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Agent Skill · 前端设计

prd-to-engineering-spec(PRD 至工程规范)

prd-to-engineering-spec 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。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。

prd-to-engineering-spec 是前端设计类 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,按安装量在前端设计类的 10,216 个 Skill 里排第 4,064。

总安装 1,011周安装 43GitHub Stars 47下载 354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:prd-to-engineering-spec(PRD 至工程规范)
来源仓库:https://github.com/okwinds/miscellany
仓库路径:skills/prd-to-engineering-spec
安装命令:
npx skills add https://github.com/okwinds/miscellany --skill prd-to-engineering-spec
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/okwinds/miscellany --skill prd-to-engineering-spec

这个 Skill 是做什么的

前端设计类 Skill 关注页面结构、视觉规范和组件写法,输出通常是可运行的界面代码。

用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中围绕仓库状态、代码变更或协作事项进行整理。适用于需要查询项目状态、整理变更、辅助创建或检查协作事项的场景。

通过 npx skills add 命令从指定 GitHub 仓库安装使用。涉及写入操作时应确认 token 权限、目标仓库范围和用户授权。prd-to-engineering-spec 属于前端设计类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/prd-to-engineering-spec

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/okwinds/miscellany --skill prd-to-engineering-…;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

prd-to-engineering-spec 怎么安装?

在终端执行 npx skills add https://github.com/okwinds/miscellany --skill prd-to-engineering-spec。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

prd-to-engineering-spec 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。

prd-to-engineering-spec 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。

prd-to-engineering-spec 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。

prd-to-engineering-spec 用的人多吗?

公开数据是累计安装 1,011 次,近一周安装 43 次,下载 354 次,GitHub 47 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。

prd-to-engineering-spec 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。
  • 需要处理前端设计类任务、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。

前端设计类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
frontend-design

前端设计 · Codex、Claude

8,823,360126,072只读MIT通过
vercel-composition-patterns

Vercel 组合模式 · Codex、Claude

3,858,81625,893需要联网MIT通过
vercel-react-native-skills

Vercel React native skills 前端 · Codex、Claude

2,468,66425,878只读MIT通过
adapt

adapt 搜索 · Codex、Claude

2,027,04023,125操作浏览器未明确通过
bolder

bolder 分析 · Codex、Claude

2,004,28823,130只读未明确通过
prd-to-engineering-spec

PRD 至工程规范 · 本页

1,01147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

PRD to Engineering Spec

Overview

Transform product requirements into engineering specifications so complete that developers can implement the entire system step-by-step without ambiguity, and the resulting system can be replicated or migrated without information loss.

Skill Workflow Context

┌─────────────────┐     ┌─────────────────┐     ┌─────────────────┐
│ prd-writing-    │────►│ prd-to-         │     │ reverse-        │
│ guide           │     │ engineering-    │     │ engineering-    │
│ Write PRD       │     │ spec            │     │ spec            │
│                 │     │ [THIS SKILL]   │     │ Code→Spec       │
└─────────────────┘     └─────────────────┘     └─────────────────┘
         │
         ▼  For AI Agent products:
┌─────────────────┐
│ ai-agent-prd    │────► This skill handles Agent PRD conversion too
└─────────────────┘

Input: Complete PRD (from prd-writing-guide or ai-agent-prd) Output: Engineering specifications at replicability-grade detail

Core Principle: Validate PRD first, design second. Incomplete requirements → incomplete specs.

Quick Start

  1. Validate PRD against prd-validation-checklist.md
  2. For Agent systems, also validate with agent-system-spec.md
  3. Generate defect report; do NOT proceed until all ❌ resolved
  4. Run bash scripts/generate_spec_skeleton.sh
  5. Apply the Engineering Lenses to every component
  6. Fill specs using spec-templates.md
  7. Validate with bash scripts/validate_spec.sh

The Engineering Lenses

Apply these seven lenses to every component during Phases 2-3. They are the engineering equivalent of prd-writing-guide's Seven Lenses.

┌──────────────────────────────────────────────────────────────────┐
│                    The Engineering Lenses                         │
├──────────────────────────────────────────────────────────────────┤
│                                                                  │
│  1. ARCHITECTURE  How does it fit? Layers, modules, comms.       │
│  2. DATA          How modeled, validated, stored, migrated?      │
│  3. CONTRACT      Interfaces? Versioning? What breaks?           │
│  4. FAILURE       How does it fail? Detect, recover, cascade?    │
│  5. SECURITY      Auth, authz, encryption, audit, secrets?       │
│  6. OPERATIONS    Deploy, configure, monitor, scale, rollback?   │
│  7. REPLICABILITY All configs, deps, assumptions documented?     │
│                                                                  │
└──────────────────────────────────────────────────────────────────┘

For every major component (service, module, API, data store, integration):

LensKey QuestionSpec Output
ArchitectureWhere does it sit? What depends on it?Module diagram, dependency graph
DataWhat data does it own? Shape? Consistency?Entity definitions, schemas
ContractWhat's the interface? What can't change?API specs, event schemas
FailureWhat can go wrong? What then?Error catalog, retry policies
SecurityWho accesses? How protected?Auth rules, encryption spec
OperationsHow deployed and observed?Config, metrics, alerts
ReplicabilityAny implicit knowledge not captured?Env setup, all dependencies

