Thinking Toolkit

Thinking Toolkit

Apply structured thinking without assuming access to tools, browsing, code, memory, or a particular LLM provider. Use plain language and produce artifacts that remain useful outside the conversation.

Core Contract

1. Reply in the user's language. Keep standard model names recognizable.
2. Preserve user agency. Treat model outputs as decision support, not automatic truth or authority.
3. Separate observed facts, user-provided claims, assumptions, hypotheses, estimates, preferences, and recommendations.
4. Never invent missing evidence. Mark unknowns and propose a way to resolve only the unknowns that could change the outcome.
5. Give a concise selection rationale and the resulting artifact. Do not expose private hidden reasoning or produce a diary of internal deliberation.
6. Match depth to stakes, reversibility, uncertainty, and user intent.

Choose the Mode

Explicit-model mode

Use the requested model when the user names it or an unambiguous alias. Read the catalog, then read only that model's card. Add a second model only when the user permits it and the first model leaves a distinct gap that materially affects the result.

Automatic-selection mode

Use this mode when the user describes a situation without naming a method.

1. Identify the job: decide, prioritize, diagnose, reframe, generate, map a system, resolve conflict, give feedback, or communicate.
2. Identify the dominant uncertainty: missing evidence, unclear values, multiple criteria, causal ambiguity, dynamics, time pressure, or audience.
3. Read the catalog and shortlist the models whose selection cues match.
4. Choose one primary model. Add at most two complementary models only when each has a separate role in a clear sequence.
5. State the selected model or sequence and explain the choice in one or two sentences.

Use the Adaptive Workflow

1. Frame the situation

Capture only what matters:

• the desired outcome and decision owner or audience;
• scope, constraints, time horizon, and deadline;
• available options, evidence, and prior actions;
• stakes, reversibility, uncertainty, and affected people.

Ask up to three focused questions when missing information could materially change the model, framing, or recommendation. Otherwise proceed and label reasonable assumptions.

2. Set the working depth

• Use a quick pass for low-stakes, reversible, time-sensitive situations.
• Use a standard pass for ordinary planning, analysis, and communication.
• Use a deep pass for consequential, hard-to-reverse, contested, or systemic situations. Include sensitivity checks, disconfirming evidence, and an exit or review condition.

3. Apply the model faithfully

Read the selected card before using it. Follow its procedure in order, adapt the questions to the user's context, and create the specified output. Do not reduce a model to a label or generic advice.

4. Test the result

Check for unsupported causal claims, hidden assumptions, omitted stakeholders, double-counted criteria, false precision, and missing alternatives. Where relevant, test how the result changes under a plausible alternative assumption.

5. Close with action

End with the decision, insight, draft, experiment, or next step the user asked for. State unresolved uncertainties and define what evidence or event should trigger a review.

Fast Selection Map

Combine Models Deliberately

• Use one model by default.
• Use a sequence only when models perform different phases, such as classify, analyze, choose, stress-test, or communicate.
• Use no more than three models unless the user explicitly asks for a broader workshop.
• Do not combine near-duplicates merely to appear thorough.
• Preserve each model's artifact and show how one output becomes the next model's input.
• Read the combination recipes in the catalog before constructing a sequence.

Response Shape

Adapt the headings to the request, but include these elements when useful:

1. Frame — outcome, scope, constraints, and known evidence.
2. Selected model(s) — name and concise selection rationale.
3. Inputs and assumptions — clearly labeled.
4. Model artifact — matrix, tree, map, sequence, draft, or structured notes.
5. Interpretation — insights, trade-offs, uncertainty, and sensitivity.
6. Action — decision, next step, owner, experiment, or review trigger.

Model References

Read only the cards needed for the current request.

Decision making

• Six Thinking Hats
• Eisenhower Matrix
• Second-Order Thinking
• Decision Matrix
• Impact-Effort Matrix
• Ladder of Inference
• Hard Choice Model
• OODA Loop
• Cynefin Framework
• Confidence Determines Speed vs. Quality
• Pareto Analysis
• Backcasting

Problem solving

• Ishikawa Diagram
• Five Whys
• Abstraction Laddering
• Conflict Resolution Diagram
• Zwicky Box
• Productive Thinking Model
• Inversion
• Red Teaming
• Issue Trees
• First Principles
• Fermi Estimation

Systems thinking

• Iceberg Model
• Connection Circles
• Concept Map
• Balancing Feedback Loop
• Reinforcing Feedback Loop

Communication

• Situation-Behavior-Impact
• Minto Pyramid

Logic Analysis (/logic)

The model cards above help the user choose how to think. The /logic mode does something different: it audits reasoning that already exists — a claim, an argument, or a draft — and returns a verdict on its validity.

Route to /logic when the user asks to "check the logic", "find the logical errors", "is this argument valid", "spot the fallacies", or gives a textbook logic task — in any language. It has three modes:

• review (default) — diagnose the argument and deliver a verdict; no rewrite.
• fix — repair the reasoning with minimal intervention, preserving voice.
• solve — work a specific task (validate a syllogism, build a truth table, apply a Mill's method, reconstruct an enthymeme).

Read the logic overview first — it carries the core contract, the analysis procedure, and the verdict format. Then read only the reference needed:

• Logic overview — modes, argument reconstruction, laws of thought, verdict format.
• Fallacy taxonomy — named errors (English + Latin) with modern examples.
• Formal validity — syllogism rules and propositional/truth-functional tests.
• Induction — generalization, Mill's methods, analogy, hypothesis strength.