startproject — for Claude Code startproject, community, for Claude Code, ide skills, team-implement, team-review, ## Workflow, Project, Gemini, Overview

v1.0.0

关于此技能

适用场景: Ideal for AI agents that need gemini の 1m コンテキストと agent teams を活用したプロジェクト開始スキル。. 本地化技能摘要: Your job: Research external information needed for this project. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

功能特性

Gemini の 1M コンテキストと Agent Teams を活用したプロジェクト開始スキル。
このスキルは計画フェーズ(Phase 1-3)を担当する。実装は /team-implement、レビューは /team-review で行う。
/startproject <feature ← このスキル(計画)
/team-implement ← 並列実装
/team-review ← 並列レビュー

# 核心主题

ribon-org ribon-org
[0]
[0]
更新于: 3/9/2026

Killer-Skills Review

Decision support comes first. Repository text comes second.

Reference-Only Page Review Score: 10/11

This page remains useful for teams, but Killer-Skills treats it as reference material instead of a primary organic landing page.

Original recommendation layer Concrete use-case guidance Explicit limitations and caution Quality floor passed for review
Review Score
10/11
Quality Score
67
Canonical Locale
ja
Detected Body Locale
ja

适用场景: Ideal for AI agents that need gemini の 1m コンテキストと agent teams を活用したプロジェクト開始スキル。. 本地化技能摘要: Your job: Research external information needed for this project. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

核心价值

推荐说明: startproject helps agents gemini の 1m コンテキストと agent teams を活用したプロジェクト開始スキル。. Your job: Research external information needed for this project. This AI agent skill supports Claude Code, Cursor, and Windsurf

适用 Agent 类型

适用场景: Ideal for AI agents that need gemini の 1m コンテキストと agent teams を活用したプロジェクト開始スキル。.

赋予的主要能力 · startproject

适用任务: Applying Gemini の 1M コンテキストと Agent Teams を活用したプロジェクト開始スキル。
适用任务: Applying このスキルは計画フェーズ(Phase 1-3)を担当する。実装は /team-implement、レビューは /team-review で行う。
适用任务: Applying /startproject <feature ← このスキル(計画)

! 使用限制与门槛

  • 限制说明: Requires repository-specific context from the skill documentation
  • 限制说明: Works best when the underlying tools and dependencies are already configured

Why this page is reference-only

  • - Current locale does not satisfy the locale-governance contract.

Source Boundary

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

评审后的下一步

先决定动作,再继续看上游仓库材料

Killer-Skills 的主价值不应该停在“帮你打开仓库说明”,而是先帮你判断这项技能是否值得安装、是否应该回到可信集合复核,以及是否已经进入工作流落地阶段。

实验室 Demo

Browser Sandbox Environment

⚡️ Ready to unleash?

Experience this Agent in a zero-setup browser environment powered by WebContainers. No installation required.

Boot Container Sandbox

常见问题与安装步骤

以下问题与步骤与页面结构化数据保持一致,便于搜索引擎理解页面内容。

? FAQ

startproject 是什么?

适用场景: Ideal for AI agents that need gemini の 1m コンテキストと agent teams を活用したプロジェクト開始スキル。. 本地化技能摘要: Your job: Research external information needed for this project. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

如何安装 startproject?

运行命令:npx killer-skills add ribon-org/ribon/startproject。支持 Cursor、Windsurf、VS Code、Claude Code 等 19+ IDE/Agent。

startproject 适用于哪些场景?

典型场景包括:适用任务: Applying Gemini の 1M コンテキストと Agent Teams を活用したプロジェクト開始スキル。、适用任务: Applying このスキルは計画フェーズ(Phase 1-3)を担当する。実装は /team-implement、レビューは /team-review で行う。、适用任务: Applying /startproject <feature ← このスキル(計画)。

startproject 支持哪些 IDE 或 Agent?

该技能兼容 Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer。可使用 Killer-Skills CLI 一条命令通用安装。

startproject 有哪些限制?

