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Detool

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LilMGenius
detool

Make durable artifacts portable by replacing incidental stack, vendor, model, CLI, path, quota, or harness nouns with the mechanism they mean, while keeping provenance, runbooks, and tool-subject claims concrete.

Overview

PublisherLilMGenius
Repositorypaperthin
Skill namedetool
Stars
1.3K
Forks
118
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 LilMGenius on GitHub. Read the source before you install it.

Installation

Install the Detool 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/LilMGenius/paperthin/tree/main/skills/depth/detool
  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/LilMGenius/paperthin.git /tmp/paperthin
mkdir -p .claude/skills
cp -r /tmp/paperthin/skills/depth/detool .claude/skills/detool
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Detool 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 Detool 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 Detool 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.

Remove incidental tool coupling from artifacts that claim to outlive the stack that wrote them.

Goal

A durable artifact should stay true and actionable when the agent, harness, operating system, vendor, model, or toolchain changes. detool finds stack-specific nouns in portable content and rewrites them to the underlying mechanism without deleting the action they enabled.

The point is portability, not vagueness. A reader should still know what to inspect, run, measure, compare, or verify after the rewrite.

Workflow

  1. Read the target artifact end to end.
  2. Role before edit: classify the whole artifact, or each section if mixed, as durable/portable content, provenance/operational record, or a claim about a named tool.
  3. Sweep durable content for incidental coupling: harness paths, vendor CLIs and flags, model or product brands used as mechanisms, tool-specific environment variables, quotas, UI steps, cache homes, session files, and version-pinned behavior stated as timeless truth.
  4. Mechanism not euphemism: replace each durable-content hit with the neutral mechanism that preserves the action. If neutral wording would lose the action, keep the concrete detail as an example of the mechanism instead of pretending it generalizes.
  5. Keep provenance and operational content concrete. Build records, capsules, benchmark logs, install guides, runbooks, tool-targeted how-tos, command transcripts, and exact reproduction steps are supposed to name the stack that produced them.
  6. Keep comparative and tool-subject claims concrete. If the sentence is about a named tool, vendor, model, bug, prior-art source, or measured limit, the name is the subject, not incidental coupling.
  7. Re-read as a reader on a different stack: the artifact should still be true, portable, and executable where it promised action.
  8. Report what was neutralized, what was deliberately kept, and the role judgment behind each keep.

Rules

  • Role before edit. Never scrub before deciding whether the text is portable content, provenance, operational instruction, or a tool-subject claim.
  • Mechanism, not euphemism. "Use the session execution log and sum usage records" is a mechanism; "check the logs" is a euphemism that loses the work.
  • Preserve actionable detail. Abstract only the coupling, not the procedure, evidence, comparison, or constraint.
  • Keep provenance and operational records exact. Concrete paths, commands, flags, versions, products, and UI steps stay when they record what happened or explain how to drive a specific tool.
  • Keep comparative/tool-subject names. A bug report about a CLI, a benchmark against a model, a prior-art citation, or a vendor-specific limit keeps the named subject.
  • A pass that finds no incidental coupling changes nothing.
  • Mutate with edit-safety: assert each target exists and report a MISS instead of silently no-oping; edit unicode-safe; replace per occurrence, never by blanket sweep; script large structural moves.

Verification

Before finishing, confirm:

  1. Every changed hit was in durable or portable content.
  2. Every rewrite preserved the actionable mechanism.
  3. Every kept tool noun is provenance, operational instruction, or the subject of its claim.
  4. The report names neutralized couplings, deliberate keeps, and any judgment calls.

Frequently asked questions

What does the Detool AI skill do?

Make durable artifacts portable by replacing incidental stack, vendor, model, CLI, path, quota, or harness nouns with the mechanism they mean, while keeping provenance, runbooks, and tool-subject claims concrete.

Why use Detool on TypingMind?

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

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

Which AI models can use Detool?

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 Detool?

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

Is the Detool AI skill free?

Yes. It is published on GitHub by LilMGenius 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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