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create-project创建项目

Agent Skill

create-project 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

267

周安装

11

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2

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87
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

3

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:create-project(创建项目)
来源仓库:https://github.com/abdullahbeam/nexus-design-abdullah
仓库路径:skills/create-project
安装命令:
npx skills add https://github.com/abdullahbeam/nexus-design-abdullah --skill create-project
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/abdullahbeam/nexus-design-abdullah --skill create-project

简介

初始化 Nexus 项目结构并提供生命周期管理指导。

  • 适用于首次使用项目功能或需要结构化工作流的用户。
  • 包含教程建议、目录创建和注册流程自动化。create-project 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 安装前需完成 onboarding 配置,确认 learn_projects 状态。
  • 首次项目建议先学习使用指南,避免常见误用问题。

SKILL.md

🎯 Onboarding Awareness (CHECK BEFORE STARTING)

Before creating a project, AI MUST check user-config.yaml for incomplete onboarding:

Pre-Flight Check (MANDATORY)

# Check learning_tracker.completed in user-config.yaml
learn_projects: false  → SUGGEST 'learn projects' skill FIRST

If learn_projects: false AND this is user's FIRST project:

💡 Before creating your first project, would you like a quick 8-minute tutorial
on how Nexus projects work? It covers:
- When to use projects vs skills (avoid common mistakes)
- Project structure and lifecycle
- How to track progress effectively

Say 'learn projects' to start the tutorial, or 'skip' to create directly.

If user says 'skip': Proceed with project creation but add this note at the end:

💡 Tip: Run 'learn projects' later if you want to understand the project system deeply.

If learn_projects: true: Proceed normally without suggestion.

Recommended Onboarding Sequence

When checking learning_tracker.completed, if user hasn't done core onboarding:

  1. setup_goals: false → Consider suggesting (but don't block project creation)
  2. learn_projects: false → Suggest before FIRST project (high priority)

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⚠️ CRITICAL EXECUTION REQUIREMENTS ⚠️

WORKFLOW: Structure FIRST, Collaborative Planning SECOND

MANDATORY STEPS (DO NOT SKIP):

  1. ✅ Create TodoWrite with ALL steps
  2. ✅ Offer project type selection (Build, Research, Strategy, Content, Process, Generic)
  3. ✅ Ask project name
  4. ✅ RUN init_project.py IMMEDIATELY (creates 4 directories + 3 planning files)
  5. ✅ Display created structure
  6. ✅ Load overview.md → Fill collaboratively → PAUSE → User confirms
  7. ✅ Load plan.md → Apply mental models → Research dependencies → PAUSE → User confirms
  8. ✅ Load steps.md → Break down execution → PAUSE → User confirms
  9. ✅ Close session

ANTI-PATTERN (DO NOT DO THIS): ❌ Skip project type selection ❌ Skip running init_project.py ❌ Try to create files manually ❌ Generate content before structure exists ❌ Skip mental model questions (Socratic, devil's advocate) ❌ Skip dependency research ❌ Skip pauses between documents ❌ Complete skill in single response

CORRECT PATTERN (DO THIS): ✅ TodoWrite → Offer types → Ask name → RUN SCRIPT → Files created ✅ Then: Load overview.md → Fill collaboratively → PAUSE → Confirm ✅ Then: Load plan.md → Ask Socratic questions → Research dependencies → Add adaptive sections → PAUSE → Confirm ✅ Then: Load steps.md → Break down phases → PAUSE → Confirm ✅ Then: Close session

MENTAL MODELS (MANDATORY): ✅ Socratic Questioning during Approach section ✅ Devil's Advocate during risk assessment ✅ Dependency Research before completing plan.md

SCRIPT RUNS FIRST - ALWAYS! ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

Create Project

Collaborative project design with intelligent, adaptive planning and deep thinking frameworks.

Purpose

The create-project skill creates project structure and guides you through collaborative planning. The workflow: Create structure FIRST (via script), THEN fill in the templates with AI-guided depth.

