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dyad%3amulti-pr-reviewdyad%3a 多重公关审核

Agent Skill

dyad%3amulti-pr-review 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

706

周安装

30

GitHub Stars

20,193

下载量

247
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:dyad%3amulti-pr-review(dyad%3a 多重公关审核)
来源仓库:https://github.com/dyad-sh/dyad
仓库路径:skills/dyad%3Amulti-pr-review
安装命令:
npx skills add https://github.com/dyad-sh/dyad --skill dyad:multi-pr-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 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/dyad-sh/dyad --skill dyad:multi-pr-review

简介

dyad:multi-pr-review 派生三个专业化子代理从不同角度评审 PR 代码变更。

  • 分别由正确性专家、代码健康专家和 UX 向导独立审查,减少偏见影响。
  • 通过 randomized 文件顺序分发降低排序偏差,最终聚合分析结果。
  • 使用前需确认 PR 差异可读性和子代理资源配置,注意可能增加执行时间。
  • dyad%3amulti-pr-review 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Multi-Agent PR Review

This skill spawns three independent sub-agents to review code changes from different perspectives, then validates and aggregates their findings through reasoned analysis.

Overview

  1. Fetch PR diff and existing comments
  2. Spawn 3 sub-agents with specialized personas using the Task tool

- Each agent receives files in a different randomized order to reduce ordering bias - Correctness Expert: Bugs, edge cases, control flow, security, error handling - Code Health Expert: Dead code, duplication, complexity, meaningful comments, abstractions - UX Wizard: User experience, consistency, accessibility, error states, delight

  1. Each agent reviews and classifies issues (HIGH/MEDIUM/LOW severity)
  2. Validate issues using reasoned analysis (not just vote counting)
  3. Determine merge verdict based on confirmed issues
  4. Filter out issues already commented on (deduplication)
  5. Post findings: summary with verdict + inline comments for HIGH/MEDIUM issues

Workflow

Step 1: Determine PR Number and Repo

Parse the PR number and repo from the user's input. If not provided, try to infer from the current git context:

# Get current repo
gh repo view --json nameWithOwner -q '.nameWithOwner'

# If user provides a PR URL, extract the number
# If user just says "review this PR", check for current branch PR
gh pr view --json number -q '.number'

Step 2: Fetch PR Diff and Context

IMPORTANT: Always save files to the current working directory (e.g. ./pr_diff.patch), never to /tmp/ or other directories outside the repo. In CI, only the repo working directory is accessible.

# Save the diff to current working directory (NOT /tmp/)
gh pr diff <PR_NUMBER> --repo <OWNER/REPO> > ./pr_diff.patch

# Get PR metadata
gh pr view <PR_NUMBER> --repo <OWNER/REPO> --json title,body,files,headRefOid

# Fetch existing comments to avoid duplicates
gh api repos/<OWNER/REPO>/pulls/<PR_NUMBER>/comments --paginate
gh api repos/<OWNER/REPO>/issues/<PR_NUMBER>/comments --paginate

Save the diff content and existing comments for use in the review.

Step 3: Spawn Review Agents in Parallel

Use the Task tool to spawn 3 sub-agents in parallel (all in a single message with multiple Task tool calls). Each agent should be a general-purpose subagent.

File Ordering: Before spawning, create 3 different orderings of the changed files (randomize/shuffle the order). Each agent gets the files in a different order to reduce ordering bias (reviewers tend to focus more on files they see first).

IMPORTANT: Each agent's prompt must include:

  1. Their role description (from the corresponding file in references/)
  2. The full PR diff content (inline, NOT a file path - agents cannot read files from the parent's context)
  3. The list of existing PR comments (so they can avoid flagging already-commented issues)
  4. Instructions to output findings as structured JSON

Agent Prompt Template

For each agent, the prompt should follow this structure:

You are a code reviewer with this specialization:

<role>
[Contents of references/<role>.md - e.g., correctness-reviewer.md]
</role>

You are reviewing PR #<NUMBER> in <REPO>: "<PR TITLE>"

<pr_description>
[PR body/description]
</pr_description>

Here is the diff to review (files presented in a specific order for this review):

<diff>
[Full diff content - with files in THIS agent's randomized order]
</diff>

Here are existing PR comments (do NOT flag issues already commented on):

<existing_comments>
[Existing comment data as JSON]
</existing_comments>

## Instructions

1. Read your role description carefully and review the diff from your expert perspective.
2. For each issue you find, classify it as HIGH, MEDIUM, or LOW severity using the guidelines in your role description.
3. Output your findings as a JSON array with this schema:

[ { "file": "path/to/file.ts", "line_start": 42, "line_end": 45, "severity": "MEDIUM", "category": "category-name", "title": "Brief title", "description": "Clear description of the issue and its impact", "suggestion": "How to fix (optional)" } ]


Severity levels:
- HIGH: Security vulnerabilities, data loss risks, crashes, broken functionality, UX blockers
- MEDIUM: Logic errors, edge cases, performance issues, sloppy code that hurts maintainability, UX issues that degrade the experience
- LOW: Minor style issues, nitpicks, minor polish improvements

Be thorough but focused. Only flag real issues, not nitpicks disguised as higher severity issues.

