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Agent Skill · 研究检索

afrexai-prd-engine(Afrexai PRD 发动机)

afrexai-prd-engine 用于查找、检索和筛选相关信息,适合在 OpenClaw 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。

afrexai-prd-engine 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为需要联网;许可证为 MIT-0,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 6,015。

总安装 23,525周安装 961GitHub Stars 公开资料未说明下载 7,611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
MIT-0
版本
1.0.0

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:afrexai-prd-engine(Afrexai PRD 发动机)
来源仓库:https://github.com/1kalin/afrexai-prd-engine
安装命令:
openclaw skills install afrexai-prd-engine
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install afrexai-prd-engine

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。

建立产品需求文档(PRD)从创意到交付的全生命周期管理体系。适用于敏捷开发中需求澄清、跨部门对齐与验收标准设定。内置模板校验、版本追踪与干系人审批流程设计。安装命令:openclaw skills install afrexai-prd-engine;务必基于实际用户场景编写用例。

适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。

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 OpenClaw;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 openclaw skills install afrexai-prd-engine;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

afrexai-prd-engine 怎么安装?

在终端执行 openclaw skills install afrexai-prd-engine。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

afrexai-prd-engine 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。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。

afrexai-prd-engine 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。

afrexai-prd-engine 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

afrexai-prd-engine 用的人多吗?

公开数据是累计安装 23,525 次,近一周安装 961 次,下载 7,611 次。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。

afrexai-prd-engine 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。

先想清楚的地方

  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 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 OpenClaw,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
afrexai-prd-engine

Afrexai PRD 发动机 · 本页

23,525—需要联网MIT-0有提醒

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

PRD Engine — Product Requirements That Ship

Complete product requirements methodology: from idea to spec to shipped feature. Not just a JSON template — a full system for writing PRDs that developers actually follow and stakeholders actually approve.

When to Use This Skill

  • Turning a vague idea into a buildable specification
  • Writing PRDs for new features, products, or major refactors
  • Reviewing/improving existing PRDs before sprint planning
  • Breaking epics into right-sized user stories
  • Creating technical design documents alongside product specs
  • Preparing specs for AI coding agents (Claude Code, Cursor, Copilot)

Phase 1: Discovery Brief

Before writing a single requirement, answer these questions. Skip this and you'll rewrite the PRD 3 times.

Problem Validation Checklist

discovery_brief:
  problem:
    statement: "" # One sentence. If you need two, you don't understand it yet.
    who_has_it: "" # Specific persona, not "users"
    frequency: "" # Daily? Weekly? Once? (daily problems > occasional ones)
    current_workaround: "" # What do they do today? (no workaround = maybe not a real problem)
    evidence:
      - type: "" # support_ticket | user_interview | analytics | churned_user | sales_objection
        detail: ""
        date: ""

  impact:
    users_affected: "" # Number or percentage
    revenue_impact: "" # $ at risk or $ opportunity
    strategic_alignment: "" # Which company goal does this serve?

  constraints:
    deadline: "" # Hard date or flexible?
    budget: "" # Engineering weeks available
    dependencies: "" # What must exist first?
    regulatory: "" # Any compliance requirements?

  success_metrics:
    primary: "" # ONE metric that defines success
    secondary: [] # 2-3 supporting metrics
    measurement_method: "" # How will you actually measure this?
    target: "" # Specific number, not "improve"
    timeframe: "" # When do you expect to see results?

Problem Statement Formula

[Persona] needs [capability] because [reason], but currently [blocker], which causes [measurable impact].

Examples:

  • ❌ "Users need better onboarding" (vague, unmeasurable)
  • ✅ "New free-trial users (500/month) need to reach their first 'aha moment' within 10 minutes because 73% who don't will churn within 48 hours, but currently the average time-to-value is 34 minutes due to a 12-step setup wizard, which costs us ~$18K/month in lost conversions."

Kill Criteria

Before proceeding, check these. If any are true, STOP and push back:

SignalAction
No evidence of the problem (just someone's opinion)Demand evidence. Opinions aren't requirements.
Solution already decided ("just build X")Rewind to the problem. Solutions without problems = features nobody uses.
Success metric is unmeasurableDefine how you'll measure it or don't build it.
Affects <1% of users with no revenue impactDeprioritize. Small problems with small impact = small returns.
Scope keeps expanding during discoveryScope lock. If everything is in scope, nothing is.