限制说明: Requires repository-specific context from the skill documentation;限制说明: Works best when the underlying tools and dependencies are already configured。

安装步骤

  1. 1. 打开终端

    在你的项目目录中打开终端或命令行。

  2. 2. 执行安装命令

    运行:npx killer-skills add ribon-org/ribon/startproject。CLI 会自动识别 IDE 或 AI Agent 并完成配置。

  3. 3. 开始使用技能

    startproject 已启用,可立即在当前项目中调用。

! 参考页模式

此页面仍可作为安装与查阅参考,但 Killer-Skills 不再把它视为主要可索引落地页。请优先阅读上方评审结论,再决定是否继续查看上游仓库说明。

Upstream Repository Material

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

Upstream Source

startproject

Your job: Research external information needed for this project. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows. Gemini の 1M コンテキストと

SKILL.md
Readonly
Upstream Repository Material
The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.
Supporting Evidence

Start Project

Gemini の 1M コンテキストと Agent Teams を活用したプロジェクト開始スキル。

Overview

このスキルは計画フェーズ(Phase 1-3)を担当する。実装は /team-implement、レビューは /team-review で行う。

/startproject <feature>     ← このスキル(計画)
    ↓ 承認後
/team-implement             ← 並列実装
    ↓ 完了後
/team-review                ← 並列レビュー

Workflow

Phase 1: UNDERSTAND (Gemini 1M context + Claude Lead)
  Gemini がコードベースを分析(1M context)、Claude がユーザーと対話
    ↓
Phase 2: RESEARCH & DESIGN (Agent Teams — 並列)
  Researcher(Gemini)←→ Architect が双方向通信しながら調査・設計
    ↓
Phase 3: PLAN & APPROVE (Claude Lead + User)
  調査と設計を統合し、計画を作成してユーザー承認

Phase 1: UNDERSTAND (Gemini + Claude Lead)

Gemini の 1M コンテキストでコードベースを分析し、Claude がユーザーと対話する。

Claude Code のコンテキストは 200K。大規模コードベースの全体分析は Gemini(1M context)に委譲する。

Step 1: Analyze Codebase with Gemini

Gemini CLI を使い、コードベース全体を分析する:

bash
1# gemini-explore サブエージェント経由(推奨) 2Task tool: 3 subagent_type: "gemini-explore" 4 prompt: | 5 Analyze this codebase comprehensively: 6 - Directory structure and organization 7 - Key modules and their responsibilities 8 - Existing patterns and conventions 9 - Dependencies and tech stack 10 - Test structure 11 12 gemini -p "Analyze this codebase: directory structure, key modules, architecture patterns, dependencies, conventions, and test structure" 2>/dev/null 13 14 Save analysis to .claude/docs/research/{feature}-codebase.md 15 Return concise summary (5-7 key findings).

Gemini の分析結果を補完するため、Claude は Glob/Grep/Read で特定ファイルを確認できる。

Step 2: Requirements Gathering

ユーザーに質問して要件を明確化(日本語で):

  1. 目的: 何を達成したいですか?
  2. スコープ: 含めるもの・除外するものは?
  3. 技術的要件: 特定のライブラリ、制約は?
  4. 成功基準: 完了の判断基準は?
  5. 最終デザイン: どのような形にしたいですか?

Step 3: Create Project Brief

コードベース理解 + 要件を「プロジェクト概要書」にまとめる:

markdown
1## Project Brief: {feature} 2 3### Current State 4- Architecture: {existing architecture summary} 5- Relevant code: {key files and modules} 6- Patterns: {existing patterns to follow} 7 8### Goal 9{User's desired outcome in 1-2 sentences} 10 11### Scope 12- Include: {list} 13- Exclude: {list} 14 15### Constraints 16- {technical constraints} 17- {library requirements} 18 19### Success Criteria 20- {measurable criteria}

This brief is passed to Phase 2 teammates as shared context.


