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Agent Skill · 研究检索

refine-review(细化审查)

refine-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。

refine-review 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,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 69,087。

总安装 220周安装 9GitHub Stars 6下载 71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
unknown

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:refine-review(细化审查)
来源仓库:https://github.com/duc01226/easyplatform
仓库路径:skills/refine-review
安装命令:
npx skills add https://github.com/duc01226/easyplatform --skill refine-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/duc01226/easyplatform --skill refine-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。

refine-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。适用于研究检索类任务,如信息搜集、资料筛选和知识整理,尤其适合多源数据聚合与初步分析。

通过关键词、任务描述或来源仓库提供查询条件,返回结构化候选结果列表供进一步处理。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。可结合来源仓库、安装命令和原始 README 继续核验具体用法。

来源仓库内路径:skills/refine-review

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 Codex、Claude、Cursor、Gemini CLI;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 npx skills add https://github.com/duc01226/easyplatform --skill refine-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

refine-review 怎么安装?

在终端执行 npx skills add https://github.com/duc01226/easyplatform --skill refine-review。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

refine-review 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。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。

refine-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。

refine-review 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

refine-review 用的人多吗?

公开数据是累计安装 220 次,近一周安装 9 次,下载 71 次,GitHub 6 星。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。

refine-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

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 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

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 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 Codex,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。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 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
refine-review

细化审查 · 本页

2206需要联网未明确通过

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

[IMPORTANT] Use TaskCreate to break ALL work into small tasks BEFORE starting — including tasks for each file read. This prevents context loss from long files. For simple tasks, AI MUST ATTENTION ask user whether to skip.
Evidence Gate: MANDATORY IMPORTANT MUST ATTENTION — every claim, finding, and recommendation requires file:line proof or traced evidence with confidence percentage (>80% to act, <80% must verify first).
OOP & DRY Enforcement: MANDATORY IMPORTANT MUST ATTENTION — flag duplicated patterns that should be extracted to a base class, generic, or helper. Classes in the same group or suffix (ex *Entity, *Dto, *Service, etc...) MUST ATTENTION inherit a common base (even if empty now — enables future shared logic and child overrides). Verify project has code linting/analyzer configured for the stack.
External Memory: For complex or lengthy work (research, analysis, scan, review), write intermediate findings and final results to a report file in plans/reports/ — prevents context loss and serves as deliverable.
Deep Multi-Round Review — THREE mandatory escalating-depth rounds. NEVER combine. NEVER PASS after Round 1 alone. Round 1: Normal review building understanding. Read all files, note issues. Round 2: MANDATORY re-read ALL files from scratch. Focus on: - Cross-cutting concerns missed in Round 1 - Interaction bugs between changed files - Convention drift (new code vs existing patterns) - Missing pieces (what should exist but doesn't) Round 3: MANDATORY adversarial simulation (for >3 files or cross-cutting changes). Pretend you are using/running this code RIGHT NOW: - "What input causes failure? What error do I get?" - "1000 concurrent users — what breaks?" - "After deployment rollback — backward compatible?" - "Can I debug issues from logs/monitoring output?" Rules: NEVER rely on prior round memory — re-read everything. NEVER declare PASS after Round 1. Final verdict must incorporate ALL rounds. Report must include ## Round 2 Findings and ## Round 3 Findings sections.
Graph Impact Analysis — When .code-graph/graph.db exists, run blast-radius --json to detect ALL files affected by changes (7 edge types: CALLS, MESSAGE_BUS, API_ENDPOINT, TRIGGERS_EVENT, PRODUCES_EVENT, TRIGGERS_COMMAND_EVENT, INHERITS). Compute gap: impacted_files - changed_files = potentially stale files. Risk: <5 Low, 5-20 Medium, >20 High. Use trace --direction downstream for deep chains on high-impact files.

Quick Summary

Goal: Auto-review a refined PBI artifact for completeness, quality, and correctness before story creation proceeds.

Key distinction: AI self-review (automatic), NOT user interview.

Be skeptical. Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence percentages (Idea should be more than 80%).

Frontend/UI Context (if applicable)

When this task involves frontend or UI changes,
UI System Context — For ANY task touching .ts, .html, .scss, or .css files: MUST ATTENTION READ before implementing: 1. docs/project-reference/frontend-patterns-reference.md — component base classes, stores, forms 2. docs/project-reference/scss-styling-guide.md — BEM methodology, SCSS variables, mixins, responsive 3. docs/project-reference/design-system/README.md — design tokens, component inventory, icons Reference docs/project-config.json for project-specific paths.
  • Component patterns: docs/project-reference/frontend-patterns-reference.md (content auto-injected by hook — check for [Injected:...] header before reading)
  • Styling/BEM guide: docs/project-reference/scss-styling-guide.md
  • Design system tokens: docs/project-reference/design-system/README.md

