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Superpowers Executing Plans

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christopherarter
superpowers-executing-plans

Executing a written plan yourself? Load first to track progress and verify each task.

Overview

Publisherchristopherarter
Repositorysuperpowers-reasonix
Skill namesuperpowers-executing-plans
Stars
101
Forks
7
Bundled files
Instructions only
LicenseMIT
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 christopherarter on GitHub. Read the source before you install it.

Installation

Install the Superpowers Executing Plans 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/christopherarter/superpowers-reasonix/tree/main/skills/superpowers-executing-plans
  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/christopherarter/superpowers-reasonix.git /tmp/superpowers-reasonix
mkdir -p .claude/skills
cp -r /tmp/superpowers-reasonix/skills/superpowers-executing-plans .claude/skills/superpowers-executing-plans
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Superpowers Executing Plans 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 Superpowers Executing Plans 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 Superpowers Executing Plans 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.

Executing Plans

Execute the plan yourself, task by task, in this session. The plan carries the design; a persistent ledger carries your decisions and progress through compaction. TDD is the per-task gate, and a fresh whole-branch review is the final second opinion.

Announce at start: "I'm using the superpowers-executing-plans skill to implement this plan."

Continue from one task to the next without asking the user to say "continue." User instructions and approvals already given remain valid. Keep commentary concise; the ledger and test output carry the detail.

Setup

  1. Verify an isolated worktree using superpowers-using-git-worktrees. Do not implement on main without explicit authorization.
  2. Read the plan and linked spec. If they conflict, the spec is binding; when neither answers, make a reasonable ruling.
  3. Create a task list with Reasonix todo_write. Todos show current status; they do not replace the ledger.
  4. Create a ledger at ~/.reasonix/plan-ledgers/<repo>/<plan-name>.md (or another persistent, plan-specific location). Its first line names the absolute plan path. Check for an existing ledger first; after compaction, trust its completed-task lines and git log rather than your memory. Never overwrite a ledger for a different plan.
  5. Load superpowers-test-driven-development before Task 1. Scan task interfaces for conflicts and record pre-flight findings in the ledger. Record Pre-flight: no shared interfaces when none exist.

Keep plan-specific artifacts together. Don't remove another plan's ledger. If the ledger is lost, reconstruct completion from commits and tests before continuing.

Task Loop

For each incomplete task:

  1. Read that task's exact brief and note BASE, the commit before its work. Mark the todo in progress.
  2. Follow its steps in RED-GREEN order. Run each command and compare actual output with its Expected: line. A test that passes before implementation needs investigation.
  3. If code is wrong, load superpowers-systematic-debugging and find the cause. If the plan is wrong or ambiguous, make the smallest decision satisfying the spec and add Task N: Ruling: <decision> — <why> — <cost if wrong> to the ledger. Continue. An unrecorded deviation is a hidden decision.
  4. Commit as the plan directs. Verify every named test exists and ran, every expected output was checked, and the final task test command passed. Load superpowers-verification-before-completion before claiming task completion.
  5. Append Task N: complete (commits <BASE>..<HEAD>, tests: <command> → <result>) to the ledger only after the test passes. Mark the todo complete and take the next task.

Record rulings and completion as work happens, not at the end. After compaction, resume at the first task without a completion line. A task spanning multiple commits uses its saved BASE, not HEAD~1.

When to Stop

Resolve routine conflicts and plan gaps by ruling and continuing. Stop only for an irreversible or destructive action, a security-sensitive action, an external side effect that normally needs user approval, or a plan so broken that every path forward is a guess. Existing user authorization satisfies a gate; do not ask twice.

Whole-Branch Review

After all tasks pass, review the full range from the branch's merge base to HEAD, not only the last commit. Give a fresh native Reasonix review or task reviewer the plan, spec, diff, ledger rulings, and the plan's Review Focus. If no independent reviewer is available, perform a separate self-review and disclose that limit.

Re-grade findings by the effect on a reasonable user, even when the spec is silent. Fix critical and important findings in one pass: reproduce each with a failing test, make it pass, run the full suite, and record Final: fixed <finding> — <test> RED→GREEN, suite <result>. Record deferred minor findings in the ledger and final handoff. If you decline a substantive finding, ledger a ruling with the cost if wrong. Do not silently discard reviewer concerns.

Then load superpowers-finishing-a-development-branch. Report the verification evidence and all rulings and deferred minors. Preserve the ledger until the branch result is settled; remove only this plan's scratch files when they are no longer needed.

Red Flags

ThoughtReality
"I remember Task N"Read the exact brief; memory is a summary.
"The test should pass"Run it and read the output.
"I'll write ledger lines later"Compaction may happen before later. Record each decision now.
"The plan is wrong, so I'll just do the right thing"Rule, ledger the reason and cost, then continue.
"I should check in before the next task"Continue through the authorized plan.
"I reviewed my own diff, so a fresh review adds nothing"A fresh context can catch assumptions carried from implementation.

Frequently asked questions

What does the Superpowers Executing Plans AI skill do?

Executing a written plan yourself? Load first to track progress and verify each task.

Why use Superpowers Executing Plans on TypingMind?

Because you install it once and use it with any model. Superpowers Executing Plans 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 Superpowers Executing Plans in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/christopherarter/superpowers-reasonix/tree/main/skills/superpowers-executing-plans. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Superpowers Executing Plans?

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 Superpowers Executing Plans?

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

Is the Superpowers Executing Plans AI skill free?

Yes. It is published on GitHub by christopherarter under the MIT 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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