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Agent Skill · 研究检索

self-improving-agent(自我改进 Agent)

self-improving-agent 用于记录任务执行中的错误、用户纠正、经验和能力缺口,适合在 Codex、Claude、Cursor、Gemini CLI 中希望让 Agent 持续沉淀问题、修正和最佳实践时使用。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。

self-improving-agent 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 13,584。

总安装 9,253周安装 378GitHub Stars 公开资料未说明下载 2,994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:self-improving-agent(自我改进 Agent)
来源仓库:https://github.com/grail-computer/self-improving-agent
仓库路径:skills/self-improving-agent
安装命令:
npx skills add https://github.com/grail-computer/self-improving-agent --skill self-improving-agent
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/grail-computer/self-improving-agent --skill self-improving-agent

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。

self-improving-agent 用于记录任务执行中的错误、用户纠正和经验缺口。适合让 Agent 持续沉淀问题、修正实践并提升自我优化能力。通过 npx skills add 从 GitHub 仓库安装并使用。安装前应确认权限范围、维护状态及是否涉及联网或文件操作。

建议参考原始 README 了解具体实现细节和使用限制。

来源仓库内路径:skills/self-improving-agent

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/grail-computer/self-improving-agent --skill se…;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

self-improving-agent 怎么安装?

在终端执行 npx skills add https://github.com/grail-computer/self-improving-agent --skill self-improvi…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

self-improving-agent 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。

self-improving-agent 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。

self-improving-agent 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。

self-improving-agent 用的人多吗?

公开数据是累计安装 9,253 次,近一周安装 378 次,下载 2,994 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。

self-improving-agent 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
self-improving-agent

自我改进 Agent · 本页

9,253—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

Self-Improving Agent

When to use this skill: - After completing a significant task (post-task reflection) - When you notice yourself repeating a multi-step workflow - When a human corrects your behavior and you need to persist the correction - When the codebase map in AGENTS.md is stale - At the end of a working session

Step 1: Diagnose What Needs Improving

Ask yourself these questions after completing work:

  1. Did I wander? Did I spend time searching for files that should have been in the codebase map?

- → Update the Codebase Map in AGENTS.md

  1. Did I get corrected? Did the human tell me to do something differently?

- → Add the correction to Local Norms, Guardrails, or Patterns & Gotchas in AGENTS.md

  1. Did I repeat a workflow? Did I follow a multi-step procedure that I've done before (or will likely do again)?

- → Create a new skill (see Step 3 below)

  1. Did something surprise me? Did I discover a gotcha, a deprecated API, or a non-obvious coupling?

- → Add it to Patterns & Gotchas in AGENTS.md

  1. Is the AGENTS.md stale? Do the norms, entry points, or conventions no longer match the actual codebase?

- → Update the outdated sections now

If none of these apply, no action is needed. Don't create artifacts for the sake of it.


Step 2: Update AGENTS.md

When updating AGENTS.md, follow these rules:

Codebase Map Updates

  1. Read the current map in AGENTS.md.
  2. Use find or ls (not recursive full-tree) to see the actual top-level structure.
  3. Update only the parts that have changed. Don't rewrite the whole map.
  4. Focus on: entry points, directory roles, config files, test locations.

Adding Norms or Guardrails

  1. Write the rule as a short, imperative statement — one line if possible.
  2. Place it in the correct section:

- Local Norms → How to build, test, run, or style code in this repo - Guardrails → What the agent must NEVER do - Patterns & Gotchas → Non-obvious discoveries about the codebase

  1. If a correction contradicts an existing entry, update the existing entry rather than adding a duplicate.

Quality Checks

  • Keep entries concise. Agents read this every session — brevity compounds.
  • Remove placeholder/example entries (italicized) once real entries exist.
  • Don't add generic advice. Every entry should be specific to this repo.

Step 3: Create a New Skill

Use this procedure when you've identified a repeatable workflow worth capturing.

Decision: Is This a Skill or an AGENTS.md Entry?

Is it a multi-step procedure with a clear output?
  → YES → Skill
  → NO  → AGENTS.md entry

Is it specific to HOW this repo works (norms, navigation)?
  → YES → AGENTS.md entry
  → NO  → Skill

Am I unsure?
  → Start as an AGENTS.md entry. Promote to skill if it grows.