Workflow

Phase 0: PRD Validation ──────► Defect Report ──────► PRD Complete
         ↓
Phase 1: Decomposition ──► User Stories, Requirements Matrix
         ↓
Phase 2: Technical Design (Interactive) ──► Decision Log
         ↓
Phase 3: Detailed Specs ──► Engineering Lenses on every component
         ↓
Phase 4: Test Specs ──► Unit, Integration, E2E, Acceptance
         ↓
Phase 5: Task Breakdown ──► Tasks, Milestones, Risks
         ↓
Phase 6: Assembly & Replicability Review

Phase 0: PRD Validation

Goal: Ensure PRD completeness before technical work begins.

  1. Review against prd-validation-checklist.md
  2. Agent systems: Also validate against agent-system-spec.md §PRD Validation
  3. Mark: ✅ Present | ⚠️ Unclear | ❌ Missing
  4. Do NOT proceed until all ❌ resolved

Defect Report Template

# PRD Validation Report
**PRD:** [title] | **Status:** [PASS / NEEDS REVISION]

## Critical Gaps (Must Fix)
| # | Category | Issue | Impact | Resolution |
|---|----------|-------|--------|------------|

## Warnings (Should Clarify)
## Assumptions (Document explicitly with risk-if-wrong)

Phase 1: Requirements Decomposition

Goal: Break PRD into structured, implementable requirements.

User Story Format

## US-001: [Title]
**Priority:** P0/P1/P2
As a [role], I want [action], so that [benefit].
**Acceptance Criteria:** (Given/When/Then)
**Business Rules:** BR-001, BR-002
**Dependencies:** US-002

Requirements Matrix

IDRequirementSourceTypePriority
FR-001[description]US-001CRUD/LogicP0
NFR-001API response <200ms P95PRD §7PerformanceP0

Phase 2: Technical Design (Interactive)

Goal: Make architectural decisions with explicit user confirmation.

Decision Process

For each significant decision:

  1. Present 2-3 options with pros, cons, effort, risk, and operational cost
  2. Recommend with rationale
  3. Wait for user confirmation
  4. Record in Decision Log

Decision Log

IDDecisionOptionsChosenRationaleTrade-offsDate
D-001DatabasePG, MongoPostgreSQLACID, JSON supportHigher ops complexity[date]

Tech Stack

ComponentChoiceVersionRationaleAlternatives
Language
Framework
Database
Cache
Queue
Infra

Phase 3: Detailed Specification

Goal: Specs detailed enough for implementation without questions. Apply Engineering Lenses to every component.

Templates: spec-templates.md, feature-spec-template.md

3.1 Data Model

Per entity: purpose, all fields (type, nullable, default, constraints, description), indexes with rationale, relationships with cascade rules, validation rules, lifecycle (create/update/delete behavior).

3.2 API Specification

Per endpoint: method + path, auth/authz, request (params, body, validation rules), response (structure, all status codes with conditions), business logic steps, side effects, rate limits, idempotency.

3.3 Business Logic

Per complex rule: interface (inputs/outputs/errors), algorithm in pseudocode, decision table for branching, concrete edge case examples, transaction boundaries, rollback behavior.

3.4 Security Architecture ⭐

See security-spec-guide.md. Specify:

AreaMust Document
AuthenticationProtocol (OAuth2/JWT/session), token lifecycle, refresh flow, MFA
AuthorizationPermission model (RBAC/ABAC), role-permission matrix, enforcement points
Data SecurityClassification levels, encryption (at-rest, in-transit), PII handling
Input SecurityValidation strategy, injection prevention, file upload rules
AuditEvents to log, format, retention period, tamper protection
SecretsStorage method, rotation policy, access control

3.5 Operations & Deployment ⭐

See operations-spec.md. Specify:

AreaMust Document
EnvironmentsDev, staging, prod differences; how to provision
DeploymentCI/CD pipeline, container spec, rollout strategy
ConfigurationEvery env var / config param with type, default, description, allowed values
MonitoringKey metrics, alert thresholds, dashboard definitions
LoggingFormat, levels, correlation IDs, PII redaction
ScalingTriggers, resource limits, auto-scale rules
RecoveryBackup schedule, RTO/RPO, failover procedure, data restore process

3.6 AI/Agent Components

For AI features: ai-feature-spec.md For Agent systems: agent-system-spec.md, covering:

  • Agent orchestration (reasoning loop, tool dispatch, state management)
  • System prompt as versioned artifact (with testing strategy)
  • Skills/Tools registration and dispatch mechanism
  • Memory system (working, session, long-term storage design)
  • RAG pipeline (embedding → chunking → indexing → retrieval → reranking)
  • Evaluation infrastructure and continuous feedback loops
  • Cost model per interaction

3.7 Migration & Compatibility

If replacing existing system. See spec-templates.md §Migration:

  • Data migration strategy (ETL pipeline, validation steps, rollback)
  • API backward compatibility (versioning scheme, deprecation timeline)
  • Feature parity matrix (old → new mapping, intentional gaps)
  • Cutover plan (strategy, rollback trigger, coexistence period)

Phase 4: Test Specification

Goal: Tests that verify all requirements are met.

