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improveimprove 搜索

Agent Skill

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。

总安装

717

周安装

29

GitHub Stars

43

下载量

225
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

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

简介

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。

SKILL.md

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

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

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

external-service

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。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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