Phase 2: PRD Document

PRD Template

# PRD: [Feature Name]

**Author:** [Name]
**Status:** Draft | In Review | Approved | In Progress | Shipped
**Created:** YYYY-MM-DD
**Last Updated:** YYYY-MM-DD
**Approvers:** [Names + roles]

## 1. Problem & Opportunity

[Problem statement from discovery brief — one paragraph max]

### Evidence
- [Evidence point 1 — with data]
- [Evidence point 2 — with data]

### Impact
- Users affected: [number]
- Revenue impact: [$ amount or % change]
- Strategic goal: [which one]

## 2. Solution Overview

[2-3 paragraphs max. What are we building and why this approach?]

### What This Is
- [Bullet list of what's in scope]

### What This Is NOT
- [Explicit exclusions — this prevents scope creep]

### Key Decisions Made
| Decision | Options Considered | Chosen | Rationale |
|----------|-------------------|--------|-----------|
| [Decision 1] | A, B, C | B | [Why] |

## 3. User Stories

[See Phase 3 below for story writing methodology]

## 4. Design & UX

### User Flow
1. User [action] →
2. System [response] →
3. User sees [outcome]

### Wireframes/Mockups
[Link to Figma/screenshots or describe key screens]

### Edge Cases
| Scenario | Expected Behavior |
|----------|------------------|
| [Edge case 1] | [What happens] |
| [Edge case 2] | [What happens] |
| Empty state | [What user sees with no data] |
| Error state | [What user sees on failure] |
| Slow connection | [Loading behavior] |

## 5. Technical Considerations

### Architecture Notes
- [Key technical decisions]
- [New services/APIs needed]
- [Database changes]

### Dependencies
- [External service X]
- [Team Y's API]
- [Library Z]

### Performance Requirements
- Page load: <[X]ms
- API response: <[X]ms
- Concurrent users: [X]

### Security & Privacy
- [Data handling requirements]
- [Auth/permissions needed]
- [PII considerations]

## 6. Release Plan

### Rollout Strategy
- [ ] Feature flag: [flag name]
- [ ] Beta group: [who]
- [ ] % rollout: [10% → 50% → 100%]
- [ ] Rollback plan: [how]

### Launch Checklist
- [ ] QA sign-off
- [ ] Analytics events implemented
- [ ] Monitoring/alerts configured
- [ ] Documentation updated
- [ ] Support team briefed
- [ ] Stakeholders notified

## 7. Success Criteria

| Metric | Current | Target | Timeframe |
|--------|---------|--------|-----------|
| [Primary metric] | [X] | [Y] | [Z weeks] |
| [Secondary metric] | [X] | [Y] | [Z weeks] |

### Post-Launch Review
- **1-week check:** [What to look at]
- **1-month review:** [What to measure]
- **Kill/iterate decision:** [Criteria for each]

PRD Quality Rubric (score before sharing)

Dimension0-2 (Weak)3-4 (Adequate)5 (Strong)Weight
Problem clarityVague, no dataClear but thin evidenceSharp statement + multiple evidence pointsx4
Scope disciplineEverything in scopeSome boundariesExplicit in/out + "what this is NOT"x3
Story qualityVague tasksStories with some criteriaINVEST stories + verifiable acceptance criteriax4
Edge casesNone listedHappy path + 1-2 edgesComprehensive: empty, error, slow, permissions, concurrentx3
Success metrics"Improve X"Metric + targetMetric + baseline + target + timeframe + measurement methodx3
Technical feasibilityNo tech sectionArchitecture notesDependencies, performance, security, migration planx2
Release planNone"Ship it"Feature flag + rollout % + rollback + launch checklistx1

Scoring: Sum (score × weight). Max = 100.

  • 80-100: Ship-ready. Get approvals.
  • 60-79: Solid but missing pieces. Fill gaps before review.
  • 40-59: Needs work. Major sections incomplete.
  • <40: Start over or go back to discovery.

Phase 3: User Story Methodology

Story Format

story:
  id: "US-001"
  title: "" # Action-oriented: "Add priority field to tasks table"
  persona: "" # Who benefits
  narrative: "As a [persona], I want [capability] so that [benefit]"
  acceptance_criteria:
    - criterion: "" # Verifiable statement
      type: "functional" # functional | performance | security | ux
  priority: 1 # Execution order (dependencies first)
  size: "" # XS | S | M | L | XL
  status: "todo" # todo | in_progress | review | done
  notes: "" # Runtime observations
  depends_on: [] # Story IDs this depends on
  blocked_by: [] # External blockers

INVEST Checklist (every story must pass)

LetterCriterionTest
I — IndependentCan be built without other incomplete storiesNo circular dependencies
N — NegotiableDetails can flex (the "what" is fixed, the "how" is flexible)Multiple implementation approaches exist
V — ValuableDelivers user or business value on its ownWould a user/stakeholder care if only this shipped?
E — EstimableTeam can size itNo major unknowns (if unknowns exist, add a spike first)
S — SmallCompletable in one sprint (or one context window for AI agents)1-3 days of work max
T — TestableHas verifiable acceptance criteriaCan write a test for each criterion

