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blueprint

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blueprint とは?

blueprint is a Claude Code agent skill that >-.

対応Claude CodeCodex CLI~Cursor
npx skills add https://github.com/affaan-m/everything-claude-code/tree/main/skills/blueprint

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ドキュメント

Blueprint — Construction Plan Generator

Turn a one-line objective into a step-by-step construction plan that any coding agent can execute cold.

When to Use

  • Breaking a large feature into multiple PRs with clear dependency order
  • Planning a refactor or migration that spans multiple sessions
  • Coordinating parallel workstreams across sub-agents
  • Any task where context loss between sessions would cause rework

Do not use for tasks completable in a single PR, fewer than 3 tool calls, or when the user says "just do it."

How It Works

Blueprint runs a 5-phase pipeline:

  1. Research — Pre-flight checks (git, gh auth, remote, default branch), then reads project structure, existing plans, and memory files to gather context.
  2. Design — Breaks the objective into one-PR-sized steps (3–12 typical). Assigns dependency edges, parallel/serial ordering, model tier (strongest vs default), and rollback strategy per step.
  3. Draft — Writes a self-contained Markdown plan file to plans/. Every step includes a context brief, task list, verification commands, and exit criteria — so a fresh agent can execute any step without reading prior steps.
  4. Review — Delegates adversarial review to a strongest-model sub-agent (e.g., Opus) against a checklist and anti-pattern catalog. Fixes all critical findings before finalizing.
  5. Register — Saves the plan, updates memory index, and presents the step count and parallelism summary to the user.

Blueprint detects git/gh availability automatically. With git + GitHub CLI, it generates full branch/PR/CI workflow plans. Without them, it switches to direct mode (edit-in-place, no branches).

Examples

Basic usage

/blueprint myapp "migrate database to PostgreSQL"

Produces plans/myapp-migrate-database-to-postgresql.md with steps like:

  • Step 1: Add PostgreSQL driver and connection config
  • Step 2: Create migration scripts for each table
  • Step 3: Update repository layer to use new driver
  • Step 4: Add integration tests against PostgreSQL
  • Step 5: Remove old database code and config

Multi-agent project

/blueprint chatbot "extract LLM providers into a plugin system"

Produces a plan with parallel steps where possible (e.g., "implement Anthropic plugin" and "implement OpenAI plugin" run in parallel after the plugin interface step is done), model tier assignments (strongest for the interface design step, default for implementation), and invariants verified after every step (e.g., "all existing tests pass", "no provider imports in core").

Key Features

  • Cold-start execution — Every step includes a self-contained context brief. No prior context needed.
  • Adversarial review gate — Every plan is reviewed by a strongest-model sub-agent against a checklist covering completeness, dependency correctness, and anti-pattern detection.
  • Branch/PR/CI workflow — Built into every step. Degrades gracefully to direct mode when git/gh is absent.
  • Parallel step detection — Dependency graph identifies steps with no shared files or output dependencies.
  • Plan mutation protocol — Steps can be split, inserted, skipped, reordered, or abandoned with formal protocols and audit trail.
  • Zero runtime risk — Pure Markdown skill. The entire repository contains only .md files — no hooks, no shell scripts, no executable code, no package.json, no build step. Nothing runs on install or invocation beyond Claude Code's native Markdown skill loader.

Installation

This skill ships with Everything Claude Code. No separate installation is needed when ECC is installed.

Full ECC install

If you are working from the ECC repository checkout, verify the skill is present with:

test -f skills/blueprint/SKILL.md

To update later, review the ECC diff before updating:

cd /path/to/everything-claude-code
git fetch origin main
git log --oneline HEAD..origin/main       # review new commits before updating
git checkout <reviewed-full-sha>          # pin to a specific reviewed commit

Vendored standalone install

If you are vendoring only this skill outside the full ECC install, copy the reviewed file from the ECC repository into ~/.claude/skills/blueprint/SKILL.md. Vendored copies do not have a git remote, so update them by re-copying the file from a reviewed ECC commit rather than running git pull.

Requirements

  • Claude Code (for /blueprint slash command)
  • Git + GitHub CLI (optional — enables full branch/PR/CI workflow; Blueprint detects absence and auto-switches to direct mode)

Source

Inspired by antbotlab/blueprint — upstream project and reference design.

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

accessibility

Design, implement, and audit inclusive digital products using WCAG 2.2 Level AA. Use when building or auditing UI that must meet WCAG 2.2 Level AA, or when reviewing a change for keyboard, contrast, or screen-reader support.

affaan-m/claude-api

Anthropic Claude API patterns for Python and TypeScript. Covers Messages API, streaming, tool use, vision, extended thinking, batches, prompt caching, and Claude Agent SDK. Use when building applications with the Claude API or Anthropic SDKs.

affaan-m/everything-claude-code

End-to-end marketing campaign planning and execution. Covers audience research, positioning, campaign angle definition, landing page copy, email sequences, social posts, ad copy, short-form video scripts, and content calendars. Use as the orchestration layer for multi-channel product launches. Use when planning or executing a multi-channel product launch, or producing landing page, email, social, or ad copy.

affaan-m/everything-claude-code

Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.

affaan-m/everything-claude-code-conventions

Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.

affaan-m/frontend-design

Create distinctive, production-grade frontend interfaces with high design quality. Use when the user asks to build web components, pages, or applications and the visual direction matters as much as the code quality.

affaan-m/gget

gget CLI and Python workflow for quick genomic database queries, sequence lookup, BLAST-style searches, enrichment checks, and reproducible bioinformatics evidence logs.

affaan-m/literature-review

Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.

affaan-m/motion-ui

Production-ready UI motion system for React/Next.js. Use when implementing animations, transitions, or motion patterns.

affaan-m/project-guidelines-example

Example project-specific skill template based on a real production application.

affaan-m/pubmed-database

Direct PubMed and NCBI E-utilities search workflows for biomedical literature, MeSH queries, PMID lookup, citation retrieval, and API-backed literature monitoring.

affaan-m/scholar-evaluation

Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.

affaan-m/uspto-database

USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.

agent-architecture-audit

Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings with code-first fixes. Essential for developers building agent applications, autonomous loops, or any LLM-powered feature. Use when an agent or LLM feature misbehaves and the failing layer is unknown, or before shipping an agent stack.

agent-eval

Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics. Use when choosing between coding agents, or when a change to an agent setup needs measured pass rate, cost, and time rather than an impression.

agent-harness-construction

Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates. Use when defining or revising an agent

agentic-engineering

Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing. Use when planning or executing engineering work that agents will carry out end to end.

agentic-os

Build persistent multi-agent operating systems on Claude Code. Covers kernel architecture, specialist agents, slash commands, file-based memory, scheduled automation, and state management without external databases. Use when building a persistent multi-agent system on Claude Code with its own memory, commands, and scheduling.

agent-introspection-debugging

Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails and you need a reproducible diagnosis instead of a retry.

agent-payment-x402

Add x402 payment execution to AI agents with per-task budgets, spending controls, and non-custodial wallets. Supports Base through agentwallet-sdk and X Layer through OKX Payments / OKX Agent Payments Protocol. Use when an agent must pay for something itself and needs per-task budgets, spending controls, and a non-custodial wallet.

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