Creating the Skill

  1. Choose a name. Use a verb-noun pattern reflecting the job: debug-ci, draft-release-notes, run-migration, etc.
  2. Create the folder and file: skills/<skill-name>/SKILL.md
  3. Write the SKILL.md with this structure: --- name: <skill-name> description: <one-line description of what job this skill does> --- # <Skill Name> > **When to use:** <clear trigger condition> ## Steps 1. <Step 1 — be specific and imperative> 2. <Step 2> 3.... ## Output Contract <What "done" looks like. Be specific about format, location, and quality.>
  4. Key principles for good skills:

- Frame around a job to be done, not a tool ("debug CI failure", not "use grep") - Make the trigger clear — when should an agent reach for this? - Define the output contract — what does "done" look like? - Include examples of good output as assets if helpful (put in skills/<name>/examples/) - Keep steps imperative and specific — avoid vague instructions

  1. Add the new skill to the skills table in AGENTS.md: | [<skill-name>](skills/<skill-name>/SKILL.md) | <purpose> | <trigger> |

Adding Scripts or Assets to a Skill

If a skill needs deterministic execution (not just LLM judgment), add scripts:

skills/<skill-name>/
├── SKILL.md          # The playbook (always required)
├── scripts/          # Helper scripts for deterministic steps
│   └── validate.sh
└── examples/         # Reference outputs showing "good" quality
    └── example-output.md

Reference these from SKILL.md: "Run scripts/validate.sh to verify the output."


Step 4: Decide Scope — Repo-Local vs Global vs Shared

Does this skill only matter for THIS repo?
  → Keep it in skills/ within this repo (repo-local)

Have I felt this pain in another repo too?
  → Promote to ~/.agent/skills/<name>/ (machine-global)
  → Copy the skill folder there

Does my team keep repeating this workflow?
  → Promote to a shared repo or registry (shared)
  → Move the skill folder into the team's shared skills repo

Promotion Checklist

When promoting a skill from repo-local to global:

  1. Remove any repo-specific paths or references from the SKILL.md.
  2. Make the instructions generic enough for any project.
  3. Test it works without the original repo's context.
  4. Keep the repo-local version if it has repo-specific customizations.

Step 5: Validate the Improvement

After making any changes (AGENTS.md update or new skill):

  1. Re-read the updated file. Does it read clearly? Would a fresh agent session benefit from it?
  2. Check for contradictions. Does the new entry conflict with anything existing?
  3. Check for bloat. Is this file getting too long? If AGENTS.md exceeds ~200 lines, consider:

- Archiving old gotchas that are no longer relevant - Moving detailed procedures into skills - Summarizing verbose entries

  1. Commit the changes with a clear message: docs: update AGENTS.md with <what you learned> or feat: add <skill-name> skill for <job description>

Anti-Patterns to Avoid

❌ Don't✅ Do Instead
Add generic advice ("write clean code")Add repo-specific rules ("use pnpm, not npm")
Create skills for one-off tasksCreate skills for tasks you'll do again
Let AGENTS.md grow unboundedPrune stale entries, move procedures to skills
Write vague skill steps ("figure out what's wrong")Write specific steps ("run npm test, read the first failing assertion")
Create a skill around a toolCreate a skill around a job to be done
Start with shared/global skillsStart repo-local, promote when pain repeats

Quick Reference: The Compounding Loop

Work on task
    ↓
Complete task
    ↓
Reflect: Did I wander? Get corrected? Repeat a workflow? Discover a gotcha?
    ↓
    ├── Navigation miss     → Update Codebase Map
    ├── Behavior correction → Add to Local Norms / Guardrails
    ├── Repeated workflow   → Create a Skill
    ├── Surprise discovery  → Add to Patterns & Gotchas
    └── Nothing notable     → Move on
    ↓
Next task starts from a better baseline
*"The most valuable skill is the habit of watching yourself work."* Each improvement makes future improvements easier. That's how agents compound.

平台分布

Codex

34.16%
按下载量换算1,023

Claude

30.12%
按下载量换算902

Cursor

18.48%
按下载量换算553

Gemini CLI

7.99%
按下载量换算239

安全审计

Gen Agent Trust Hub

未通过

Socket

通过

Snyk

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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