Traceability Matrix

RequirementUnitIntegrationE2EAcceptancePerformanceSecurity
FR-001UT-001IT-001E2E-001AT-001--
NFR-001----PERF-001-

Test Types

Unit: Per function—happy path, validation, edge cases, error handling. Integration: Module interactions—API contracts, DB operations, external services. E2E: Complete user journeys—critical paths with variations. Acceptance: Given/When/Then—maps to acceptance criteria. Performance: Load/stress under specified conditions—verify NFRs. Security: Auth bypass, injection, permission escalation—verify security spec.

Templates in spec-templates.md.


Phase 5: Task Breakdown

Task Template

## TASK-001: [Title]
**Implements:** FR-001, US-001 | **Estimate:** 4h
**Description:** [what to do]
**Done Criteria:** [how to verify]
**Dependencies:** TASK-000 | **Blocks:** TASK-002

Milestones

MilestoneTasksTargetDeliverableVerification
M1: Data001-003[date]Schema + migrationsRuns clean
M2: API004-008[date]Endpoints + testsIntegration tests pass
M3: Security009-011[date]Auth + auditSecurity review pass
M4: Deploy012-014[date]CI/CD + monitoringHealth checks green

Risk Register

RiskProbImpactMitigationContingency
[risk]H/M/LH/M/L[prevent][if happens]

Phase 6: Assembly & Replicability Review ⭐

Cross-Reference Check

  • Every user story → functional requirement(s)
  • Every requirement → technical spec section(s)
  • Every spec → test case(s)
  • Every test → traces back to requirement
  • All external dependencies documented with versions

Replicability Verification

The bar: Could a competent team rebuild this system from the spec alone?

  • Environment: All dependencies listed with pinned versions. Build + run commands.
  • Configuration: Every env var, feature flag, config param documented (type, default, range).
  • Data: Schema definitions, seed data specs, migration scripts referenced.
  • Infrastructure: Deploy architecture, container specs, resource requirements.
  • Integrations: Every external dep has connection details, auth, failure handling.
  • Business Logic: No implicit knowledge—every "obvious" rule written down.
  • Security: Auth flow, permissions, encryption, secrets handling fully specified.
  • Monitoring: Metrics, alerts, dashboards defined—operable from day one.
  • No TODOs/TBDs: Every placeholder resolved.

Run: bash scripts/validate_spec.sh <spec_root>


Output Structure

engineering-spec/
├── 00_Overview/
│   ├── SUMMARY.md, REQUIREMENTS_MATRIX.md, DECISION_LOG.md, TECH_STACK.md
├── 01_Requirements/
│   ├── USER_STORIES.md, FUNCTIONAL_REQS.md, NON_FUNCTIONAL_REQS.md
├── 02_Technical_Design/
│   ├── ARCHITECTURE.md, DATA_MODEL.md, API_SPEC.md
│   ├── BUSINESS_LOGIC.md, AI_COMPONENTS.md (if applicable)
├── 03_Security/
│   ├── AUTH_DESIGN.md, DATA_SECURITY.md, AUDIT_SPEC.md
├── 04_Operations/
│   ├── DEPLOYMENT.md, CONFIGURATION.md, MONITORING.md, RUNBOOK.md
├── 05_Testing/
│   ├── TEST_PLAN.md, ACCEPTANCE_TESTS.md
├── 06_Implementation/
│   ├── TASK_BREAKDOWN.md, MILESTONES.md, RISKS.md, MIGRATION.md
└── SPEC_INDEX.md

Resources

  • scripts/generate_spec_skeleton.sh - Create output structure
  • scripts/validate_spec.sh - Validate spec completeness
  • references/prd-validation-checklist.md - PRD validation checklist
  • references/spec-templates.md - Specification templates
  • references/feature-spec-template.md - Feature spec template
  • references/ai-feature-spec.md - AI feature specification
  • references/agent-system-spec.md - Agent system engineering spec ⭐
  • references/security-spec-guide.md - Security architecture spec ⭐
  • references/operations-spec.md - Operations & deployment spec ⭐
  • references/worked-example.md - End-to-end worked example (HelpBot PRD→Spec) ⭐

Critical Reminders

  1. Validate PRD first — Incomplete requirements = incomplete specs
  2. Apply Engineering Lenses — Every component through all 7 lenses
  3. Confirm decisions — Document rationale, not just choices
  4. Trace everything — Requirement → Spec → Test → Requirement
  5. Security is architecture — Not a checkbox; design it explicitly
  6. Operations from day one — Deploy/monitor/debug specs are not optional
  7. Replicability is the bar — If it can't be rebuilt from the spec, it's incomplete

平台分布

Codex

37.94%
按下载量换算134

Claude

31.5%
按下载量换算112

Cursor

18.86%
按下载量换算67

Gemini CLI

9.02%
按下载量换算32

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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