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Agent Skill · 研究检索

compound-eng-receiving-code-review(复合工程接受代码审查)

compound-eng-receiving-code-review 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。

compound-eng-receiving-code-review 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为需要联网;许可证为 MIT-0,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 14,422。

总安装 8,561周安装 364GitHub Stars 公开资料未说明下载 2,999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
3.0.5

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:compound-eng-receiving-code-review(复合工程接受代码审查)
来源仓库:https://github.com/iliaal/compound-eng-receiving-code-review
安装命令:
openclaw skills install compound-eng-receiving-code-review
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 compound-eng-receiving-code-review

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。

compound-eng-receiving-code-review 批判性处理代码审查反馈,拒绝不正确建议。适用于 OpenClaw 中接收外部评审意见或 AI 生成修改建议时使用。支持验证建议准确性,避免盲目执行可能引入风险的变更。安装需确认项目代码可读权限,建议建立内部评审协议规范流程。

涉及高危操作时应二次确认变更影响,防止破坏现有功能稳定性。

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 compound-eng-receiving-code-review;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

compound-eng-receiving-code-review 怎么安装?

在终端执行 openclaw skills install compound-eng-receiving-code-review。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

compound-eng-receiving-code-review 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。

compound-eng-receiving-code-review 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。

compound-eng-receiving-code-review 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。

compound-eng-receiving-code-review 用的人多吗?

公开数据是累计安装 8,561 次,近一周安装 364 次,下载 2,999 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。

compound-eng-receiving-code-review 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

  • 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。
  • 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

  • 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。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 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
compound-eng-receiving-code-review

复合工程接受代码审查 · 本页

8,561—需要联网MIT-0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

name
ia-receiving-code-review
class
discipline
description
>-

Receiving Code Review

Core Principle

Verify before implementing. Technical correctness matters more than social comfort. A reviewer can be wrong -- blindly implementing bad suggestions creates bugs.

Response Pattern

For each piece of feedback, follow this sequence:

0. Prior feedback check (re-reviews only) -- if this is not the first review round, check whether previously flagged issues were addressed before processing new comments. Compare the current diff against prior review threads (gh api repos/{owner}/{repo}/pulls/{pr}/comments). Surface any that were ignored or only partially fixed -- these take priority over new feedback.

  1. Read -- Understand what's being suggested and why
  2. Verify -- Is the suggestion technically correct for THIS codebase?
  3. Evaluate -- Does it improve the code, or is it preference/style?
  4. Respond -- Agree with evidence, disagree with evidence, or ask for clarification
  5. Implement -- Only after verification confirms the suggestion is correct

Triage all feedback first (see Implementation Order below), then implement one item at a time. Don't batch-implement everything at once.

Handling Unclear Feedback

When feedback is ambiguous or incomplete:

  • Stop -- do not implement anything unclear
  • Clarify ALL unclear items before implementing ANY of them (they may be related)
  • Ask specific questions: "Are you suggesting X or Y?" not "Can you elaborate?"
  • If the reviewer's intent is clear but the technical approach is wrong, say so

Batched clarification for critical-path ambiguity: When multiple ambiguous findings land on critical-path code (auth, payments, data migrations, permission checks) AND the AskUserQuestion tool is available, batch up to 4 of them into a single call rather than asking one at a time. Each question's header is the truncated filename and line, and the options are Valid / False positive / Defer. Skip the batched ask entirely when ambiguous findings are only on non-critical paths — just auto-triage those and move on. If AskUserQuestion is not available, fall back to a single prose block listing all ambiguous items numbered, asking for Valid/False-positive/Defer decisions. The batching limit is 4 because it caps cleanly at that size; asking more becomes noise rather than judgment.

Source-Specific Handling

From the user (project owner)

  • Trusted context -- they know the codebase and business requirements
  • Implement after understanding, but still verify technical correctness
  • Ask clarifying questions when the intent is clear but the approach seems risky
  • No performative agreement -- just acknowledge and implement

From automated review agents

  • Skeptical by default -- agents lack full context
  • Verify every suggestion against the actual codebase
  • Check for YAGNI violations (agents love adding "just in case" code)
  • Discard suggestions that contradict project conventions (check CLAUDE.md)
  • Agents may flag things that are intentional design decisions -- check before changing

From external reviewers (PR comments, open source)

  • Verify technical correctness for THIS stack and codebase
  • Check if the suggestion applies to this version of the framework/library
  • Push back if the reviewer lacks context about architectural decisions
  • Distinguish between "this is wrong" and "I would do it differently"

When to Push Back

Push back (with evidence) when a suggestion:

  • Breaks existing functionality -- "This would break X because Y depends on Z"
  • Violates project conventions -- "Our CLAUDE.md specifies we do it this way because..."
  • Is technically incorrect -- "This API was deprecated in v3. We're on v4 which uses..."
  • Adds unnecessary complexity -- "This handles a case that can't occur because..."
  • Is unused (YAGNI) -- when a reviewer suggests "implementing properly", grep the codebase for actual usage FIRST. Zero callers? Suggest removal: "This endpoint isn't called. Remove it (YAGNI)?" If used, implement properly.
  • Conflicts with architectural decisions -- "We chose X over Y in the brainstorm because..."

Valid evidence: code references (file:line), test output, git blame/log, framework docs, reproduction steps, grep results showing usage patterns. Not evidence: "I think", "it should work", "it's fine", appeals to convention without citing the convention, or restating the original code as justification.