Acceptance Criteria Rules

Good criteria are:

  • Binary (pass/fail, not subjective)
  • Specific (numbers, not adjectives)
  • Independent (testable in isolation)
❌ Bad✅ Good
"Works correctly""Returns 200 with JSON body containing id, name, status fields"
"Fast enough""API responds in <200ms at p95 with 100 concurrent users"
"User-friendly""Form shows inline validation errors within 100ms of field blur"
"Secure""Endpoint returns 403 for users without admin role"
"Handles errors""On network timeout, shows retry button + cached data if available"

Always include these universal criteria:

  • Typecheck passes (tsc --noEmit --strict) (for TypeScript projects)
  • All existing tests still pass
  • New functionality has test coverage

Story Sizing Guide

SizeScopeTimeExample
XSConfig change, copy update, env var<2 hours"Update error message text"
SSingle component/function, no new deps2-4 hours"Add date picker to form"
MFeature slice: DB + API + UI1-2 days"Add task priority with filter"
LMulti-component feature, new patterns2-3 days"Add real-time notifications"
XLToo big. Split it.——

Story Ordering: The Dependency Pyramid

Always order stories bottom-up:

Level 1: Schema & Data (migrations, models, seed data)
    ↑
Level 2: Backend Logic (services, APIs, business rules)
    ↑
Level 3: Integration (API routes, auth, middleware)
    ↑
Level 4: UI Components (forms, tables, modals)
    ↑
Level 5: UX Polish (animations, empty states, loading)
    ↑
Level 6: Analytics & Monitoring (events, dashboards)

Each level depends ONLY on levels below it. Never build UI before the API exists.

Splitting Strategies

When a story is too big, split using one of these patterns:

StrategyWhen to UseExample
By layerFull-stack feature"Add schema" → "Add API" → "Add UI"
By operationCRUD feature"Create task" → "Read/list tasks" → "Update task" → "Delete task"
By personaMulti-role feature"Admin creates template" → "User fills template" → "Viewer sees results"
By happy/sad pathComplex flows"Successful payment" → "Payment declined" → "Payment timeout"
By platformCross-platform"iOS support" → "Android support" → "Web support"
Spike + implementHigh uncertainty"Spike: evaluate auth libraries (2h)" → "Implement auth with chosen library"

Phase 4: PRD for AI Coding Agents

When the PRD will be executed by AI agents (Claude Code, Cursor, Copilot Workspace, etc.), add these adaptations:

Agent-Optimized Story Format

agent_story:
  id: "US-001"
  title: "Add priority field to tasks table"
  context: |
    The tasks table is in src/db/schema.ts using Drizzle ORM.
    Priority values should be: high, medium, low (default: medium).
    See existing fields for naming conventions.
  acceptance_criteria:
    - "Add `priority` column to `tasks` table in src/db/schema.ts"
    - "Type: enum('high', 'medium', 'low'), default 'medium', not null"
    - "Generate migration: `npx drizzle-kit generate`"
    - "Run migration: `npx drizzle-kit push`"
    - "Verify: `tsc --noEmit --strict` passes"
    - "Verify: existing tests pass (`npm test`)"
  files_to_touch:
    - src/db/schema.ts
    - drizzle/ (generated migration)
  commands_to_run:
    - "npx drizzle-kit generate"
    - "npx drizzle-kit push"
    - "tsc --noEmit --strict"
    - "npm test"
  done_when: "All verify commands pass with exit code 0"

Agent-Specific Rules

  1. Be explicit about file paths. Agents can't guess your project structure.
  2. Include verification commands. Agents need a "definition of done" they can check.
  3. One context window per story. If a story needs the agent to remember more than ~50 files, it's too big.
  4. List files to touch. Reduces agent exploration time and prevents hallucination.
  5. Order matters even more. Agents execute sequentially — wrong order = compounding errors.
  6. Include the commands. Don't say "run the migration" — say npx drizzle-kit push.

