39 Mental Models and Critical-Thinking Frameworks for Claude Code
Claude Code Thinking Skills is a collection of 39 mental-model and critical-thinking frameworks for Claude Code that give Anthropic's AI coding agent structured ways to reason about decisions, debugging, systems, risk, and strategy. Each skill packages a proven thinking framework — from first-principles reasoning to the theory of constraints — into a Claude Code skill you can invoke by name, and the whole collection is backed by a transparent, replication-gated evaluation pipeline.
| What it is | A library of 39 mental-model and critical-thinking skills for Claude Code. |
| Who it's for | Engineers, founders, and analysts who want Claude Code to reason with structured frameworks instead of ad-hoc heuristics. |
| How to start | Install via the plugin marketplace, then invoke thinking-model-router to be routed to the right skill. |
| License | MIT — free to use, modify, and distribute. |
| Evidence | Every skill ran through a replication-gated Elevate-or-Kill evaluation pipeline. The honest headline: zero skills currently hold a robust, replicated ELEVATE verdict — and we publish that result rather than hide it. |
| Entry point | thinking-model-router → START HERE |
- Why This Project Is Different
- Features
- Quick Start
- Available Skills
- How the Skills Were Evaluated
- Quality Assurance Tools
- Detailed Skill Descriptions
- FAQ
- Contributing
- Keywords
- Related Resources
- License
- Author
Most "AI prompt pack" repositories claim their content makes models smarter and never test the claim. This project did the opposite: it built an objective, length-controlled, replication-gated evaluation harness and ran all 39 skills through it. The result is documented openly, including the inconvenient finding that no skill yet meets the bar for a proven, replicated accuracy gain.
That rigor is the point. These skills are useful structured-reasoning scaffolds grounded in established frameworks, and the evaluation methodology is honest enough to tell you exactly how strong the evidence is. Transparency over hype is the standard here.
- 39 Thinking Frameworks — A curated library of mental models for decision-making, debugging, and strategy.
- Eval-Backed and Honest — Built and tested with a rigorous, replication-gated evaluation pipeline; see the Elevate-or-Kill Scorecard.
- Battle-Tested Foundations — Grounded in frameworks from cognitive science, systems thinking, and strategic analysis (Munger, Meadows, Kahneman, Goldratt, Altshuller/TRIZ, Boyd/OODA).
- Claude Code Native — Designed specifically for Claude Code's skill system and invocation model.
- Quality Scripts — Tooling to validate, score, and improve skill quality.
- Zero Configuration — Install and invoke skills by name; no setup required.
Install directly in Claude Code using the plugin system:
# Add the marketplace
/plugin marketplace add tjboudreaux/cc-thinking-skills
# Install the plugin
/plugin install thinking-skills@thinking-skills-marketplaceClone and copy skills directly:
# Clone the repository
git clone https://github.com/tjboudreaux/cc-thinking-skills.git
# Copy skills to your global Claude Code config
cp -r cc-thinking-skills/skills/* ~/.claude/skills/
# Or copy to a specific project
cp -r cc-thinking-skills/skills/* /path/to/your/project/.claude/skills/For testing or development:
claude --plugin-dir ./cc-thinking-skillsOnce installed, invoke any skill by name in Claude Code. If you're not sure which framework fits, start with thinking-model-router and let it route you:
> Use the thinking-model-router to pick the right framework for this problem
> Use first-principles thinking to analyze this architecture decision
> Apply the pre-mortem framework to this project plan
> Help me use Bayesian reasoning to evaluate this hypothesis
> Use the theory of constraints to find our bottleneck
All 39 skills, grouped by domain. The meta-skill thinking-model-router is the recommended entry point.