Workflow

  1. Locate PBI — Find latest PBI artifact in team-artifacts/pbis/ or active plan context
  2. Evaluate checklist — Score each check as PASS/FAIL
  3. Classify — PASS (all Required + >=50% Recommended), WARN (all Required), FAIL (any Required fails)
  4. Output verdict — Status, issues, recommendations

Checklist

Required (all must pass)

  • Problem statement — Clear problem defined (not just solution description)
  • Acceptance criteria — Minimum 3 GIVEN/WHEN/THEN scenarios
  • Story points + complexity — Both fields present with valid values
  • Dependencies table — Has dependency table with must-before/can-parallel/blocked-by types
  • Stakeholder validation — User interview was conducted (validation section present)
  • No vague language — No "should work", "might need", "TBD" in acceptance criteria
  • Scope boundary — Clear "out of scope" or "not included" section
  • Authorization defined — PBI has "Authorization & Access Control" section with roles × CRUD table
  • UI Layout section — If PBI involves UI changes: has ## UI Layout section per UI wireframe protocol (wireframe + components with tiers + states + design tokens). If backend-only: explicit "N/A"

Recommended (>=50% should pass)

  • RICE/MoSCoW score — Prioritization applied
  • Domain vocabulary — Uses project-specific terms from domain-entities-reference.md
  • Risk assessment — Risks identified with mitigations
  • Non-functional requirements — Performance, security, accessibility considered
  • Production readiness concerns — PBI includes "Production Readiness Concerns" table with Yes/No/Existing for: code linting, error handling, loading indicators, Docker integration, CI/CD quality gates
  • Seed data assessed — PBI addresses seed data needs (reference data, config data, test data) or explicitly states "N/A"
  • Data migration assessed — PBI addresses schema changes and data migration needs or explicitly states "N/A"

Output

## PBI Review Result

**Status:** PASS | WARN | FAIL
**Artifact:** {pbi-path}

### Required ({X}/{Y})

- ✅/❌ Check description

### Recommended ({X}/{Y})

- ✅/⚠️ Check description

### Issues Found

- ❌ FAIL: {issue}
- ⚠️ WARN: {issue}

### Verdict

{PROCEED | REVISE_FIRST}

Round 2: Focused Re-Review (MANDATORY)

Protocol: Deep Multi-Round Review (inlined via SYNC:double-round-trip-review above)

After completing Round 1 checklist evaluation, execute a second full review round:

  1. Re-read the Round 1 verdict and checklist results
  2. Re-evaluate ALL checklist items — do NOT rely on Round 1 memory
  3. Challenge Round 1 PASS items: "Is this really PASS? Did I verify with evidence?"
  4. Focus on what Round 1 typically misses:

- Implicit assumptions that weren't validated - Missing acceptance criteria coverage - Edge cases not addressed in the artifact - Cross-references that weren't verified

  1. Update verdict if Round 2 found new issues
  2. Final verdict must incorporate findings from BOTH rounds

Key Rules

  • FAIL blocks workflow — If FAIL, do NOT proceed to /story. List specific fixes needed.
  • WARN allows proceeding — Note gaps but continue.
  • No guessing — Every check must reference specific content in the PBI artifact.
  • Constructive — Focus on implementation-blocking issues, not pedantic details.

Next Steps

MANDATORY IMPORTANT MUST ATTENTION — NO EXCEPTIONS after completing this skill, you MUST ATTENTION use AskUserQuestion to present these options. Do NOT skip because the task seems "simple" or "obvious" — the user decides:

  • "/story (Recommended)" — Create user stories from validated PBI
  • "/refine" — Re-refine if FAIL verdict
  • "Skip, continue manually" — user decides

Closing Reminders

MANDATORY IMPORTANT MUST ATTENTION break work into small todo tasks using TaskCreate BEFORE starting. MANDATORY IMPORTANT MUST ATTENTION validate decisions with user via AskUserQuestion — never auto-decide. MANDATORY IMPORTANT MUST ATTENTION add a final review todo task to verify work quality. MANDATORY IMPORTANT MUST ATTENTION READ the following files before starting:

  • IMPORTANT MUST ATTENTION execute TWO review rounds. Round 2 re-reads from scratch — never skip or combine with Round 1.
  • IMPORTANT MUST ATTENTION run blast-radius when graph.db exists. Flag impacted files NOT in changeset as potentially stale.
  • IMPORTANT MUST ATTENTION read frontend-patterns-reference, scss-styling-guide, design-system/README before any UI change.

平台分布

Codex

34.61%
按下载量换算25

Claude

28.91%
按下载量换算21

Cursor

17.68%
按下载量换算13

Gemini CLI

10.62%
按下载量换算8

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

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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