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refine-review细化审查

Agent Skill

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。

总安装

220

周安装

9

GitHub Stars

6

下载量

71
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: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

简介

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。

SKILL.md

[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.

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

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。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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