| Skill | Description | Best For |
|---|---|---|
thinking-first-principles |
Break problems into fundamental truths | Innovation, challenging assumptions |
thinking-second-order |
Think beyond immediate consequences | Strategic decisions, policy changes |
thinking-inversion |
Approach problems by identifying paths to failure | Risk identification, planning |
thinking-pre-mortem |
Imagine failure and work backward | Project kickoffs, risk assessment |
thinking-kepner-tregoe |
Systematic rational process for complex analysis | High-stakes decisions, root cause analysis |
thinking-reversibility |
Classify decisions by reversibility (Type 1/2) | Commitment sizing, risk assessment |
thinking-regret-minimization |
Project to future self to test decisions | Career choices, major life decisions |
thinking-opportunity-cost |
Evaluate choices by what you give up | Resource allocation, prioritization |
| Skill | Description | Best For |
|---|---|---|
thinking-bayesian |
Update beliefs based on evidence | Probability estimation, uncertainty |
thinking-debiasing |
Identify and counteract cognitive biases | Major decisions, high stakes |
thinking-dual-process |
Recognize when to trust intuition vs. analysis | Speed vs. accuracy tradeoffs |
thinking-bounded-rationality |
Make good-enough decisions under constraints | Time pressure, satisficing |
thinking-socratic |
Systematic questioning framework | Requirements, debugging, coaching |
thinking-probabilistic |
Calibrated probability estimation | Forecasting, uncertainty quantification |
thinking-steel-manning |
Argue the strongest opposing position | Debate, decision validation |
| Skill | Description | Best For |
|---|---|---|
thinking-systems |
Analyze interconnected systems | Complex debugging, architecture |
thinking-feedback-loops |
Identify reinforcing and balancing loops | Growth design, organizational dynamics |
thinking-archetypes |
Recognize recurring system patterns | Organizational problems, recurring issues |
thinking-ooda |
Rapid decision-making for dynamic situations | Incident response, competitive scenarios |
thinking-leverage-points |
Find where small changes have big effects | System optimization, intervention design |
thinking-theory-of-constraints |
Identify and manage bottlenecks | Performance optimization, throughput |
thinking-cynefin |
Classify problems by complexity domain | Methodology selection, approach matching |
| Skill | Description | Best For |
|---|---|---|
thinking-occams-razor |
Prefer simpler explanations | Debugging, architecture decisions |
thinking-map-territory |
Recognize limits of mental models | Expectation mismatches, abstractions |
thinking-circle-of-competence |
Know the boundaries of expertise | Delegation, learning decisions |
thinking-triz |
Resolve technical contradictions | Engineering design, innovation |
thinking-five-whys-plus |
Enhanced root cause analysis with bias guards | Debugging, incident postmortems |
thinking-scientific-method |
Hypothesis-differential debugging | Fault localization, ambiguous symptoms |
thinking-thought-experiment |
Structured imagination for exploration | Architecture, edge cases, philosophy |
| Skill | Description | Best For |
|---|---|---|
thinking-fermi-estimation |
Order-of-magnitude calculations | Quick sizing, feasibility checks |
thinking-margin-of-safety |
Build in buffers for uncertainty | Risk management, system design |
thinking-lindy-effect |
Older things likely to last longer | Technology selection, durability |
thinking-via-negativa |
Improve by removing, not adding | Simplification, robustness |
thinking-red-team |
Attack your own plans adversarially | Security review, plan validation |
| Skill | Description | Best For |
|---|---|---|
thinking-jobs-to-be-done |
Understand the job customers hire products for | Product development, feature design |
thinking-effectuation |
Start with means, not goals | Startups, innovation, uncertainty |
| Skill | Description | Best For |
|---|---|---|
thinking-model-router |
START HERE - Route to the right model by domain | Entry point for all thinking skills |
thinking-model-selection |
Choose the right model for the problem | New problems, approach selection |
thinking-model-combination |
Combine multiple models for richer analysis | Complex problems, high-stakes decisions |
Honesty about evidence is a core feature of this project, so the evaluation results are reported plainly.
- The pipeline: All 39 skills were run through an "Elevate-or-Kill" process — a length-controlled, replication-gated evaluation that compares skill-guided runs against placebo prompts and demands that any apparent win survive an independent replication.
- The headline result: Zero skills currently hold a robust, replicated ELEVATE verdict. No skill in this collection is proven to improve Claude's accuracy.
- The closest candidate:
thinking-scientific-method(hypothesis-differential debugging). Its M5 fresh primary run scored +5.3pp (p=0.061, n=150) — directional, but it fails the p<0.05 significance gate. A separate replication was significant at +8.0pp (p=0.001). Because a significant replication cannot rescue a primary run that fails the gate, its final verdict is DIRECTIONAL-NOT-REPLICATED. A pre-registered, larger-N study is recommended as future work. - What that means for you: Treat these skills as well-grounded structured-reasoning scaffolds, not as a guaranteed accuracy boost. The frameworks are real and useful; the empirical proof of a model-accuracy lift is not yet there, and we say so.
Read the evidence yourself:
- Elevate-or-Kill Scorecard — canonical single source of truth for all 39 skills.
- Executive Synthesis — the full executive summary of the mission.
- Future Consolidation Plan — a proposed (unexecuted) plan for consolidating skills.
All 39 skills remain shipped; no directories were removed.
This collection includes scripts to maintain and improve skill quality.
The evals/ and experiments/ directories contain the current outcome-based harness:
- Structural lint for frontmatter and format checks
- Routing evals for skill discoverability and false-positive control
- Length-controlled behavioral evals using skill-vs-placebo prompts
- Objective SWE-bench localization evals for debugging skills
- SQLite dashboard for reviewing eval and experiment results
Check all skills against quality criteria:
node scripts/validate-skills.jsOutputs a report showing:
- Required sections present/missing
- Quality metrics (examples, tables, checklists)
- Overall score per skill
- Skills needing attention
Get specific improvement suggestions for a skill:
# Single skill
node scripts/enhance-skill.js thinking-first-principles
# All skills summary
node scripts/enhance-skill.jsCreate prompts for Claude to enhance skills:
node scripts/generate-improvement-prompt.js thinking-bayesianThis generates a detailed prompt you can use with Claude Code to systematically improve any skill.
Strip away assumptions to reveal fundamental truths, then rebuild solutions from basics. Championed by Elon Musk and rooted in Aristotle's philosophy.