Phase 2: RESEARCH & DESIGN (Agent Teams — Parallel)

Agent Teams で Researcher と Architect を並列起動し、双方向通信させる。

サブエージェントとの決定的な違い: Teammates は相互通信できる。 Researcher の発見が Architect の設計を変え、Architect の要求が新たな調査を生む。

Team Setup

Create an agent team for project planning: {feature}

Spawn two teammates:

1. **Researcher** — Gemini CLI (1M context + Google Search grounding) で外部調査を行う
   Prompt: "You are the Researcher for project: {feature}.

   Your job: Research external information needed for this project.

   Project Brief:
   {project brief from Phase 1}

   Tasks:
   1. Research libraries and tools: usage patterns, constraints, best practices
   2. Find latest documentation and API specifications
   3. Identify common pitfalls and anti-patterns
   4. Look for similar implementations and reference architectures

   How to research:
   - Use Gemini CLI for comprehensive research (1M context + Google Search grounding):
     gemini -p 'Research: {topic}. Find latest best practices, constraints, and recommendations' 2>/dev/null
   - Use WebSearch/WebFetch for targeted lookups when needed

   Save all findings to .claude/docs/research/{feature}.md
   Save library docs to .claude/docs/libraries/{library}.md

   Communicate with Architect teammate:
   - Share findings that affect design decisions
   - Respond to Architect's research requests
   - Flag constraints that limit implementation options

   IMPORTANT — Work Log:
   When ALL your tasks are complete, write a work log file to:
     .claude/logs/agent-teams/{team-name}/researcher.md

   Use this format:
   # Work Log: Researcher
   ## Summary
   (1-2 sentence summary of what you researched)
   ## Tasks Completed
   - [x] {task}: {brief description of findings}
   ## Sources Consulted
   - {URL or source}: {what was found}
   ## Key Findings
   - {finding}: {relevance to project}
   ## Communication with Teammates
   - → {recipient}: {summary of message sent}
   - ← {sender}: {summary of message received}
   ## Issues Encountered
   - {issue}: {how it was resolved}
   (If none, write 'None')
   "

2. **Architect** — 設計・計画を行う
   Prompt: "You are the Architect for project: {feature}.

   Your job: Design the architecture and create implementation plan.

   Project Brief:
   {project brief from Phase 1}

   Tasks:
   1. Design architecture (modules, interfaces, data flow)
   2. Select patterns (considering existing codebase conventions)
   3. Create step-by-step implementation plan with dependencies
   4. Identify risks and mitigation strategies

   Update .claude/docs/DESIGN.md with architecture decisions.

   Communicate with Researcher teammate:
   - Request specific library/tool research
   - Share design constraints that need validation
   - Adjust design based on Researcher's findings

   IMPORTANT — Work Log:
   When ALL your tasks are complete, write a work log file to:
     .claude/logs/agent-teams/{team-name}/architect.md

   Use this format:
   # Work Log: Architect
   ## Summary
   (1-2 sentence summary of what you designed)
   ## Tasks Completed
   - [x] {task}: {brief description of what was done}
   ## Design Decisions
   - {decision}: {rationale}
   ## Communication with Teammates
   - → {recipient}: {summary of message sent}
   - ← {sender}: {summary of message received}
   ## Issues Encountered
   - {issue}: {how it was resolved}
   (If none, write 'None')
   "

Wait for both teammates to complete their tasks.

Why Bidirectional Communication Matters

Example interaction flow:

Researcher: "httpx has a connection pool limit of 100 by default"
    → Architect: "Need to add connection pool config to design"
    → Architect: "Also research: does httpx support HTTP/2 multiplexing?"
    → Researcher: "Yes, via httpx[http2]. Requires h2 dependency."
    → Architect: "Updated design to use HTTP/2 for the API client module"

Without Agent Teams (old subagent approach), this would require:

  1. Gemini subagent finishes → returns summary
  2. Claude reads summary → creates new prompt
  3. Another subagent finishes → returns summary
  4. If more info needed → another round

Agent Teams collapses this into a single parallel session with real-time interaction.


