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Make Plan

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thedotmack
make-plan

Create a detailed, phased implementation plan with documentation discovery. Use when asked to plan a feature, task, or multi-step implementation — especially before executing with do.

Overview

Publisherthedotmack
Repositoryclaude-mem
Skill namemake-plan
Stars
94.1K
Forks
8.3K
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 thedotmack on GitHub. Read the source before you install it.

Installation

Install the Make Plan 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/thedotmack/claude-mem.git /tmp/claude-mem
mkdir -p .claude/skills
cp -r /tmp/claude-mem/plugin/skills/make-plan .claude/skills/make-plan
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Make Plan 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 Make Plan 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 Make Plan 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.

Make Plan

You are an ORCHESTRATOR. Create an LLM-friendly plan in phases that can be executed consecutively in new chat contexts.

Delegation Model

Use subagents for fact gathering and extraction (docs, examples, signatures, grep results). Keep synthesis and plan authoring with the orchestrator (phase boundaries, task framing, final wording). If a subagent report is incomplete or lacks evidence, re-check with targeted reads/greps before finalizing.

Subagent Reporting Contract (MANDATORY)

Each subagent response must include:

  1. Sources consulted (files/URLs) and what was read
  2. Concrete findings (exact API names/signatures; exact file paths/locations)
  3. Copy-ready snippet locations (example files/sections to copy)
  4. "Confidence" note + known gaps (what might still be missing)

Reject and redeploy the subagent if it reports conclusions without sources.

Plan Structure

Phase 0: Documentation Discovery (ALWAYS FIRST)

Before planning implementation, deploy "Documentation Discovery" subagents to:

  1. Search for and read relevant documentation, examples, and existing patterns
  2. Identify the actual APIs, methods, and signatures available (not assumed)
  3. Create a brief "Allowed APIs" list citing specific documentation sources
  4. Note any anti-patterns to avoid (methods that DON'T exist, deprecated parameters)

The orchestrator consolidates findings into a single Phase 0 output.

Each Implementation Phase Must Include

  1. What to implement — Frame tasks to COPY from docs, not transform existing code
    • Good: "Copy the V2 session pattern from docs/examples.ts:45-60"
    • Bad: "Migrate the existing code to V2"
  2. Documentation references — Cite specific files/lines for patterns to follow
  3. Verification checklist — How to prove this phase worked (tests, grep checks)
  4. Anti-pattern guards — What NOT to do (invented APIs, undocumented params)

Final Phase: Verification

  1. Verify all implementations match documentation
  2. Check for anti-patterns (grep for known bad patterns)
  3. Run tests to confirm functionality

Key Principles

  • Documentation Availability ≠ Usage: Explicitly require reading docs
  • Task Framing Matters: Direct agents to docs, not just outcomes
  • Verify > Assume: Require proof, not assumptions about APIs
  • Session Boundaries: Each phase should be self-contained with its own doc references

Anti-Patterns to Prevent

  • Inventing API methods that "should" exist
  • Adding parameters not in documentation
  • Skipping verification steps
  • Assuming structure without checking examples

See Also

  • oh-my-issues — the issue-side sibling. When the plan you're being asked to make is rooted in a bug or feature backlog rather than a fresh idea, route through oh-my-issues first to cluster issues by root cause into plan masters and plans/0X-*.md design docs. make-plan then operates on the design doc for one plan slice.

Frequently asked questions

What does the Make Plan AI skill do?

Create a detailed, phased implementation plan with documentation discovery. Use when asked to plan a feature, task, or multi-step implementation — especially before executing with do.

Why use Make Plan on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/thedotmack/claude-mem/tree/main/plugin/skills/make-plan. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Make Plan?

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 Make Plan?

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

Is the Make Plan AI skill free?

Yes. It is published on GitHub by thedotmack 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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