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Blueprint

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Fmarzochi
blueprint

Turn a one-line objective into a step-by-step construction plan for multi-session, multi-agent engineering projects. Each step has a self-contained context brief so a fresh agent can execute it cold. Includes adversarial review gate, dependency graph, parallel step detection, anti-pattern catalog, and plan mutation protocol. TRIGGER when: user requests a plan, blueprint, or roadmap for a complex multi-PR task, or describes work that needs multiple sessions. DO NOT TRIGGER when: task is completable in a single PR or fewer than 3 tool calls, or user says "just do it".

Overview

PublisherFmarzochi
RepositoryEGC
Skill nameblueprint
Stars
68
Forks
49
Bundled files
Instructions only
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by Fmarzochi on GitHub. Read the source before you install it.

Installation

Install the Blueprint AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/Fmarzochi/EGC/tree/main/skills/architecture/blueprint
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Fmarzochi/EGC.git /tmp/EGC
mkdir -p .claude/skills
cp -r /tmp/EGC/skills/architecture/blueprint .claude/skills/blueprint
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Blueprint in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Blueprint on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Blueprint is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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 EGC - Extended Global Context. No separate installation is needed when EGC is installed.

Full EGC install

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

bash
test -f skills/blueprint/SKILL.md

To update later, review the EGC diff before updating:

bash
cd /path/to/EGC
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 EGC install, copy the reviewed file from the EGC repository into ~/.gemini/skills/blueprint/SKILL.md. Vendored copies do not have a git remote, so update them by re-copying the file from a reviewed EGC commit rather than running git pull.

Requirements

  • An AI coding tool with slash commands (for /blueprint)
  • Git + GitHub CLI (optional: enables full branch/PR/CI workflow; Blueprint detects absence and auto-switches to direct mode)

Frequently asked questions

What does the Blueprint AI skill do?

Turn a one-line objective into a step-by-step construction plan for multi-session, multi-agent engineering projects. Each step has a self-contained context brief so a fresh agent can execute it cold. Includes adversarial review gate, dependency graph, parallel step detection, anti-pattern catalog, and plan mutation protocol. TRIGGER when: user requests a plan, blueprint, or roadmap for a complex multi-PR task, or describes work that needs multiple sessions. DO NOT TRIGGER when: task is completable in a single PR or fewer than 3 tool calls, or user says "just do it".

Why use Blueprint on TypingMind?

Because you install it once and use it with any model. Blueprint is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Blueprint in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Fmarzochi/EGC/tree/main/skills/architecture/blueprint. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Blueprint?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Blueprint?

As many as you like. As long as a model supports skills, you can use Blueprint with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Blueprint AI skill free?

Yes. It is published on GitHub by Fmarzochi under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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