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Think

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AgriciDaniel
think

Apply the Fable-derived 10-stage OBSERVE, OBSERVE, LISTEN, THINK, CONNECT, CONNECT, FEEL, ACCEPT, CREATE, GROW loop to consequential or ambiguous reasoning and decisions. Use for think this through, deep think, architecture review, postmortem, tradeoff analysis, or challenges to assumptions. This is a reasoning review, not a deterministic vault health check or repair workflow.

Overview

PublisherAgriciDaniel
Repositoryclaude-obsidian
Skill namethink
Stars
15K
Forks
1.5K
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 AgriciDaniel on GitHub. Read the source before you install it.

Installation

Install the Think 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/AgriciDaniel/claude-obsidian.git /tmp/claude-obsidian
mkdir -p .claude/skills
cp -r /tmp/claude-obsidian/skills/think .claude/skills/think
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Think 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 Think 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 Think 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.

Think

Use the ten stages as a loop of attention, not a ceremonial transcript. Scale the depth to novelty, stakes, uncertainty, and irreversibility. Keep the final reasoning summary concise and evidence-bearing.

This skill is read-only. It may inspect available evidence, but it does not edit files, execute a vault mutation, commit Git, or publish anything. If the CREATE stage recommends a change, compose with the appropriate mutation skill after the user authorizes that operation.

Establish an evidence frame

Before the loop, separate:

  • Observed: directly supported by an input, source, test, or measurement.
  • Inferred: a conclusion drawn from observations; state the bridge.
  • Unknown: missing evidence that could change the decision.
  • Preference: a user or designer choice, not a factual claim.

Attach citations or concrete locators when sources exist. Never fabricate a quotation, locator, test result, consensus, or confidence level.

The ten stages

1. OBSERVE — external

Read the actual inputs, current state, constraints, failures, and prior work. Distinguish what was inspected in full from what was sampled or assumed.

2. OBSERVE — internal

Name the biases most likely to distort this decision: anchoring, ownership, novelty, familiarity, urgency, sunk cost, confirmation, or a desired verdict. Recalibrate confidence to the evidence available.

3. LISTEN

Recover the user's intent, success condition, constraints, and unstated stakes. Attend to error messages, dissent, edge cases, and affected voices. Ask only questions whose answers could materially change the outcome.

4. THINK

Reduce the problem to invariants, alternatives, tradeoffs, and failure modes. Prefer the smallest reversible test that could disprove the leading hypothesis. Treat failure behavior as part of the specification.

5. CONNECT — lateral

Look for the same structure in adjacent components or another domain. Use an analogy only when its mapped similarities and limits are explicit.

6. CONNECT — system

Trace upstream inputs, downstream consumers, ownership, state boundaries, interfaces, and recovery paths. Check whether a locally sound decision creates an integration failure elsewhere.

7. FEEL

Consider the user's cognitive load, emotional state, accessibility, trust, and error-recovery experience. Treat intuition as a signal to investigate, never as a substitute for evidence.

8. ACCEPT

State constraints, uncertainty, contradictory evidence, and unfavorable findings plainly. Do not inflate a score, soften a material risk to please the user, or mistake agreement for correctness. Present the strongest reasonable counterargument to the preferred conclusion.

9. CREATE

Produce the smallest useful artifact: a recommendation, decision record, experiment, draft, review, or handoff. Mark assumptions and unresolved risks. Do not mutate state under this skill.

10. GROW

Define what feedback or measurement should update the decision, when to revisit it, and what lesson is reusable. Saving the lesson is a separate explicit operation composed with save.

Verification discipline

Before calling the work complete:

  1. Test the highest-risk claim or clearly state why it remains untested.
  2. Seek disconfirming evidence, not only supporting examples.
  3. Match verification effort to blast radius and reversibility.
  4. Report actual commands, sources, artifacts, or observations used.
  5. Separate a passing check from broader correctness it does not establish.
  6. Give confidence as a calibrated qualitative judgment with reasons, not as a decorative percentage.

Output shape

Adapt the headings to the task, but preserve these outcomes:

markdown
## Decision
<recommendation or artifact>

## Evidence
<observed facts and important inferences>

## Counterargument and risks
<strongest alternative, contradictions, unknowns>

## Verification
<checks performed and checks still needed>

## Growth loop
<feedback signal, revisit condition, reusable lesson>

For a trivial, reversible lookup or typo, skip the formal loop. For a consequential decision, loop back whenever a later stage exposes a missing observation or misunderstood requirement.

Frequently asked questions

What does the Think AI skill do?

Apply the Fable-derived 10-stage OBSERVE, OBSERVE, LISTEN, THINK, CONNECT, CONNECT, FEEL, ACCEPT, CREATE, GROW loop to consequential or ambiguous reasoning and decisions. Use for think this through, deep think, architecture review, postmortem, tradeoff analysis, or challenges to assumptions. This is a reasoning review, not a deterministic vault health check or repair workflow.

Why use Think on TypingMind?

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

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

Which AI models can use Think?

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 Think?

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

Is the Think AI skill free?

Yes. It is published on GitHub by AgriciDaniel 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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