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研究检索敏感数据github未标认证来源可访问许可证需确认审计提醒

resolve-reviews解决评论

Agent Skill

resolve-reviews 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

2,994

周安装

126

GitHub Stars

154

下载量

1,048
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:resolve-reviews(解决评论)
来源仓库:https://github.com/pbakaus/agent-reviews
仓库路径:skills/resolve-reviews
安装命令:
npx skills add https://github.com/pbakaus/agent-reviews --skill resolve-reviews
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/pbakaus/agent-reviews --skill resolve-reviews

简介

查找、检索和筛选与评论相关的信息。

  • 适合根据关键词快速定位候选结果。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。
  • 通过 npx skills add 命令从指定仓库安装并使用。
  • 需确认权限范围、维护状态,注意是否触发联网或文件读写。
  • resolve-reviews 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Automatically resolve all review comments (both human and bot) on the current PR. Uses a two-phase workflow: fix all existing issues, then poll for new ones until quiet.

Prerequisites

All commands below use npx agent-reviews. If the project uses a different package manager, substitute the appropriate runner (e.g., pnpm dlx agent-reviews for pnpm, yarn dlx agent-reviews for Yarn, bunx agent-reviews for Bun). Honor the user's package manager preference throughout.

Cloud environments only (e.g., Codespaces, remote agents): verify git author identity so CI checks can map commits to the user. Run git config --global --get user.email and if empty or a placeholder, set it manually. Skip this check in local environments.

Phase 1: FETCH & FIX (synchronous)

Step 1: Fetch All Comments (Expanded)

Run npx agent-reviews --unanswered --expanded

The CLI auto-detects the current branch, finds the associated PR, and authenticates via gh CLI or environment variables. If anything fails (no token, no PR, CLI not installed), it exits with a clear error message.

This shows all unanswered comments (both human and bot) with full detail: complete comment body (no truncation), diff hunk (code context), and all replies. Each comment shows its ID in brackets (e.g., [12345678]).

If zero comments are returned, print "No unanswered comments found" and skip to Phase 2.

Step 3: Process Each Unanswered Comment

For each comment from the expanded output, apply the appropriate evaluation based on whether the author is a bot or a human.

For Bot Comments

Read the referenced code and determine:

  1. TRUE POSITIVE - A real bug that needs fixing
  2. FALSE POSITIVE - Not actually a bug (intentional behavior, bot misunderstanding)
  3. UNCERTAIN - Not sure; ask the user

Likely TRUE POSITIVE:

  • Code obviously violates stated behavior
  • Missing null checks on potentially undefined values
  • Type mismatches or incorrect function signatures
  • Logic errors in conditionals
  • Missing error handling for documented failure cases

Likely FALSE POSITIVE:

  • Bot doesn't understand the framework/library patterns
  • Code is intentionally structured that way (with comments explaining why)
  • Bot is flagging style preferences, not bugs
  • The "bug" is actually a feature or intentional behavior
  • Bot misread the code flow

For Human Comments

Read the referenced code and the reviewer's comment. Human reviewers are generally more accurate and context-aware than bots. Determine:

  1. ACTIONABLE - The reviewer identified a real issue or requested a concrete change
  2. DISCUSSION - The comment raises a valid point but the right approach is unclear
  3. ALREADY ADDRESSED - The concern has already been fixed or is no longer relevant

Likely ACTIONABLE:

  • Reviewer points out a bug or logic error
  • Reviewer requests a specific code change
  • Reviewer identifies missing edge cases or error handling

Likely DISCUSSION -- ask the user:

  • Reviewer suggests an architectural change you're unsure about
  • Comment involves a tradeoff (performance vs readability, etc.)
  • The feedback is subjective without team consensus

When UNCERTAIN -- ask the user

For both bot and human comments:

  • The fix would require architectural changes
  • You're genuinely unsure if the behavior is intentional
  • Multiple valid interpretations exist
  • The fix could have unintended side effects

Act on Evaluation

If TRUE POSITIVE / ACTIONABLE: Fix the code. Track the comment ID and a brief description of the fix.