IMPORTANT: Cross-reference infrastructure changes (DB migrations, new tables/columns, API endpoints, config entries) against actual usage in the diff. If a migration creates a table but no code in the PR reads from or writes to it, that's dead infrastructure and should be flagged.

Output ONLY the JSON array, no other text.

Step 4: Collect and Parse Results

Wait for all 3 agents to complete. Parse the JSON array from each agent's response.

Step 5: Validate Issues with Reasoned Analysis

Do NOT use simple consensus voting (e.g., "2+ agents agree"). Instead, perform reasoned validation:

For each unique issue found (group similar issues by file + approximate line range):

  1. Evaluate validity: Is this a real issue or a false positive? Consider:

- Does the code actually have this problem? - Is the reviewer misunderstanding the code's purpose? - Is this issue already handled elsewhere in the codebase?

  1. Evaluate severity: Is the severity rating correct? Consider:

- What's the actual user/system impact? - Is this being over- or under-rated?

  1. Make a decision:

- CONFIRMED: Issue is valid and severity is appropriate - CONFIRMED (adjusted): Issue is valid but severity should be changed - DROPPED: Issue is a false positive, explain why

Track dropped issues with reasoning for the summary comment.

Step 6: Determine Merge Verdict

Based on the confirmed issues, determine the verdict:

  • :white_check_mark: YES - Ready to merge: No HIGH issues, at most minor MEDIUM issues that are judgment calls
  • :thinking: NOT SURE - Potential issues: Has MEDIUM issues that should probably be addressed, but none are clear blockers
  • :no_entry: NO - Do NOT merge: Has HIGH severity issues or multiple serious MEDIUM issues that NEED to be fixed

Step 7: Deduplicate Against Existing Comments

Before posting, filter out issues that match existing PR comments:

  • Same file path
  • Same or nearby line number (within 3 lines)
  • Similar keywords in the issue title appear in the existing comment body

Step 8: Post GitHub Comments

Summary Comment

Post a summary comment on the PR using gh pr comment:

## :mag: Dyadbot Code Review Summary

**Verdict: [VERDICT EMOJI + TEXT]**

Reviewed by 3 independent agents: Correctness Expert, Code Health Expert, UX Wizard.

### Issues Summary

| Severity               | File                  | Issue                  |
| ---------------------- | --------------------- | ---------------------- |
| :red_circle: HIGH      | `src/auth.ts:45`      | SQL injection in login |
| :yellow_circle: MEDIUM | `src/ui/modal.tsx:12` | Missing loading state  |

<details>
<summary>:green_circle: Low Priority Notes (X items)</summary>

- **Minor naming inconsistency** - `src/helpers.ts:23`
- **Could add hover state** - `src/button.tsx:15`

</details>

<details>
<summary>:no_entry_sign: Dropped False Positives (X items)</summary>

- **~~Potential race condition~~** - Dropped: State is only accessed synchronously in this context
- **~~Missing null check~~** - Dropped: Value is guaranteed non-null by the caller's validation

</details>

---

_Generated by Dyadbot multi-agent code review_

Always post a summary, even if no issues are found. In that case:

## :mag: Dyadbot Code Review Summary

**Verdict: :white_check_mark: YES - Ready to merge**

:white_check_mark: No issues found by multi-agent review.

---

_Generated by Dyadbot multi-agent code review_

Inline Comments

For each HIGH and MEDIUM issue, post an inline review comment at the relevant line using gh api:

# Post a review with inline comments
gh api repos/<OWNER/REPO>/pulls/<PR_NUMBER>/reviews \
  -X POST \
  --input payload.json

Where payload.json contains:

{
  "commit_id": "<HEAD_SHA from PR metadata>",
  "body": "Multi-agent review: X issue(s) found",
  "event": "COMMENT",
  "comments": [
    {
      "path": "src/auth.ts",
      "line": 45,
      "body": "**:red_circle: HIGH** | security\n\n**SQL injection in login**\n\nDescription of the issue...\n\n:bulb: **Suggestion:** Use parameterized queries"
    }
  ]
}

Severity Guidelines

Across all reviewers:

  • HIGH: Security vulnerabilities, data loss risks, crashes, broken functionality, race conditions, UX blockers
  • MEDIUM: Logic errors, unhandled edge cases, performance issues, sloppy code that hurts maintainability, poor error messages, missing loading/empty states, accessibility gaps
  • LOW: Minor style issues, naming nitpicks, optional polish improvements

Philosophy: Sloppy code that hurts maintainability is MEDIUM, not LOW. We care about code health.

File Structure

references/
  correctness-reviewer.md  - Role description for the correctness expert
  code-health-reviewer.md  - Role description for the code health expert
  ux-reviewer.md           - Role description for the UX wizard
  issue_schema.md          - JSON schema for issue output

Configuration Notes

  • No Python scripts needed: This skill executes entirely through Claude Code tools
  • No ANTHROPIC_API_KEY needed: Sub-agents spawned via Task tool have automatic access
  • GITHUB_TOKEN required: For PR access and commenting (usually already configured)

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

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

37.58%
按下载量换算93

Claude

29.89%
按下载量换算74

Cursor

16.91%
按下载量换算42

Gemini CLI

9.53%
按下载量换算24

安全审计

暂无安全审计结果可展示。

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/dyad-sh/dyad --skill dyad:multi-pr-review 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

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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