Token导航 LogoToken导航

Agent Skill · 研究检索

ultra-agent-stinct(超级特工本能)

ultra-agent-stinct 用于查找、检索和筛选相关信息,适合在 OpenClaw 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。

ultra-agent-stinct 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为执行命令;许可证为 MIT-0,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 5,595。

总安装 25,185周安装 1,039GitHub Stars 公开资料未说明下载 8,229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
MIT-0
版本
1.2.0

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:ultra-agent-stinct(超级特工本能)
来源仓库:https://github.com/grimmjoww/ultra-agent-stinct
安装命令:
openclaw skills install ultra-agent-stinct
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install ultra-agent-stinct

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。

超级特工本能用于查找、检索和筛选相关信息,适合在 OpenClaw 中快速定位候选结果。适用于需要根据关键词或任务场景进行信息搜索和线索筛选的场景。通过 clawhub 安装后,结合来源仓库和 README 文档即可使用具体功能。安装前需确认权限范围、维护状态,注意是否涉及联网或文件操作。

建议核验原始 README 了解实际能力边界和使用限制。

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 OpenClaw;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 openclaw skills install ultra-agent-stinct;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

    它需要执行命令,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

ultra-agent-stinct 怎么安装?

在终端执行 openclaw skills install ultra-agent-stinct。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

ultra-agent-stinct 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。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。

ultra-agent-stinct 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 openclaw skills install ultra-agent-stinct 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。

ultra-agent-stinct 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

ultra-agent-stinct 用的人多吗?

公开数据是累计安装 25,185 次,近一周安装 1,039 次,下载 8,229 次。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。

ultra-agent-stinct 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。

先想清楚的地方

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 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 OpenClaw,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

  • 不能接受 Skill 在你机器上执行命令的人。
  • 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
ultra-agent-stinct

超级特工本能 · 本页

25,185—执行命令MIT-0有提醒

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

name
ultra-agent-stinct
description
Internal debugging and coding skill. Activates automatically when YOU hit a code error, build failure, stack trace, or unexpected behavior during any task. This is your instinct for fixing things — not a user-triggered skill. If a command fails, a script throws an error, or something breaks while you're working, use this to debug and fix it yourself.
version
1.2.0
author
grimmjoww
homepage
https://github.com/grimmjoww/ultra-agent-stinct
metadata
{"openclaw": {"emoji": "\⚡", "os": ["darwin", "linux", "win32"]}}

Ultra Agent Stinct

Your internal debugging instinct. When something breaks while you're working, this is how you fix it.

Always Follow These (Any Time You Touch Code)

These rules apply every time, even for quick fixes. No exceptions.

Safety

  1. Read before edit. Never edit without read first — exact text match required or it fails
  2. write overwrites entirely. Use edit for changes to existing files
  3. Never delete without asking. Prefer safe deletion over rm -rf
  4. Never push without asking. git push only when the user explicitly says to
  5. Never commit without asking. Stage and commit only on request
  6. Backup awareness. Before large refactors, suggest a branch or stash

Good Practices

  1. Always verify your fix. After every change, re-run the failing command or tests. Never assume it worked
  2. Tell the user what happened. After fixing, briefly explain what broke and what you changed
  3. Read the error first. Don't guess at fixes — read the actual error message, stack trace, or test output before touching code
  4. Minimal changes. Fix the bug, don't refactor the neighborhood. Keep diffs small and focused

When to Activate Full Workflow

If you hit an error during a task, try a quick fix first while following the rules above. But if you:

  • Get stuck — your first fix didn't work, same error or new ones
  • Hit something complex — errors across multiple files, unfamiliar code, architectural issues
  • Need structure — not sure where the bug is or where to start

Then activate Ultra Agent Stinct — follow the full structured workflows below step by step.


Debug Workflow

When you encounter an error or something breaks:

1. Reproduce — Run the failing command:

exec command:"<failing command>" workdir:"<project dir>"

2. Read the error — Parse the stack trace. Identify file + line number.

3. Read the code — Read the relevant file(s):

read path:"<file from stack trace>"

4. Trace the cause — Follow the call chain. Read imports, dependencies, config. Check for:

  • Typos, wrong variable names
  • Missing imports or dependencies
  • Type mismatches, null/undefined access
  • Wrong paths, missing env vars
  • Logic errors in conditionals

5. Fix — Apply the minimal correct fix:

read path:"<file>"
edit path:"<file>" old:"<exact broken code>" new:"<fixed code>"

6. Verify — Re-run the original failing command. Confirm the fix works.

7. Report — Tell the user what broke and what you fixed (brief). Then continue your original task.

Writing New Code

When you need to create or modify code as part of a task:

1. Understand the project — Check existing patterns:

exec command:"ls -la" workdir:"<project dir>"

Read package.json, pyproject.toml, Cargo.toml, or equivalent. Match existing style and conventions.

2. Plan first — Before writing, outline what you'll create. Think through structure, dependencies, edge cases.

3. Write — Create the file:

write path:"<new file path>" content:"<complete file content>"

4. Verify — Run it, test it, make sure it actually works before moving on.

Running Tests

1. Find the test runner:

  • Node.js: npm test / npx jest / npx vitest
  • Python: pytest / python -m unittest
  • Rust: cargo test
  • Go: go test ./...

2. Run tests:

exec command:"<test command>" workdir:"<project>" timeout:120

3. On failure: Read the failing test, read the source under test, apply Debug Workflow.

4. On success: Report summary and continue.

Git Integration

Only when the user asks to commit, stage, or check git status.

exec command:"git status" workdir:"<project>"
exec command:"git diff --stat" workdir:"<project>"
exec command:"git add <specific files>" workdir:"<project>"
exec command:"git commit -m '<message>'" workdir:"<project>"

For detailed git workflows, see references/git-workflow.md.

Spawning Coding Agents (Heavy Tasks)

For large tasks (multi-file refactors, entire features, long builds), spawn a background agent:

exec pty:true workdir:"<project>" background:true command:"claude '<detailed task>'"

Monitor:

process action:list
process action:log sessionId:<id>
process action:poll sessionId:<id>

See references/escalation-guide.md for when to self-handle vs delegate.

Cross-Platform Quick Reference

TaskmacOS/LinuxWindows (Git Bash)
Find filesfind . -name "*.ts" -not -path "*/node_modules/*"Same
Search codegrep -rn "pattern" --include="*.ts" .Same
Process list`ps aux \grep node``tasklist \findstr node`
Kill processkill -9 <PID>taskkill //f //pid <PID>
Pythonpython3 (or python)python
Open fileopen <file>start <file>

Context Management

  • Keep tool calls focused — one task per chain
  • Don't read files already in your system prompt
  • For large files, read targeted sections rather than the whole thing
  • If context is getting heavy, summarize findings before continuing

平台分布

OpenClaw

94.69%
按下载量换算7,792

安全审计

VirusTotal

可疑

ClawScan

通过

Static analysis

未展示

权限和风险

执行命令

安装流程涉及命令执行,可能通过 openclaw skills install ultra-agent-stinct 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。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。

继续浏览同类 Skills