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project-planning项目策划

Agent Skill

project-planning 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

374

周安装

15

GitHub Stars

公开资料未说明

下载量

121
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

MIT

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:project-planning(项目策划)
来源仓库:https://github.com/forever-efficient/pitfal-solutions-website
仓库路径:skills/project-planning
安装命令:
npx skills add forever-efficient/pitfal-solutions-website --skill "project-planning"
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。

AgentSkills.tonpx skills
npx skills add forever-efficient/pitfal-solutions-website --skill "project-planning"

简介

project-planning 提供项目策划相关资源与模板查找服务。

  • 适用于任务分解、里程碑设定与协作流程设计的规划类需求。
  • 可通过关键词匹配候选方案,辅助生成初步计划草案。
  • 使用前需确认项目阶段与团队规模,避免推荐不匹配的方法论。
  • 建议结合实际情况调整输出内容,不可直接套用未经核实的框架。

SKILL.md

Project Planning Workflow

Guide the user through structured project planning with active research to generate comprehensive documentation.

Phase 1: Problem Definition

Ask and document:

  1. What problem are you solving? (pain point)
  2. Who has this problem? (target users)
  3. How is it being solved today? (alternatives)
  4. Why will your solution be better? (differentiation)

Phase 2: User Personas

For each user type:

  1. Name and demographics
  2. Goals - What do they want to achieve?
  3. Pain points - What frustrates them today?
  4. User journey - How will they use the product?

Create 2-3 personas minimum.

Phase 3: Feature Requirements

Guide through requirements gathering:

  1. List all features user envisions
  2. Categorize by priority:

- P0 - MVP, must have for launch - P1 - Important, soon after launch - P2 - Nice to have, future

  1. Assign requirement IDs (REQ-AREA-NNN)

Phase 4: Research MCP Servers (CRITICAL)

Based on identified features and integrations, actively research available MCP servers:

Research steps:

  1. List all external services the project will integrate with
  2. Web search for each: "MCP server for [service name]"
  3. Check official registry: https://github.com/modelcontextprotocol/servers
  4. Check community registry: https://mcp.so/

For each discovered server:

  • Does it cover needed functionality?
  • What are the setup requirements?
  • Is it actively maintained?

Document findings in CLAUDE.md

Phase 5: Research Skills Needed

Identify workflows that should become skills:

Ask:

  • What multi-step processes will be repeated?
  • What commands are complex or error-prone?
  • What workflows need consistency?

Research similar projects:

  • Web search: "[project type] development workflow"
  • What automation do similar teams use?

Document planned skills in CLAUDE.md

Phase 6: Research Technical Architecture

Don't assume - research what fits:

  1. Web search: "[problem domain] architecture patterns 2025"
  2. Web search: "[similar product] tech stack"
  3. Consider constraints: budget, team skills, scale requirements

Evaluate options for:

  • Frontend - Framework, styling, state management
  • Backend - Language, framework, hosting model
  • Database - SQL vs NoSQL, managed vs self-hosted
  • Infrastructure - Cloud provider, serverless vs containers

Create ASCII architecture diagram.

Phase 7: Success Metrics

Define measurable goals:

  1. Business metrics - Revenue, users, engagement
  2. Technical metrics - Performance, uptime, latency
  3. Timeline - Milestones and deadlines

Phase 8: Risks & Mitigations

Identify:

  1. Technical risks (new tech, scaling, integrations)
  2. Business risks (market, competition, timing)
  3. Resource risks (budget, timeline, skills)

For each: probability, impact, mitigation strategy.

Output

Generate these documents with research findings:

  1. docs/PRD.md - Complete product requirements
  2. docs/ARCHITECTURE.md - Technical design with rationale
  3. docs/REQUIREMENTS.md - Detailed feature specs
  4. .mcp.json - Configured with researched servers
  5. .claude/skills/ - Initial skills based on research
  6. CLAUDE.md - Updated with full project context

Tips

  • Don't skip research phases - assumptions cause rework
  • Be specific - "fast" → "< 2s load time"
  • Prioritize ruthlessly - MVPs should be minimal
  • Document research findings - future you will thank you
  • Validate MCP servers exist before planning around them

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

04

需要参考平台分布和安装热度时

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

补充不同宿主或平台的使用分布数据

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

mcpjam

28.49%
按下载量换算34

qwen-code

23.14%
按下载量换算28

windsurf

15.52%
按下载量换算19

zencoder

11.53%
按下载量换算14

crush

7.87%
按下载量换算10

Claude Code

3.54%
按下载量换算4

安全审计

暂无安全审计结果可展示。

权限和风险

external-service

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

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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