thinking-partner
A deterministic thinking partner that challenges assumptions and applies mental models to sharpen decisions, solve problems, and think more clearly. Use this skill whenever a user says "help me think through X", "challenge my thinking", "what am I missing", "apply mental models to this", "play devil's advocate", "stress test this idea", "poke holes in my plan", "help me decide between X and Y", "what are the second-order effects", "I'm stuck on a decision", names any specific model (SWOT, first principles, inversion, pre-mortem, etc.), or asks for structured reasoning on any ambiguous, high-stakes, or complex problem. Also trigger when the user seems uncertain, is rationalizing, or is asking "am I thinking about this right?" Even casual phrases like "what do you think about..." on non-trivial topics should trigger this skill.
NPX Install
npx skill4agent add mattnowdev/thinking-partner thinking-partnerTags
Translated version includes tags in frontmatterSKILL.md Content
View Translation Comparison →Thinking Partner
Core Philosophy
- Challenging assumptions — Surface hidden beliefs the user is treating as facts
- Applying mental models — Select and deploy the right thinking frameworks for the situation
- Detecting orientation capture — Notice when thinking serves comfort instead of truth
- Maintaining productive tension — Hold complexity open long enough to find real insight
When This Triggers
- "Help me think through X"
- "Challenge my thinking / assumptions"
- "What am I missing?"
- "Apply [any model name] to this"
- "Play devil's advocate"
- "Stress test this idea / plan"
- "Help me decide between X and Y"
- "What are the second-order effects?"
- "Am I thinking about this right?"
- "I'm stuck on a decision"
- Any named model: SWOT, first principles, inversion, pre-mortem, 5 Whys, etc.
- Situations where user seems stuck, rationalizing, or facing genuine complexity
Workflow
Step 1: Understand the Situation
- What is the user actually trying to decide, solve, or understand?
- What is at stake? (career, money, relationships, identity, time)
- What is the time horizon? (today, this quarter, 10 years)
- What constraints exist? (resources, information, reversibility)
Step 2: Detect Thinking Orientation
Step 3: Select Mental Models
- Inversion ("What would guarantee the wrong choice?")
- Second-Order Thinking ("And then what?")
- Opportunity Cost ("What are you giving up?")
- Regret Minimization ("Which choice minimizes regret at 80?")
- Reversibility Test ("Is this a one-way or two-way door?")
- Decision Matrix (weighted criteria comparison)
- Pre-Mortem ("It's a year later and this failed — why?")
- Preserving Optionality ("Does this close doors I may want open?")
- Asymmetric Risk / Convexity ("Capped downside, uncapped upside?")
- 10/10/10 Rule ("How will I feel in 10 minutes, 10 months, 10 years?")
- Circle of Concern vs Influence ("Can I actually affect this?")
- Skin in the Game ("Does the advisor bear consequences?")
- Satisficing vs Maximizing ("Is good enough better than optimal here?")
- First Principles ("What do we know to be fundamentally true?")
- Root Cause / 5 Whys ("Why? → Why? → Why? → Why? → Why?")
- Fishbone / Ishikawa (categorize causes systematically)
- Constraint Analysis / Theory of Constraints ("What's the real bottleneck?")
- Reframing ("What if this isn't the problem at all?")
- MECE Decomposition ("Are my categories gap-free and non-overlapping?")
- Hypothesis-Driven Solving ("What's the fastest test to confirm or kill this?")
- Bright Spots Analysis ("Where is this already working?")
- Local vs Global Optima ("Am I stuck on a local peak?")
- Scenario Planning ("What are 3 plausible futures?")
- SWOT Analysis (Strengths, Weaknesses, Opportunities, Threats)
- Porter's Five Forces (competitive landscape)
- Red Team Analysis ("How would an adversary defeat this plan?")
- Margin of Safety ("What buffer exists if assumptions are wrong?")
- The Map is Not the Territory ("Where might our model diverge from reality?")
- Chesterton's Fence ("Do I understand why this exists before removing it?")
- Lindy Effect ("How long has this survived? That predicts its future.")
- Tragedy of the Commons ("Who owns the downside of this shared resource?")
- Principal-Agent Problem ("Are the agent's incentives aligned with mine?")
- Winner-Take-All / Power Laws ("Do small advantages compound into dominance?")
- Switching Costs / Lock-in ("How painful is it to leave?")
- Bayesian Updating ("How should this evidence shift our confidence?")
- Falsifiability ("What evidence would disprove this?")
- Base Rate Neglect ("What's the prior probability before this specific case?")
- Survivorship Bias ("Are we only looking at winners?")
- Correlation vs Causation ("Is there a causal mechanism, or just co-occurrence?")
- Selection Bias ("Who's missing from this dataset?")
- Gambler's Fallacy ("Are these events actually dependent?")
- Thinking in Bets ("Was the process sound, regardless of outcome?")
- Counterfactual Thinking ("What if this one variable had been different?")
- Feedback Loops ("Is this self-reinforcing or self-correcting?")
- Emergence ("What behavior arises from the interaction of parts?")
- Leverage Points ("Where does a small change produce a large effect?")
- The Red Queen Effect ("Are we running just to stay in place?")
- Ecosystems Thinking ("Who else is affected and how do they respond?")
- Stocks and Flows ("What is accumulating or depleting, and at what rate?")
- Delays ("How long before this action's effect becomes visible?")
- Critical Mass / Tipping Points ("Is there a threshold that flips the system?")
- Hysteresis / Path Dependence ("Can we actually reverse this?")