False-Positive Taxonomy (for dismissed suggestions)

When dismissing a suggestion (AUTO-DECLINE, manual push-back), tag the dismissal with one of four categories so the reviewer sees structured reasoning, not a bare "no":

CategoryReviewer's response citedEvidence requiredMaps to "When to Push Back"
FP-ASSUMPTIONReviewer assumed behavior that doesn't match the codeQuote the specific line that contradicts the assumption"Is technically incorrect"
FP-CONVENTIONSuggestion conflicts with this project's conventionsCite the CLAUDE.md rule, ADR, or the established pattern in file:line"Violates project conventions"
FP-ALREADY-HANDLEDThe concern is handled elsewhere (parent function, middleware, framework)Show the existing handler in file:line"Adds unnecessary complexity"
FP-OUT-OF-SCOPEValid concern but belongs in a separate changeState where it will be tracked (issue, todo, next PR)YAGNI / scope creep

Use the tag in the reply: "FP-ALREADY-HANDLED: null check happens in auth/middleware.ts:42 before this handler runs. Keeping as-is." Structured tags prevent the "you're wrong because reasons" reply pattern and make future triage faster (if the same comment class keeps hitting FP-CONVENTION, the convention needs better documentation).

When NOT to Push Back

Accept feedback when:

  • The suggestion is correct and you missed something
  • It catches a genuine bug or edge case
  • It improves readability without changing behavior
  • It aligns with project conventions you overlooked
  • The reviewer has domain expertise you lack

Common Mistakes

MistakeFix
Agreeing before verifyingVerify first, then state what you found
Implementing without understanding impactTrace the change through callers before editing
Apologizing instead of fixingState the correction factually, then implement
Thanking the reviewer instead of responding technicallyDelete "Thanks" -- state the fix instead
Pushing back without evidenceInclude the specific code path or test that proves your point
Batch-implementing then testingTest after each individual fix
Can't verify the suggestionSay so: "Can't verify this without [X]. Should I [investigate/ask/proceed]?" -- don't guess or implement blind

Approved Response Templates

When feedback IS correct: "Verified -- [specific issue]. Implementing [specific fix]." When feedback is partially correct: "The [X part] is right because [reason]. The [Y part] doesn't apply here because [evidence]." When you need clarification: "Can you clarify [specific ambiguity]? The comment could mean [A] or [B], which changes the fix."

Implementation Order

After triaging all feedback:

  1. Clarify -- resolve all unclear items first
  2. Blocking issues -- fix things that break functionality
  3. Simple fixes -- quick wins that are clearly correct
  4. Complex fixes -- changes that need careful implementation

Test after each individual fix, not after implementing everything.

When Your Pushback Was Wrong

State the correction factually: "Checked this, you're correct because [reason]. Implementing." No extended apology, no self-deprecation -- just acknowledge and move on.

GitHub PR Reviews

  • Reply in the inline comment thread, not as top-level PR comments: gh api repos/{owner}/{repo}/pulls/{pr}/comments -f body="..." -f in_reply_to={comment_id}
  • Reference specific lines when explaining why you disagree
  • Mark conversations as resolved only after the fix is verified
  • If a suggestion spawns a larger discussion, suggest moving it to an issue

Headless Mode

When invoked programmatically (by another skill or command with mode:headless), skip interactive prompts and return structured triage results. See headless-mode.md for the classification table (AUTO-FIX / AUTO-DECLINE / ESCALATE), output format, and constraints.

Scope vs ia-pr-comment-resolver Agent

This skill and the ia-pr-comment-resolver agent handle different situations:

This skill (interactive)This skill (headless)ia-pr-comment-resolver agent
WhenInteractive review requiring judgmentProgrammatic triage by another skill/commandImplementing a single pre-triaged comment
ApproachVerify, evaluate, potentially push backAuto-classify and return triage resultsImplement a single pre-classified change
SkepticismHigh -- check correctness firstHigh -- same rules, automated classificationLow -- comments are pre-triaged
Use forUnclear suggestions, architectural feedbackBatch triage before dispatching resolversClear-cut fixes, style nits, typos

When the ia-pr-comment-resolver agent encounters feedback that requires judgment (architectural decisions, debatable trade-offs), it should escalate rather than implement.

Examples

Bad -- performative agreement:

Reviewer: "This should use a Map instead of an object for better performance." Response: "Great catch! Switching to Map now."

Good -- verify first:

Reviewer: "This should use a Map instead of an object for better performance." Response: "Checked this -- the object has at most 5 keys (bounded by the enum). Map overhead isn't justified here. Keeping as-is."

Bad -- blind implementation:

Reviewer: "Add null checks for the user parameter." Response: "Done, added null checks."

Good -- verify the premise:

Reviewer: "Add null checks for the user parameter." Response: "Traced the call chain -- user comes from the auth middleware which guarantees non-null (throws 401 otherwise). Adding a null check here would be dead code. Should I add it anyway for defense-in-depth?"

Good -- unclear item:

Reviewer: "This logic seems off." Response: "Can you clarify which part? The filter predicate, the sort order, or the pagination logic?"

Verify

  • All feedback items triaged (classified as correct, incorrect, or unclear)
  • Ambiguous items clarified before any implementation
  • Each fix verified individually (test after each, not batch)
  • No performative agreement phrases in responses ("Great catch!", "Absolutely right")

Integration

This skill pairs with:

  • ia-code-review -- the outbound side (requesting reviews). Their action-routing tiers (safe_auto/gated_auto/manual/advisory) roughly map to this skill's AUTO-FIX / ESCALATE-for-approval / ESCALATE / FYI.
  • ia-pr-comment-resolver agent -- for mechanical PR comment resolution (see scope table above)
  • ia-verification-before-completion -- verify each fix before marking resolved

平台分布

OpenClaw

73.06%
按下载量换算2,191

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

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。目前只有一个公开来源,建议同时核对源仓库。

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