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Plan Pipeline

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FlorianBruniaux
plan-pipeline

Orchestrates the complete planning pipeline: product direction (ceo-review) -> architecture (eng-review) -> implementation plan (start) -> validation (validate) -> execution (execute). Run stages individually or let the orchestrator coordinate the full flow.

Overview

PublisherFlorianBruniaux
Repositoryclaude-code-ultimate-guide
Skill nameplan-pipeline
Stars
6K
Forks
782
Bundled files
Instructions only
LicenseCC-BY-SA-4.0
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 FlorianBruniaux on GitHub. Read the source before you install it.

Installation

Install the Plan Pipeline 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.
  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/FlorianBruniaux/claude-code-ultimate-guide.git /tmp/claude-code-ultimate-guide
mkdir -p .claude/skills
cp -r /tmp/claude-code-ultimate-guide/examples/skills/plan-pipeline .claude/skills/plan-pipeline
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Plan Pipeline 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 Plan Pipeline 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 Plan Pipeline 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.

Plan Pipeline Orchestrator

Orchestrates the complete plan-to-execution pipeline. Can run the full pipeline or a single isolated stage.

Stages

StageSkillPurpose
1/plan-pipeline:ceo-reviewChallenge the brief, lock product direction
2/plan-pipeline:eng-reviewLock architecture, diagrams, and test matrix
3/plan-pipeline:start5-phase planning: PRD, research, ADRs, task list
4/plan-pipeline:validate2-layer validation before any code is written
5/plan-pipeline:executeWorktree isolation, parallel agents, quality gate, PR

Usage

/plan-pipeline                     # full pipeline, asks for context
/plan-pipeline --from=start        # skip gates, start from planning phase
/plan-pipeline --from=validate     # validate an existing plan
/plan-pipeline --from=execute      # execute a validated plan

When to Use Each Stage

ceo-review: use before any significant feature when the direction is not locked. Especially valuable when the request is specific (specificity signals collapsed solution space).

eng-review: use after direction is locked. Required for features with async components, external dependencies, or multi-step flows.

start: use for any non-trivial feature touching more than 2 files or involving architecture decisions.

validate: always before execute. The cost of validation is negligible against the cost of discovering issues mid-execution.

execute: after validate confirms all issues are resolved.

Workflow

  1. Collect context: what are we building, and what stage do we start from?
  2. ceo-review: product direction gate (can be skipped with --from=eng-review or later)
  3. eng-review: architecture gate (can be skipped with --from=start or later)
  4. CHECKPOINT: ask user to confirm direction and architecture before planning
  5. start: run 5-phase planning, produce docs/plans/plan-{name}.md
  6. CHECKPOINT: present plan for review before validation
  7. validate: 2-layer validation (structural + specialist agents)
  8. execute: worktree isolation -> parallel agents -> quality gate -> PR

Dependency Graph

   ceo-review
        |
   eng-review
        |
      start
        |
    validate
        |
    execute

Notes

Each stage writes its output to disk before the next stage begins. If the pipeline is interrupted, resume with --from=<stage> using the correct stage name. All decisions are recorded in docs/plans/plan-{name}.md and the corresponding ADRs in docs/adr/.

Frequently asked questions

What does the Plan Pipeline AI skill do?

Orchestrates the complete planning pipeline: product direction (ceo-review) -> architecture (eng-review) -> implementation plan (start) -> validation (validate) -> execution (execute). Run stages individually or let the orchestrator coordinate the full flow.

Why use Plan Pipeline on TypingMind?

Because you install it once and use it with any model. Plan Pipeline 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 Plan Pipeline in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/FlorianBruniaux/claude-code-ultimate-guide/tree/main/examples/skills/plan-pipeline. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Plan Pipeline?

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 Plan Pipeline?

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

Is the Plan Pipeline AI skill free?

Yes. It is published on GitHub by FlorianBruniaux under the CC-BY-SA-4.0 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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