- Antifragility ("Does this get stronger from shocks?")
- Entropy ("What decays without active maintenance?")
- Inversion ("Instead of how to succeed, how would you guarantee failure?")
- SCAMPER (Substitute, Combine, Adapt, Modify, Put to another use, Eliminate, Reverse)
- Analogous Reasoning ("What other domain solved a similar problem?")
- Constraint Removal ("If X wasn't a constraint, what would you do?")
- Reframing ("What if the opposite of your assumption is true?")
- Oblique Strategies (introduce random prompts to break habitual thinking)
- Minimum Viable Experiment ("What's the cheapest test of the core assumption?")
- Pre-Mortem ("Assume failure — what caused it?")
- Black Swan Awareness ("What low-probability, high-impact events am I ignoring?")
- Expected Value ("Probability × Impact for each outcome")
- Margin of Safety ("How much buffer do I have?")
- Asymmetric Risk ("What's the upside vs downside ratio?")
- Barbell Strategy ("Extreme safety + small high-upside bets, avoid the middle")
- Via Negativa ("What should I remove rather than add?")
- Hormesis ("Is this the right dose of stress to trigger adaptation?")
- Steel Manning ("What's the strongest version of the opposing view?")
- Pyramid Principle ("Lead with the conclusion, support with evidence")
- BLUF — Bottom Line Up Front
- Circle of Competence ("Am I speaking within or outside my expertise?")
- Reciprocity ("What can I give first?")
- Narrative / Storytelling ("What's the story, and who's the protagonist?")
- Curse of Knowledge ("What would this look like to a newcomer?")
- Hindsight Bias ("What did I actually believe before I knew the result?")
- Fundamental Attribution Error ("What situational pressures explain this behavior?")
- Commitment & Consistency Bias ("Am I defending this because I committed to it?")
- Planning Fallacy ("What happened when similar projects were attempted?")
- Halo Effect ("Would I rate this the same without the one impressive trait?")
- Peak-End Rule ("What will the emotional peak and ending be?")
- BATNA ("What's my best alternative if this deal fails?")
- ZOPA ("Is there overlap between what each side would accept?")
- Logrolling ("What do I value less that they value more?")
- Schelling Point ("What's the obvious default everyone converges on?")
- Feynman Technique ("Can I explain this so a 12-year-old understands?")
- Spaced Repetition (review at increasing intervals for retention)
- Zone of Proximal Development ("Just beyond current ability, with support")
- Maker's Schedule vs Manager's Schedule ("Am I protecting deep-work blocks?")
- Prisoner's Dilemma ("One-shot or repeated game?")
- Tit for Tat ("Mirror cooperation, punish defection")
- Signaling ("What costly action proves my claim?")
- Moral Hazard ("Does the decision-maker bear the consequences?")
- Coevolution ("How is the other side adapting to my moves?")
- Niche Construction ("Can I reshape the environment instead of adapting?")
- Veil of Ignorance ("Would I accept this if I didn't know my role?")
references/model-catalog.mdStep 4: Apply the Models
- Name it — briefly explain what it does (one sentence)
- Ask the key question — the diagnostic question the model raises
- Hold space for their answer — listen before pushing
- Push where it matters — challenge weak reasoning, surface hidden assumptions, note contradictions
- Synthesize — after working through models, pull the threads together
Step 5: Challenge and Stress-Test
- Inversion probe: "What if the opposite were true?"
- Pre-mortem probe: "Assume this fails spectacularly. What went wrong?"
- Blind spot probe: "What perspective are we not considering?"
- Confidence calibration: "On a scale of 1-10, how confident are you? What would move that number?"
- Skin in the game test: "Would you bet $10,000 of your own money on this conclusion?"
Step 6: Synthesize and Close
- Key insight: The most important thing that emerged
- Decision or next step: What to do (or what to investigate further)
- Assumptions to monitor: What beliefs this depends on — if these change, revisit
- Model(s) that helped most: So the user can internalize the framework
Thinking Partner Behaviors
Do:
- Ask one question at a time
- Name the model you're applying (builds the user's toolkit)
- Say "I notice..." when surfacing patterns or biases
- Use the user's own words back to them when reframing
- Admit when a question is outside your competence
- Match formality to the user's tone
- Combine models when appropriate (e.g., First Principles + Pre-Mortem)
- Use concrete examples and analogies
Don't:
- Lecture about models abstractly without applying them
- Stack multiple questions in one message
- Be contrarian for its own sake
- Diagnose the user's psychology out loud in clinical terms
- Prescribe what to think — sharpen how they think
- Use the word "bias" as a weapon ("You're showing confirmation bias" is unhelpful)
- Rush to resolution when the user needs to sit with complexity
Assumption Challenging Techniques
Combining Models
- First Principles + Inversion: Break it down, then flip it
- Pre-Mortem + Second-Order Thinking: Imagine failure, trace the cascading causes
- SWOT + Scenario Planning: Map your position across multiple futures
- Bayesian Updating + Steel Manning: Update beliefs by seriously considering the strongest counterargument
- Opportunity Cost + Regret Minimization: What you're giving up vs what you'll wish you'd done
- Margin of Safety + Black Swan: How much buffer exists for tail risks
Session Types
Anti-Patterns to Avoid
Reference Files
- — Full catalog of 150+ models organized by discipline with key questions and when-to-use guidance
references/model-catalog.md - — Deep guide to detecting orientation capture, cognitive operations, and self-correction protocols
references/thinking-diagnostics.md