Project Context File

For AI agent execution, create a PROJECT_CONTEXT.md alongside the PRD:

# Project Context

## Stack
- Framework: [Next.js 14 / Express / etc.]
- Language: [TypeScript strict mode]
- Database: [PostgreSQL via Drizzle ORM]
- Testing: [Vitest + Testing Library]
- Styling: [Tailwind CSS]

## Key Directories
- src/db/ — Database schema and migrations
- src/api/ — API routes
- src/components/ — React components
- src/lib/ — Shared utilities
- tests/ — Test files (mirror src/ structure)

## Conventions
- File naming: kebab-case
- Component naming: PascalCase
- Max file length: 300 lines
- Max function length: 50 lines
- All exports typed, no `any`

## Commands
- `npm run dev` — Start dev server
- `npm test` — Run tests
- `npm run build` — Production build
- `tsc --noEmit --strict` — Type check
- `npx drizzle-kit generate` — Generate migration
- `npx drizzle-kit push` — Apply migration

## Current State
- [What exists today relevant to the PRD]
- [Any tech debt or gotchas the agent should know]

Phase 5: Review & Approval

Review Checklist (before sharing the PRD)

Completeness:

  • [ ] Problem statement has evidence (not just opinion)
  • [ ] "What this is NOT" section exists and is specific
  • [ ] Every story has ≥3 acceptance criteria
  • [ ] Edge cases table covers: empty state, error state, permissions, concurrent access
  • [ ] Success metrics have baseline + target + timeframe
  • [ ] Technical section addresses: performance, security, dependencies

Quality:

  • [ ] No story larger than "L" (split XL stories)
  • [ ] All acceptance criteria are binary (pass/fail)
  • [ ] No circular dependencies between stories
  • [ ] Dependency pyramid ordering is correct
  • [ ] Release plan includes rollback strategy

Readability:

  • [ ] Executive summary is <3 sentences
  • [ ] Non-engineers can understand the problem section
  • [ ] Engineers can start building from the stories section alone
  • [ ] No jargon without definition

Approval Flow

Author writes PRD
    ↓
Self-review (score with rubric — must be ≥60)
    ↓
Peer review (another PM or tech lead)
    ↓
Engineering review (feasibility + sizing)
    ↓
Stakeholder approval (PM lead or product director)
    ↓
Status → Approved
    ↓
Sprint planning (stories → backlog)

Common Review Feedback (and how to fix it)

FeedbackFix
"What problem does this solve?"Your problem statement is weak. Add evidence.
"This is too big"Split into phases. Ship the smallest valuable slice first (MVP).
"How do we know it worked?"Your success metrics are vague. Add numbers + timeframe.
"What about [edge case]?"Your edge case table is incomplete. Add it.
"When does this ship?"Add timeline with milestones, not just a deadline.
"Who approved this?"Add approvers field and get explicit sign-offs.

Phase 6: Tracking & Iteration

PRD Status Lifecycle

Draft → In Review → Approved → In Progress → Shipped → Post-Launch Review
                ↓                                              ↓
            Rejected                                    Iterate / Kill

Progress Tracking

Track story completion in the PRD itself or a linked tracker:

progress:
  total_stories: 12
  done: 7
  in_progress: 2
  blocked: 1
  todo: 2
  completion: "58%"
  
  blocked_items:
    - story: "US-008"
      blocker: "Waiting for payments API access from finance team"
      since: "2025-01-15"
      escalation: "Pinged finance lead, follow up Friday"

  velocity:
    stories_per_week: 3.5
    estimated_completion: "2025-02-01"

Post-Launch Review Template

post_launch:
  shipped_date: ""
  review_date: "" # 2-4 weeks after ship

  metrics:
    primary:
      metric: ""
      baseline: ""
      target: ""
      actual: ""
      verdict: "" # hit | miss | exceeded

    secondary:
      - metric: ""
        actual: ""
        verdict: ""

  qualitative:
    user_feedback: []
    support_tickets: "" # count related to this feature
    unexpected_outcomes: []

  process_retro:
    what_went_well: []
    what_didnt: []
    estimation_accuracy: "" # actual vs estimated effort
    scope_changes: "" # what changed after approval

  decision: "" # iterate | maintain | deprecate | expand
  next_actions: []

Quick Commands

CommandWhat It Does
"Write a PRD for [feature]"Full PRD from discovery through stories
"Break this into stories"Takes a feature description → user stories
"Review this PRD"Scores against quality rubric + gives specific feedback
"Make this agent-ready"Converts PRD stories to agent-optimized format
"What's missing from this PRD?"Gap analysis against the template
"Split this story"Takes a large story → smaller INVEST-compliant stories
"Score this PRD"Quality rubric scoring with dimension breakdown
"Create project context for [project]"Generates PROJECT_CONTEXT.md for AI agent execution
"Post-launch review for [feature]"Generates review template with metrics
"Track progress"Updates completion stats from story statuses

平台分布

OpenClaw

70.47%
按下载量换算5,363

安全审计

VirusTotal

可疑

ClawScan

通过

Static analysis

未展示

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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