Key Features:

  • Script-Generated Structure: 4 directories (01-planning/, 02-resources/, 03-working/, 04-outputs/) + 3 planning files (overview, plan, steps) created immediately
  • Adaptive Planning: Templates expand based on project type (Build, Research, Strategy, etc.)
  • Deep Thinking: AI applies Socratic questioning and Devil's Advocate models
  • Dependency Research: AI proactively finds and links related files/systems
  • Mandatory Pauses: Review each document before proceeding
  • Separate Session Principle: Project created now, executed later

Two Modes

This skill operates in two modes based on system state:

1. Workspace Setup Mode

When: 02-projects/ directory doesn't exist Purpose: Create initial workspace folder structure (10-15 min) Workflow: See workflows.md#workspace-setup

2. Project Creation Mode

When: 02-projects/ exists Purpose: Full collaborative project planning (20-30 min) Workflow: See workflows.md#project-creation


Mode Detection Logic

CRITICAL: Before starting any workflow, detect which mode to use.

  1. Check for 02-projects/: ls -d 02-projects/ 2>/dev/null

- IF exists → PROJECT_CREATION mode - IF not exists → WORKSPACE_SETUP mode (System not initialized)

Decision Tree:

02-projects/ exists?
├── YES → PROJECT_CREATION mode
└── NO → WORKSPACE_SETUP mode

Quick Start

The One True Workflow: Intelligent Planning

There is only ONE way to create projects - always run the script first, then collaboratively plan with depth:

Step 1: Initiation (< 1 minute)

  • Offer project types (Build, Research, Strategy, etc.)
  • Run scripts/init_project.py "Project Name" --path 02-projects
  • Auto-generates 4 directories: 01-planning/, 02-resources/, 03-working/, 04-outputs/
  • Auto-generates 3 planning files in 01-planning/: overview.md, plan.md, steps.md

Step 2: Collaborative Planning (15-30 minutes) 🤔

  • overview.md: Define purpose and success criteria
  • plan.md:

- AI suggests adaptive sections based on type - AI asks Socratic questions to test assumptions - AI researches dependencies and populates links - AI plays Devil's Advocate to identify risks

  • steps.md: Break down execution into phases

Step 3: Save & Execute Later 💾

  • Close session to save progress
  • Execute project in a separate session with clean context

Workflow Steps

  1. Detect mode using logic above
  2. Offer project types from project-types.md
  3. Run init_project.py to create structure immediately
  4. Display created structure
  5. Load workflow from workflows.md
  6. Follow workflow step-by-step with mandatory pauses
  7. Close session to save state

⚠️ MANDATORY: Mental Models Selection

CRITICAL: Do NOT skip this step, even if you know which models to use from memory!

During the plan.md phase, AI MUST run select_mental_models.py script FIRST, then offer 2-3 relevant options to user.

Required Workflow (DO NOT SKIP):

  1. Run script FIRST (before applying ANY models): python 00-system/mental-models/scripts/select_mental_models.py --format brief
  2. Review script output: JSON array with all available mental models (59 models across 12 categories)
  3. Offer 2-3 relevant models to user based on project type/context with brief (3-7 words) descriptions
  4. Wait for user selection: User chooses which models to apply (or none)
  5. Load the specific model file only after user selects: # Individual model files are in: 00-system/mental-models/models/{category}/{model-slug}.md # Example: 00-system/mental-models/models/cognitive/first-principles.md
  6. Apply questions from selected models to fill plan.md collaboratively

DO NOT:

  • ❌ Skip running select_mental_models.py script
  • ❌ Apply models from memory without offering choice
  • ❌ Auto-select models without user confirmation
  • ❌ Skip user selection step

Example Offer:

Now let's dive into planning. I've reviewed the mental models catalog and recommend for your Build/Create project:

1. **First Principles** – Strip assumptions, find fundamental truths
   Best for: Novel projects, challenging assumptions

2. **Pre-Mortem** – Imagine failure modes before implementation
   Best for: High-stakes projects, risk mitigation

3. **Stakeholder Mapping** – Identify all affected parties and interests
   Best for: Multi-party projects, organizational work

Which approach(es) sound most useful? Or we can combine them!

