Token导航 LogoToken导航TokenDH.com
研究检索需要联网clawhub未标认证来源可访问clear审计提醒

code-polish代码抛光

Agent Skill

code-polish 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。

总安装

3,263

周安装

132

GitHub Stars

公开资料未说明

下载量

1,024
OpenClaw

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

MIT-0

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:code-polish(代码抛光)
来源仓库:https://github.com/tenequm/code-polish
安装命令:
openclaw skills install code-polish
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 code-polish

简介

预发布代码审查工具,运行 lint 检查并启动多维度并行分析。

  • 适合在合并前对差异进行清洁度、设计和效率的综合评估。
  • 自动识别问题并提供修复示例,提升代码质量一致性。
  • 涉及 CI/CD 集成时应注意钩子配置和网络连接稳定性。
  • 安装前请确认是否支持当前项目的语言和框架。code-polish 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

name
polish
description
Pre-release code review - runs lint/type checks, then launches 3 parallel review agents (cleanliness, design, efficiency) to analyze the diff, synthesizes a unified report, and fixes with approval. Use before committing, pushing, or releasing changes. Triggers on "review code", "check before commit", "cleanup before release", "review changes", "is this ready to ship", "polish before release", "simplify".
metadata
version
2.2.1
disable-model-invocation
true

Pre-Release Polish

Current branch: !git rev-parse --abbrev-ref HEAD Uncommitted changes: !git diff --stat 2>/dev/null | tail -1

Rules

  • Read every changed file fully before reviewing - never assess code you haven't opened
  • Only flag real issues, not style preferences already handled by the formatter
  • Do NOT add comments, docstrings, or type annotations to code that doesn't have them
  • Distinguish legitimate operational logging (logger.info, logger.error) from debug leftovers (console.log, console.debug)
  • When fixing, make minimal targeted edits - don't refactor surrounding code
  • Only flag issues in changed/added lines, not pre-existing code
  • Reuse suggestions must point to a specific existing function/utility in the codebase, not hypothetical "you could extract this"
  • Do not flag efficiency on cold paths, one-time setup code, or scripts that run once

Phase 1: Automated Checks

Run the project's lint + type-check command. Check CLAUDE.md for the correct validation command (commonly pnpm check, just check, cargo clippy, uv run ruff check, etc.).

If checks fail:

  1. Fix all errors
  2. Re-run checks until clean
  3. Then proceed to Phase 2

If no validation command is found in CLAUDE.md, ask the user what to run.

Phase 2: Diff Analysis

Determine what changed:

  1. Check for uncommitted changes: git diff + git diff --cached
  2. If no uncommitted changes, diff against main: git diff main...HEAD
  3. If no changes at all, report "nothing to review" and stop

Read every changed file fully. Understand what each change does and why.

Phase 3: Parallel Review

Use the Agent tool to launch all three agents concurrently in a single message. Pass each agent the full diff and the list of changed files so it has the complete context.

Agent 1: Cleanliness

Fast, mechanical, high-confidence. Looks for junk that should be removed.

  • Debug leftovers: console.log, console.debug, console.warn added during development; temporary debug variables, hardcoded test values. NOT structured logger calls (logger.info, logger.error, c.var.logger)
  • AI slop: comments explaining obvious code ("// increment counter", "// return the result") - flag each such comment individually, even if the code it describes is also flagged under another category; JSDoc on internal/private functions that aren't part of a public API; verbose docstrings on simple helpers; TODO/FIXME/HACK markers left by Claude (not by the user); unnecessary type annotations where the language infers correctly; emoji in code or comments (unless the project uses them)
  • Dead code: unreferenced functions, variables, types; commented-out code blocks (git has history); unused function parameters (unless required by interface/callback signature)
  • Unused imports: imports added but never referenced, imports left behind after refactoring (linter catches most - verify edge cases)
  • Hardcoded values: magic numbers or strings that should be in constants; URLs, prices, limits that belong in config. NOT obvious constants like 0, 1, true, HTTP status codes

Agent 2: Design & Reuse

Requires codebase exploration beyond the diff. Looks for structural and design issues.

