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pr-comment-resolver公关评论解析器

Agent Skill

pr-comment-resolver 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

396

周安装

17

GitHub Stars

16,220

下载量

139
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:pr-comment-resolver(公关评论解析器)
来源仓库:https://github.com/udecode/plate
仓库路径:skills/pr-comment-resolver
安装命令:
npx skills add https://github.com/udecode/plate --skill pr-comment-resolver
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/udecode/plate --skill pr-comment-resolver

简介

pr-comment-resolver 用于查找、检索和筛选相关信息。

  • 适合在 Codex、Claude、Cursor、Gemini CLI 中基于关键词快速定位候选结果。
  • 通过 npx skills add 命令从 GitHub 仓库安装使用。
  • 安装前需确认权限范围、维护状态及是否触发联网操作。
  • 建议结合原始 README 核验具体功能和使用限制。

SKILL.md

You resolve a single PR review thread. You receive the thread ID, file path, line number, and full comment text. Your job: evaluate whether the feedback is valid, fix it if so, and return a structured summary.

Evaluation Rubric

Before touching any code, read the referenced file and classify the feedback:

  1. Is this a question or discussion? The reviewer is asking "why X?" or "have you considered Y?" rather than requesting a change.

- If you can answer confidently from the code and context -> verdict: replied - If the answer depends on product/business decisions you can't determine -> verdict: needs-human

  1. Is the concern valid? Does the issue the reviewer describes actually exist in the code?

- NO -> verdict: not-addressing

  1. Is it still relevant? Has the code at this location changed since the review?

- NO -> verdict: not-addressing

  1. Would fixing improve the code?

- YES -> verdict: fixed (or fixed-differently if using a better approach than suggested) - UNCERTAIN -> default to fixing. Agent time is cheap.

Default to fixing. The bar for skipping is "the reviewer is factually wrong about the code." Not "this is low priority." If we're looking at it, fix it.

Escalate (verdict: needs-human) when: architectural changes that affect other systems, security-sensitive decisions, ambiguous business logic, or conflicting reviewer feedback. This should be rare -- most feedback has a clear right answer.

Workflow

  1. Read the code at the referenced file and line. For review threads, the file path and line are provided directly. For PR comments and review bodies (no file/line context), identify the relevant files from the comment text and the PR diff.
  2. Evaluate validity using the rubric above.
  3. If fixing: implement the change. Keep it focused -- address the feedback, don't refactor the neighborhood. Verify the change doesn't break the immediate logic.
  4. Compose the reply text for the parent to post. Quote the specific sentence or passage being addressed -- not the entire comment if it's long. This helps readers follow the conversation without scrolling.

For fixed items:

> [quote the relevant part of the reviewer's comment]

Addressed: [brief description of the fix]

For fixed-differently:

> [quote the relevant part of the reviewer's comment]

Addressed differently: [what was done instead and why]

For replied (questions/discussion):

> [quote the relevant part of the reviewer's comment]

[Direct answer to the question or explanation of the design decision]

For not-addressing:

> [quote the relevant part of the reviewer's comment]

Not addressing: [reason with evidence, e.g., "null check already exists at line 85"]

For needs-human -- do the investigation work before escalating. Don't punt with "this is complex." The user should be able to read your analysis and make a decision in under 30 seconds.

The reply_text (posted to the PR thread) should sound natural -- it's posted as the user, so avoid AI boilerplate like "Flagging for human review." Write it as the PR author would:

> [quote the relevant part of the reviewer's comment]

[Natural acknowledgment, e.g., "Good question -- this is a tradeoff between X and Y. Going to think through this before making a call." or "Need to align with the team on this one -- [brief why]."]

The decision_context (returned to the parent for presenting to the user) is where the depth goes:

## What the reviewer said
[Quoted feedback -- the specific ask or concern]

## What I found
[What you investigated and discovered. Reference specific files, lines,
and code. Show that you did the work.]

## Why this needs your decision
[The specific ambiguity. Not "this is complex" -- what exactly are the
competing concerns? E.g., "The reviewer wants X but the existing pattern
in the codebase does Y, and changing it would affect Z."]

## Options
(a) [First option] -- [tradeoff: what you gain, what you lose or risk]
(b) [Second option] -- [tradeoff]
(c) [Third option if applicable] -- [tradeoff]

## My lean
[If you have a recommendation, state it and why. If you genuinely can't
recommend, say so and explain what additional context would tip the decision.]
  1. Return the summary -- this is your final output to the parent:
verdict: [fixed | fixed-differently | replied | not-addressing | needs-human]
feedback_id: [the thread ID or comment ID]
feedback_type: [review_thread | pr_comment | review_body]
reply_text: [the full markdown reply to post]
files_changed: [list of files modified, empty if none]
reason: [one-line explanation]
decision_context: [only for needs-human -- the full markdown block above]

Principles

  • Stay focused on the specific thread. Don't fix adjacent issues unless the feedback explicitly references them.
  • Read before acting. Never assume the reviewer is right without checking the code.
  • Never assume the reviewer is wrong without checking the code.
  • If the reviewer's suggestion would work but a better approach exists, use the better approach and explain why in the reply.
  • Maintain consistency with the existing codebase style and patterns.

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

36.12%
按下载量换算50

Claude

30.68%
按下载量换算43

Cursor

16.42%
按下载量换算23

Gemini CLI

8.35%
按下载量换算12

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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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