When to use:
- Conventional approaches have failed
- You're told something is "impossible"
- Need innovation, not incremental improvement
Update beliefs systematically based on new evidence. Provides a framework for thinking about probability and uncertainty.
When to use:
- Estimating probabilities or likelihoods
- Interpreting test results or metrics
- Making decisions with incomplete information
View problems as part of interconnected wholes with feedback loops and emergent properties. Essential for debugging complex distributed systems.
When to use:
- Debugging spans multiple components
- Fix in one place breaks another
- Behavior seems emergent or unexpected
Every system has exactly one constraint limiting throughput. Optimizing anything else is wasted effort. Based on Eliyahu Goldratt's work.
When to use:
- Performance optimization
- Process improvement
- Resource allocation
- Identifying bottlenecks
Localize an ambiguous bug by enumerating falsifiable hypotheses, ranking them by likelihood x cheapness-to-check, and making the cheapest discriminating observation first. This is the most empirically scrutinized skill in the collection (final verdict: DIRECTIONAL-NOT-REPLICATED — see evaluation results).
When to use:
- A symptom could plausibly come from several files/functions/components
- You can inspect code, logs, diffs, traces, or tests now
- You need to localize the fault before applying root-cause analysis
Classify problems by the relationship between cause and effect: Clear, Complicated, Complex, or Chaotic. Each domain requires a different approach.
When to use:
- Choosing methodologies
- Understanding why approaches fail
- Crisis management
Customers don't buy products—they hire them to do jobs. Understanding the job unlocks innovation.
When to use:
- Product development
- Feature prioritization
- Understanding customer behavior
Attack your own plans before adversaries do. The best defense is knowing your weaknesses.
When to use:
- Security review
- Pre-launch preparation
- Plan stress-testing
Claude Code thinking skills are 39 reusable mental-model and critical-thinking frameworks packaged as Claude Code skills. Each one gives the AI agent a structured method — such as first-principles reasoning, Bayesian updating, or the theory of constraints — for analyzing a specific kind of problem. You invoke them by name to steer how Claude approaches decisions, debugging, and strategy.
The recommended path is the plugin marketplace: run /plugin marketplace add tjboudreaux/cc-thinking-skills, then /plugin install thinking-skills@thinking-skills-marketplace. You can also clone the repo and copy skills/* into ~/.claude/skills/ (global) or your project's .claude/skills/, or load it locally with claude --plugin-dir ./cc-thinking-skills.
Start with thinking-model-router. It's the meta-skill entry point that reads your problem and routes you to the most relevant framework, so you don't need to memorize all 39. If you already know your need — for example debugging, risk, or prioritization — you can invoke the specific skill directly.
No skill is currently proven to improve accuracy. Every skill was run through a replication-gated evaluation, and zero skills hold a robust, replicated ELEVATE verdict. The closest candidate, thinking-scientific-method, scored +5.3pp (p=0.061, n=150) on its fresh primary run — directional but short of the p<0.05 gate — with a significant +8.0pp (p=0.001) replication; because a significant replication can't rescue a primary that fails the gate, its verdict is DIRECTIONAL-NOT-REPLICATED. Treat the skills as solid structured-reasoning scaffolds, not a guaranteed accuracy boost.
thinking-model-router is a meta-skill that acts as the front door to the collection. Given a problem description, it identifies the domain (decision-making, systems, estimation, debugging, and so on) and points you to the most appropriate thinking framework. It exists so newcomers can get value without studying the entire catalog.
Yes. The frameworks draw on established work from thinkers including Charlie Munger (mental models), Donella Meadows (systems thinking), Daniel Kahneman (dual-process cognition), Eliyahu Goldratt (theory of constraints), Genrich Altshuller (TRIZ), and John Boyd (OODA loop). Beyond their source theory, the skills were also subjected to this project's own length-controlled, replication-gated evaluation pipeline, with all results published in the Elevate-or-Kill Scorecard.
Yes. The entire collection is released under the MIT License, so you're free to use, modify, and distribute it. See the LICENSE file for the full terms.
We welcome contributions! See CONTRIBUTING.md for guidelines.
- Create a new directory under
skills/with the formatthinking-{name} - Add a
SKILL.mdfile with YAML frontmatter:
---
name: thinking-your-skill-name
description: Brief description under 200 chars (used by Claude Code for skill matching)
----
Write comprehensive documentation with:
- Overview and core principle
- When to use decision flow
- Step-by-step process
- At least 2 practical examples
- Reusable template
- Verification checklist
- Key questions
-
Validate your skill:
node scripts/validate-skills.jsclaude-code claude anthropic ai skills claude-code-skills mental-models critical-thinking decision-making problem-solving ai-reasoning systems-thinking first-principles bayesian-reasoning cognitive-bias strategic-thinking frameworks triz ooda pre-mortem socratic-method theory-of-constraints cynefin jobs-to-be-done red-team fermi-estimation
- Claude Code Documentation
- Charlie Munger's Mental Models
- Thinking in Systems - Donella Meadows
- Thinking, Fast and Slow - Daniel Kahneman
- The Goal - Eliyahu Goldratt
MIT License - see LICENSE for details.
Created by TJ Boudreaux
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