analogical-thinking
Analogical Thinking
Core principle: Most genuinely hard problems have structural analogues elsewhere — often solved long ago under a different name. Recognize the shape of the problem beneath surface details, then transfer the solution structure.
The ctx harness as OS memory management. Blackboard pattern from speech recognition (1977) re-emerging in multi-agent AI. TCP congestion control inspiring rate-limiting. Evolution as search algorithm.
The risk: false analogies — surface similarity masking structural difference. This skill is as much about knowing when an analogy breaks as when it applies.
Core Process
Step 1: Abstract the Problem Structure
Strip domain vocabulary:
- What needs to coordinate with what?
- What needs to be stored, retrieved, prioritized, transformed, routed?
- What's the flow? What are the constraints?
- What failure modes are you preventing?
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Apply causal inference whenever the user is interpreting metrics, debugging system behavior, reading A/B test results, or trying to understand whether an observed change was caused by an action or by something else. Triggers on phrases like "X caused Y", "since we deployed this, metrics changed", "the A/B test showed a lift", "why did this metric move?", "is this correlation or causation?", "we changed X and Y improved", "how do we know this worked?", "the data shows…", or any situation where conclusions are being drawn from observational data. Also trigger before any decision based on metric interpretation — confusing correlation with causation leads to interventions that don't work and misattribution of credit. Never assume causation without applying this skill.
31probabilistic-thinking
Apply probabilistic and Bayesian thinking whenever the user needs to reason under uncertainty, compare risks, prioritize between options, update beliefs based on new evidence, or make decisions without complete information. Triggers on phrases like "what are the odds?", "how likely is this?", "should I be worried about X?", "which risk is bigger?", "does this data change anything?", "is this a signal or noise?", "what's the probability?", "how confident are we?", or any situation where decisions are being made based on incomplete or ambiguous evidence. Also trigger when someone is treating uncertain outcomes as certainties, or when probability language is being used loosely ("probably", "unlikely", "very likely") without quantification. Don't leave uncertainty unexamined.
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Apply inversion and pre-mortem thinking whenever the user asks to evaluate a plan, strategy, architecture, feature, or decision before execution — or when they want to stress-test something that already exists. Triggers on phrases like "is this a good idea?", "what could go wrong?", "review this plan", "should we do this?", "are we missing anything?", "stress-test this", "what are the risks?", or any request to validate a decision or design. Use this skill proactively — if the user is about to commit to something, this skill should be consulted even if they don't ask for it explicitly.
24cognitive-bias-detection
Apply cognitive bias detection whenever the user (or Claude itself) is making an evaluation, recommendation, or decision that could be silently distorted by systematic thinking errors. Triggers on phrases like "I'm pretty sure", "obviously", "everyone agrees", "we already invested so much", "this has always worked", "just one more try", "I knew it", "the data confirms what we thought", "we can't go back now", or when analysis feels suspiciously aligned with what someone wanted to hear. Also trigger proactively when evaluating high-stakes decisions, plans with significant sunk costs, or conclusions that conveniently support the evaluator's existing position. The goal is not to paralyze — it's to flag where reasoning may be compromised so it can be corrected.
24first-principles-thinking
Apply first principles thinking whenever the user is questioning whether a design, strategy, or solution is fundamentally right — not just well-executed. Triggers on phrases like "are we solving the right problem?", "why do we do it this way?", "is this the best approach?", "everyone does X but should we?", "we've always done it this way", "challenge our assumptions", "start from scratch", "is there a better way?", or when the user seems to be iterating on a flawed premise rather than questioning the premise itself. Also trigger when a proposed solution feels like an incremental improvement on something that may be fundamentally broken. Don't optimize a flawed foundation — question it first.
22scenario-planning
Apply scenario planning whenever the user is making long-term decisions, building roadmaps, evaluating strategies, or operating in an environment with significant uncertainty about how the future will unfold. Triggers on phrases like "what should our roadmap look like?", "how do we plan for the future?", "what if things change?", "we're not sure which direction the market will go", "how do we make this strategy resilient?", "what's our plan B?", "what are the different futures we could face?", or when a plan assumes a single future state. Also trigger when someone is over-committed to one expected outcome and hasn't stress-tested the strategy against alternative futures. Don't plan for one future — plan for multiple.
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