Thinking Reversibility logo

Thinking Reversibility

CommunityPopular
tjboudreaux
thinking-reversibility

Before heavy deliberation, classify the decision as cheap or costly to undo; decide two-way doors fast and stage one-way doors to preserve options.

Overview

Publishertjboudreaux
Repositorycc-thinking-skills
Skill namethinking-reversibility
Stars
1.3K
Forks
158
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 tjboudreaux on GitHub. Read the source before you install it.

Installation

Install the Thinking Reversibility 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/tjboudreaux/cc-thinking-skills.git /tmp/cc-thinking-skills
mkdir -p .claude/skills
cp -r /tmp/cc-thinking-skills/skills/thinking-reversibility .claude/skills/thinking-reversibility
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Thinking Reversibility 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 Thinking Reversibility 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 Thinking Reversibility 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.

Reversibility

Core rule: match process depth to undo cost. Most decisions are cheaper to reverse than they look; irreversible ones deserve deliberation and staged commitment.

When to Use

  • Uncertain how much analysis a decision deserves (tech, process, product, org)
  • Tempted to committee a low-blast-radius choice, or to rush a high-lock-in one
  • Can redesign the move (pilot, flag, abstraction, time-box) to lower undo cost
  • High-stakes choice where acting vs waiting have asymmetric recovery profiles

When NOT to Use

  • Already classified this session—decide at matched depth; do not re-label forever
  • Trivial two-way calls (names, local refactors) where deciding is cheaper than classifying
  • Externally forced move with no optionality (hard deadline, contract, regulation)
  • Correctness gates (security, data integrity) that need the right answer, not speed theater

Procedure

  1. Name the decision and undo path. State what would be committed and the concrete reverse move (rollback, migrate back, revoke, re-hire, re-contract).
  2. Score reversibility. Assess technical effort, time, money, reputation, dependents, and learning lost if reversed. Classify:
    • Type 2: undo in days, low cost → decide fast
    • Type 1.5: undo in weeks, moderate cost → light structure + monitor
    • Type 1: months or not realistically undoable → deliberate
  3. Asymmetric downside / recovery. For Type 1 or 1.5:
    • Acting wrong: downside, recoverable?, recovery cost
    • Not acting: what permanently closes (window, exclusivity, path lock)
    • Rule: recoverable acting downside + permanent inaction loss → staged commit over indefinite delay; catastrophic or third-party harm → refuse or redesign first
  4. Option-preserving redesign. Prefer pilots, feature flags, interfaces, versioning, time-boxed vendor terms, or strangler slices that convert Type 1 surface into Type 2 experiments. Deliberate only the residual irreversible core.
  5. Match process and commit. Type 2: pick a reasonable option, ship, monitor. Type 1: document assumptions, argue the opposing case, surface to owner if stakes require it. Stop once class and commitment depth are set—do not re-analyze without new undo-cost evidence.

Output

text
Decision: …
Undo path: …
Class: Type 2 | 1.5 | 1 (factors: …)
Acting downside / recovery: …
Not-acting permanent loss: …
Staging / option-preserving move: …
Process depth: decide-now | pilot | full deliberation
Commitment: …

Verification

  • Falsify: If "we can always change later" has no concrete undo path and cost, treat as more irreversible until proven otherwise.
  • Stop: After class and process depth are set, further taxonomy is waste—execute the matched process.
  • Over-application guard: Do not slow trivial Type 2 work with matrices. Do not use "two-way door" to skip verification on irreversible data, security, or public commitments.

Frequently asked questions

What does the Thinking Reversibility AI skill do?

Before heavy deliberation, classify the decision as cheap or costly to undo; decide two-way doors fast and stage one-way doors to preserve options.

Why use Thinking Reversibility on TypingMind?

Because you install it once and use it with any model. Thinking Reversibility 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 Thinking Reversibility in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/tjboudreaux/cc-thinking-skills/tree/main/skills/thinking-reversibility. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Thinking Reversibility?

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 Thinking Reversibility?

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

Is the Thinking Reversibility AI skill free?

Yes. It is published on GitHub by tjboudreaux 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