-hash>"
}

Continue to next task, or if all tasks in current tracer have passes: true → REVIEW-TRACER FLOW.


REVIEW-TRACER FLOW

Precondition

All tasks in current tracer have passes: true in state.json.

Step 1: Definition of Done Audit

Check each criterion from the tracer's proves field:

## DoD Audit: Tracer N

proves: "<what this tracer validates>"

Evidence:
- [x] <criterion>: <evidence>
- [x] <criterion>: <evidence>
- [ ] <criterion>: MISSING - <what's needed>

If any criterion unmet → Add tasks to state.json (with passes: false), return to NEXT-TASK FLOW. If tasks are added after a tracer was reviewed, set in state.json:

{
  "lastReviewedTracer": N-1,
  "currentTracer": N
}

Step 2: Demo

afplay /System/Library/Sounds/Hero.aiff

Present demo instructions:

## Demo: Tracer N

Please run:

    <demo command from PROGRESS.md>

Expected result:
<expected output from PROGRESS.md>

Request response inline (do not open question mode): run the demo and reply "pass" to continue, or describe what went wrong.

WAIT FOR USER RESPONSE

Continuation Logic

  • "pass" → Continue to learnings
  • Any other response → Treat as feedback, discuss adjustments, may add tasks

Step 3: Record Learnings

Use the ask question tool to ask questions:

What did we learn from this tracer?
- Decisions made?
- Surprises?
- Things to remember for future tracers?

Update both files:

state.json - Add to tracer's learnings array:

{
  "learnings": ["<learning>", "<learning>"]
}

PROGRESS.md - Append under the tracer's Learnings section:

### Learnings

- <learning>
- <learning>

Step 4: Update Future Tracers

Review remaining tracers in light of learnings:

## Future Tracer Review

Based on learnings from Tracer N:

Tracer N+1: <name>
- Still makes sense? [yes/adjust]
- Demo still valid? [yes/adjust]
- New tasks needed? [no/add]

Update PROGRESS.md if any changes needed.

Step 5: Mark Tracer Complete

Update state.json:

{
  "lastReviewedTracer": N,
  "currentTracer": N+1,
  "tracers": [{
    "id": N,
    "status": "complete",
    "completed": "<ISO date>"
  }]
}

If this was the final tracer, also set:

{
  "status": "complete"
}

Step 6: Celebrate

afplay /System/Library/Sounds/Funk.aiff
Tracer N complete!

Progress: N/<total> tracers done
Next: Tracer N+1 - <name>

Continuing to the next tracer.

适合场景

01

调用多模型

02

代码和文本生成

03

Agent 推理流程

04

OpenRouter 模型接入

能力概览

能力 1

统一调用多种 LLM

能力 2

支持 Claude、Gemini、Kimi 等模型

能力 3

适合聊天、代码和推理任务

能力 4

可作为 Agent 模型调用入口

平台分布

Codex

35.38%
按下载量换算41

Claude

28.52%
按下载量换算33

Cursor

20.63%
按下载量换算24

Gemini CLI

10.39%
按下载量换算12

安全审计

Gen Agent Trust Hub

未通过

Socket

通过

Snyk

未通过

权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

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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