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Agent Skill · 研究检索

improve(improve 搜索)

improve 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。

improve 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,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 47,825。

总安装 717周安装 29GitHub Stars 43下载 225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:improve(improve 搜索)
来源仓库:https://github.com/0xbigboss/claude-code
仓库路径:skills/improve
安装命令:
npx skills add https://github.com/0xbigboss/claude-code --skill improve
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/0xbigboss/claude-code --skill improve

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。

该技能用于查找、检索和筛选相关信息。适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词、任务场景或来源线索快速定位候选结果。通过 npx skills add 命令从指定 GitHub 仓库安装使用。安装前需确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写操作。

建议结合原始 README 文档进一步核验具体用法和功能边界。

来源仓库内路径:skills/improve

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/0xbigboss/claude-code --skill improve;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

improve 怎么安装?

在终端执行 npx skills add https://github.com/0xbigboss/claude-code --skill improve。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

improve 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。

improve 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。

improve 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。

improve 用的人多吗?

公开数据是累计安装 717 次,近一周安装 29 次,下载 225 次,GitHub 43 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。

improve 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

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。
  • 第三方扫描已通过,常见的高风险行为没有命中。

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
improve

improve 搜索 · 本页

71743调用外部服务未明确通过

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

Improve

Structured improvement pass grounded in what was observed during this session.

Principles (Always Active)

  • Every suggestion must cite a specific observation — file path, error seen, pattern noticed, or behavior verified. "I saw X" beats "common practice suggests Y."
  • Distinguish grounded suggestions (observed evidence) from speculative ones (general knowledge). Mark speculative suggestions explicitly.
  • Prioritize by impact to the user, not by ease of description.
  • Do not suggest improvements that would change public API contracts, auth boundaries, or data schemas without flagging as high-risk.
  • Simplicity is a feature. Do not suggest adding complexity unless it prevents a concrete problem observed in this session.

When to Use

  • User asks "knowing what you know now, what are some improvements?" or similar
  • Before claiming done in a ralph loop (self-check)
  • Before generating a handoff
  • After completing a significant chunk of work
  • When reviewing code that was just written or modified

When Not to Use

  • At the start of a session before meaningful work has been done
  • When the user explicitly asks to skip review and ship
  • For architectural redesigns (use spec/plan flow instead)

Dimensions

Analyze across these dimensions. Skip any dimension with nothing grounded to say.

Correctness

Error handling gaps, unhandled edge cases, type safety issues, race conditions, missing validation at system boundaries.

Simplicity

Unnecessary indirection, dead code, naming that obscures intent, over-engineered abstractions, complexity that doesn't earn its keep. Reference the simplify skill for implementation.

Security

Auth boundary gaps, input validation holes, secret handling issues, OWASP concerns observed in touched code.

Test Coverage

Untested code paths observed during the session, missing test layers (unit/integration/e2e), fixture realism gaps, assertions that don't verify meaningful behavior.

Performance

Bottlenecks observed during the session (slow queries, N+1 patterns, unnecessary recomputation). Only flag what was actually observed, not hypothetical.

Developer Experience

API ergonomics issues, missing documentation for non-obvious behavior, CLI friction, configuration that should be extracted.

Workflow

  1. Gather context: Review what happened this session — files changed, commands run, errors encountered, tests written, patterns established.
  2. Analyze each dimension: For each, check whether session observations surface anything concrete. Skip dimensions with nothing to say.
  3. Structure each suggestion:
[IMP-N] effort/gate: summary
  Observation: what was seen (file:line, error message, test gap, etc.)
  Suggestion: concrete change
  Grounded: yes/no

Where:

  • effort: trivial (< 5 min) | small (< 30 min) | medium (hours)
  • gate: which delivery gate this strengthens: TDD | DEV | E2E | REVIEW | CI
  1. Sort by impact (highest first), not by dimension.
  2. Present as actionable list. If in a ralph loop, address trivial/small improvements inline before claiming done. Log medium improvements as decisions for the user to prioritize.

Integration with Ralph Loops

When running inside a ralph loop (.rl/state.json exists):

  • Run the improvement pass before .rl/rl done
  • Address trivial improvements inline — just fix them
  • Address small improvements if they're within the current milestone scope
  • Log medium improvements: .rl/rl log decision "IMP-N deferred: [reason]"
  • Do not expand scope beyond the task's milestones for medium improvements

Integration with Handoffs

When generating a handoff, include unaddressed improvements in the <next_steps> section. Use the same [IMP-N] format so the receiving agent can reference them.

Output Format

## Improvements

N suggestions (X grounded, Y speculative)

[IMP-1] trivial/DEV: Extract magic number to config constant
  Observation: `src/server.ts:42` uses hardcoded port 3000, but other services read from env
  Suggestion: Read from `PORT` env var with 3000 as default
  Grounded: yes

[IMP-2] small/TDD: Add boundary test for empty input
  Observation: `processItems([])` path untested — saw it handle non-empty arrays only in test suite
  Suggestion: Add test case for empty array input in `process-items.test.ts`
  Grounded: yes

[IMP-3] medium/E2E: Add timeout handling for external API calls
  Observation: Catalog search took 1.2s avg in profiling — no timeout configured
  Suggestion: Add configurable timeout with bounded retry
  Grounded: yes

Red Flags

  • Suggestions without observations — if you can't point to something specific, don't suggest it
  • More than 10 suggestions — focus on the top 5-7 by impact
  • Suggestions that expand scope beyond what was touched — stay within the blast radius of the current work
  • Generic "add more tests" without specifying which paths are untested

平台分布

Codex

36.76%
按下载量换算83

Claude

28.32%
按下载量换算64

Cursor

19.18%
按下载量换算43

Gemini CLI

9.92%
按下载量换算22

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

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。目前只有一个公开来源,建议同时核对源仓库。

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