  • Reuse opportunities: search the codebase for existing utilities, helpers, and shared modules that could replace newly written code. Look in utility directories, shared modules, and files adjacent to the changed ones. Flag hand-rolled logic where a utility already exists (string manipulation, path handling, type guards, env checks)
  • Over-engineering: helper functions used exactly once (should be inlined); abstractions wrapping a single call with no added value; try/catch adding nothing (re-throwing same error, catching impossibilities); validation of internal data already validated at route boundary; feature flags or config for things that could just be code; backwards-compat shims for code that was just written
  • Redundant state: state that duplicates existing state; cached values that could be derived; observers/effects that could be direct calls
  • Parameter sprawl: adding new parameters to a function instead of generalizing or restructuring existing ones
  • Copy-paste with slight variation: near-duplicate code blocks that should be unified
  • Leaky abstractions: exposing internal details that should be encapsulated, or breaking existing abstraction boundaries
  • Stringly-typed code: using raw strings where constants, enums, or branded types already exist in the codebase
  • Structural issues: functions that grew too long during changes (>50 lines, consider splitting); inconsistent naming with existing codebase conventions

Agent 3: Efficiency

Looks for runtime performance and resource issues.

  • Redundant work: redundant computations, repeated file reads, duplicate network/API calls, N+1 patterns
  • Missed concurrency: independent operations run sequentially when they could run in parallel
  • Hot-path bloat: new blocking work added to startup or per-request/per-render hot paths
  • No-op updates: state/store updates inside polling loops, intervals, or event handlers that fire unconditionally without change detection. Also: wrapper functions that take updater/reducer callbacks but don't honor same-reference returns
  • TOCTOU anti-patterns: pre-checking file/resource existence before operating - operate directly and handle the error
  • Memory: unbounded data structures, missing cleanup, event listener leaks
  • Overly broad operations: reading entire files when only a portion is needed, loading all items when filtering for one
  • Unchecked system boundaries: fetch/HTTP calls without response status checks (r.ok), unhandled promise rejections on external calls, missing error handling at I/O boundaries

Phase 4: Validate Findings

Before presenting anything, verify every finding from the agents against actual code. Drop any finding that fails validation.

For each finding:

  • Read the exact file and lines cited - confirm the code exists and matches the description. Drop findings where the line number is wrong or the code doesn't match what was claimed
  • Dead code / unused imports - grep the entire codebase for references. If the symbol is referenced anywhere (imports, calls, type usage), drop the finding
  • Reuse suggestions - confirm the suggested utility/function actually exists at the claimed path. If it doesn't exist, drop the finding
  • Debug leftovers - confirm the flagged line is actually a debug artifact, not structured logging (logger.*, c.var.logger.*)
  • Efficiency / design claims - read the surrounding context to confirm the pattern matches. Drop speculative findings that don't hold up with full context

Only findings that survive validation proceed to the report.

Phase 5: Report

Synthesize validated findings into a single deduplicated report. If multiple agents flagged the same code, merge into one finding. Group by category:

## Review Findings

### Cleanliness (N issues)
1. `path/to/file.ts:42` - console.log("debug response")
2. ...

### Design (N issues)
1. `path/to/file.ts:15-18` - hand-rolled path join, use existing `resolveAssetPath` from shared/utils
2. ...

### Efficiency (N issues)
1. `path/to/file.ts:30-45` - sequential awaits on independent API calls, use Promise.all
2. ...

**Total: X issues across Y categories**

**Awaiting approval before proceeding with fixes.**

If zero issues found, report "Clean - no issues found" and stop.

The report MUST end with the line "Awaiting approval before proceeding with fixes." (or "Clean - no issues found"). Do not proceed to Phase 6 until the user explicitly approves.

Phase 6: Fix and Verify

After user approves:

  1. Fix all reported issues with minimal targeted edits
  2. Re-run the project's validation command
  3. If new errors appear, fix them
  4. Show summary: what was fixed, final check status

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

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

补充不同宿主或平台的使用分布数据

能力 5

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

OpenClaw

78.81%
按下载量换算807

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

可疑

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 warning/failed 结果,不能写成本站确认安全。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

继续浏览同类 Skills