If FALSE POSITIVE: Do NOT change the code. Track the comment ID and the reason it's not a real bug.

If DISCUSSION: Ask the user to consult the PR author. Apply their decision and track it.

If ALREADY ADDRESSED: Track the comment ID and note why.

If UNCERTAIN: Ask the user. If they say skip, track it as skipped.

Do NOT reply to comments yet. Replies happen after the commit (Step 5).

Step 4: Commit and Push

After evaluating and fixing ALL unanswered comments:

  1. Run your project's lint and type-check
  2. Stage, commit, and push: git add -A git commit -m "fix: address PR review findings {List of changes made, grouped by reviewer/bot}" git push
  3. Capture the commit hash from the output.

Step 5: Reply to All Comments

Now that the commit hash exists, reply to every processed comment. The --resolve flag marks the review thread as resolved on GitHub.

For each TRUE POSITIVE / ACTIONABLE:

Run npx agent-reviews --reply <comment_id> "Fixed in {hash}. {Brief description of the fix}" --resolve

For each FALSE POSITIVE:

Run npx agent-reviews --reply <comment_id> "Won't fix: {reason}. {Explanation of why this is intentional or not applicable}" --resolve

For each DISCUSSION (after user decision):

Run npx agent-reviews --reply <comment_id> "{Outcome}. {Explanation of the decision and any changes made}" --resolve

For each ALREADY ADDRESSED:

Run npx agent-reviews --reply <comment_id> "Already addressed. {Explanation of when/how this was fixed}" --resolve

For each SKIPPED:

Run npx agent-reviews --reply <comment_id> "Skipped per user request" --resolve

DO NOT start Phase 2 until all replies are posted.


Phase 2: POLL FOR NEW COMMENTS (loop until quiet)

The watcher exits immediately when new comments are found (after a 5s grace period to catch batch posts). This means you run it in a loop: start watcher, process any comments it returns, restart watcher, repeat until the watcher times out with no new comments.

Step 6: Start Watcher Loop

Repeat the following until the watcher exits with no new comments:

6a. Launch the watcher in the background:

Run npx agent-reviews --watch as a background task.

6b. Wait for the background command to complete (default 10 minutes; override with --timeout).

6c. Check the output:

  • If new comments were found (output contains EXITING WITH NEW COMMENTS):

1. Use --detail <id> to read each new comment's full detail 2. Process them exactly as in Phase 1, Steps 3-5 (evaluate, fix, commit, push, reply) 3. Go back to Step 6a to restart the watcher

  • If no new comments (output contains WATCH COMPLETE): Stop looping and move to the Summary Report.

Summary Report

After both phases complete, provide a summary:

## PR Review Resolution Summary

### Results
- Fixed: X issues
- Already addressed: X
- Won't fix (false positives): X
- Discussion resolved: X
- Skipped per user: X

### By Reviewer/Bot
#### cursor[bot]
- {description} - Fixed in {commit}
- {description} - Won't fix: {reason}

#### @reviewer-name
- {description} - Fixed in {commit}

### Status
All findings addressed. Watch completed.

Important Notes

Response Policy

  • Every comment gets a response - No silent ignores
  • For bots: responses help train them and prevent re-raised false positives
  • For humans: replies keep reviewers informed and unblock approvals

User Interaction

  • Ask the user when uncertain about a finding
  • Don't guess on architectural or business logic questions
  • It's better to ask than to make a wrong fix or wrong dismissal
  • Human reviewers often have context you don't - defer to the author when unsure

Best Practices

  • Verify findings before fixing - bots have false positives, humans rarely do
  • Keep fixes minimal and focused - don't refactor unrelated code
  • Ensure type-check and lint pass before committing
  • Group related fixes into a single commit
  • Copilot suggestion blocks often contain ready-to-use fixes
  • If a human reviewer suggests a specific code change, prefer their version unless it introduces issues

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

36.94%
按下载量换算387

Claude

29.98%
按下载量换算314

Cursor

17%
按下载量换算178

Gemini CLI

9.29%
按下载量换算97

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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

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