Loading Pattern:

User picks: "First Principles + Pre-Mortem"

AI loads individual model files:
→ Read: 00-system/mental-models/models/cognitive/first-principles.md
→ Read: 00-system/mental-models/models/diagnostic/pre-mortem.md
→ Apply questions from both models to fill plan.md

Benefits:

  • Proactive - AI always loads mental-models, shows what's available
  • User choice - User picks which models (or none) to apply
  • Efficient metadata - Brief (3-7 words) but descriptive
  • Individual files - Each model has its own file with full details
  • Script-parseable - YAML frontmatter for programmatic access
  • Maintainable - Update one model file, all skills benefit

See: mental-models framework for full catalog and offering guidance


Dependency Research

Before finalising plan.md, the AI will automatically:

  • Scan the codebase for files that reference the same domain (using codebase_search).
  • Look for existing skills that could be reused (e.g. lead-qualification).
  • Identify external system configurations (MCP servers, Airtable schemas, Slack channels).
  • Populate the Dependencies & Links section with concrete file paths and system names.

Example auto‑generated section:

## Dependencies & Links
**Files Impacted**:
- `03-skills/lead-qualification/SKILL.md` – main workflow definition
- `04-workspace/airtable-schemas/leads.json` – lead data schema

**External Systems**:
- Airtable Base: "Leads" – source of lead data
- Slack Workspace: #sales – notification destination

**Related Projects**:
- Project 03: CRM Integration – shares Airtable connection

Example Interaction Flow

AI: "What would you like to name your project?"
User: "Lead qualification workflow"

AI: "Great. This looks like a **Build/Create** project. I’ll add sections for Technical Architecture, Implementation Strategy, and Integration Points. Does that sound good?"
User: "Yes, go ahead."

AI: (runs init_project.py) → creates files.

AI: "Your project structure is ready. Let’s start with **overview.md**. What problem are you solving?"
User: "We lose leads because manual qualification takes too long."

AI: (fills purpose) → asks Socratic questions:
"What assumptions are you making about the current qualification time?"
User: "We estimate 30 minutes per lead based on recent logs."

AI: (adds to success criteria) → moves to **plan.md**.
AI: "I’ll now ask a few Socratic questions about your approach and then run a quick dependency scan."
... (continues) ...

Resources

scripts/

  • init_project.py: ⚡ Quick project template generator

- Auto-generates project structure with 4 directories (01-planning/, 02-resources/, 03-working/, 04-outputs/) - Auto-assigns next available project ID - Creates 3 planning files in 01-planning/: overview.md, plan.md, steps.md from templates - Usage: python scripts/init_project.py "Project Name" --path 02-projects

references/

  • project-types.md: Guide for offering project types and adaptive planning
  • workflows.md: Complete interactive planning workflows for both modes
  • mental-models.md: Full mental models catalog
  • project-schema.yaml: YAML frontmatter schema documentation

Error Handling

Invalid Project ID/Name

  • Explain validation rule clearly
  • Show example of correct format
  • Suggest correction

Project Already Exists

  • Inform user project exists
  • Offer options: different name, different ID, or load existing

Memory Files Missing

  • Warn user: "Memory files not initialized"
  • Suggest: "Please run 00-setup-memory project first"
  • DO NOT create project

User Abandons Mid-Creation

  • Save partial work to temp file
  • Inform: "Progress saved. Say 'continue project creation' to resume."

User Skips Review

  • Remind: "It's important we get this right!"
  • Gently insist on review before proceeding

Why This Design?

Why Interactive?

  • Quality over speed: Thoughtful planning prevents rework
  • User ownership: Collaborative design ensures buy-in
  • Learning: Mental models teach strategic thinking
  • Accuracy: Pauses catch issues early

Why Mandatory Pauses?

  • Validation: User confirms understanding before proceeding
  • Iteration: Catch issues before they cascade
  • Ownership: User feels involved, not just spectator
  • Quality: Better planning = smoother execution

Why Separate Session?

  • Context management: Clean boundaries between planning and execution
  • Focus: Execution session loads only execution context
  • Memory: close-session properly saves state between phases
  • UX: Matches natural work rhythm (plan now, execute later)

Integration:

  • close-session automatically updates project-map.md every session
  • validate-system checks project structure integrity
  • Skills can reference project outputs in their workflows

Remember: This is a COLLABORATIVE DESIGN SESSION, not a quick generation tool. The time invested in thorough planning pays dividends during execution!

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

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能力 4

补充不同宿主或平台的使用分布数据

能力 5

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。

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