Phase 3: PLAN & APPROVE (Claude Lead)

Agent Teams の結果を統合し、実装計画を作成してユーザーに承認を求める。

Step 1: Synthesize Results

Read outputs from Phase 2:

  • .claude/docs/research/{feature}.md — Researcher findings
  • .claude/docs/libraries/{library}.md — Library documentation
  • .claude/docs/DESIGN.md — Architecture decisions

Step 2: Create Implementation Plan

Create task list using TodoWrite:

python
1{ 2 "content": "Implement {specific task}", 3 "activeForm": "Implementing {specific task}", 4 "status": "pending" 5}

Task breakdown should follow references/task-patterns.md.

Step 3: Update CLAUDE.md

Add project context to CLAUDE.md for cross-session persistence:

markdown
1--- 2 3## Current Project: {feature} 4 5### Context 6- Goal: {1-2 sentences} 7- Key files: {list} 8- Dependencies: {list} 9 10### Architecture 11- {Key architecture decisions from Architect} 12 13### Library Constraints 14- {Key constraints from Researcher} 15 16### Decisions 17- {Decision 1}: {rationale} 18- {Decision 2}: {rationale}

Step 4: Present to User

Present the plan in Japanese:

markdown
1## プロジェクト計画: {feature} 2 3### コードベース分析 4{Key findings from Phase 1 — 3-5 bullet points} 5 6### 調査結果 (Researcher) 7{Key findings — 3-5 bullet points} 8{Library constraints and recommendations} 9 10### 設計方針 (Architect) 11{Architecture overview} 12{Key design decisions with rationale} 13 14### タスクリスト ({N}個) 15{Task list with dependencies} 16 17### リスクと注意点 18{From Architect's analysis} 19 20### 次のステップ 211. この計画で進めてよろしいですか? 222. 承認後、`/team-implement` で並列実装を開始できます 233. 実装後、`/team-review` で並列レビューを行います 24 25--- 26この計画で進めてよろしいですか?

Output Files

FileAuthorPurpose
.claude/docs/research/{feature}.mdResearcherExternal research findings
.claude/docs/libraries/{lib}.mdResearcherLibrary documentation
.claude/docs/DESIGN.mdArchitectArchitecture decisions
CLAUDE.md (updated)LeadCross-session project context
Task list (internal)LeadImplementation tracking

Tips

  • Phase 1: Gemini(1M context)でコードベースを分析し、Claude がユーザーと対話する
  • Phase 2: Agent Teams の双方向通信により、Researcher(Gemini)と Architect が相互に影響し合える
  • Phase 3: 計画承認後、/team-implement で並列実装に進む
  • Ctrl+T: タスクリストの表示切り替え
  • Shift+Up/Down: チームメイト間の移動(Agent Teams 使用時)

相关技能

寻找 startproject 的替代方案 (Alternative) 或可搭配使用的同类 community Skill?探索以下相关开源技能。

查看全部

openclaw-release-maintainer

Logo of openclaw
openclaw

本地化技能摘要: 🦞 # OpenClaw Release Maintainer Use this skill for release and publish-time workflow. It covers ai, assistant, crustacean workflows. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

333.8k
0
AI

widget-generator

Logo of f
f

本地化技能摘要: Generate customizable widget plugins for the prompts.chat feed system # Widget Generator Skill This skill guides creation of widget plugins for prompts.chat . It covers ai, artificial-intelligence, awesome-list workflows. This AI agent skill supports Claude Code, Cursor, and Windsurf

149.6k
0
AI

flags

Logo of vercel
vercel

本地化技能摘要: The React Framework # Feature Flags Use this skill when adding or changing framework feature flags in Next.js internals. It covers blog, browser, compiler workflows. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

138.4k
0
浏览器

pr-review

Logo of pytorch
pytorch

本地化技能摘要: Usage Modes No Argument If the user invokes /pr-review with no arguments, do not perform a review . It covers autograd, deep-learning, gpu workflows. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

98.6k
0
开发者工具