28 Mental Models and Critical-Thinking Frameworks for Claude Code, GitHub Copilot, Codex, Cursor, and other Agent Skills-compatible tools
Claude Code Thinking Skills is a portable Agent Skills catalog of 28 mental-model and critical-thinking frameworks for decisions, debugging, systems, risk, and strategy. It originated for Claude Code and now works across GitHub Copilot, Codex, Cursor, and other compatible agents. Each skill packages a proven thinking framework — from first-principles reasoning to the theory of constraints — into a skill an agent can invoke by name, and the whole collection is backed by a transparent, replication-gated evaluation pipeline.
| What it is | A portable Agent Skills library of 28 mental-model and critical-thinking frameworks. |
| Who it's for | Engineers, founders, and analysts who want compatible AI agents to reason with structured frameworks instead of ad-hoc heuristics. |
| How to start | Run npx skills add tjboudreaux/cc-thinking-skills, 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
- Verified distribution
- 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 evaluated the 39-skill legacy catalog. 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.
- 28 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, Agent Skills Portable — First-class Claude Code marketplace support plus the shared Agent Skills format used by GitHub Copilot, Codex, Cursor, and other compatible tools.
- Quality Scripts — Tooling to validate, score, and improve skill quality.
- Zero Configuration — Install through a supported client and invoke skills by name; no framework setup required.
Choose the service or client you already use. Directory-only surfaces point back to the same canonical release; they do not maintain separate copies.
Use the skills.sh CLI to discover the catalog and choose skills or target agents interactively:
npx skills add tjboudreaux/cc-thinking-skillsFor a non-interactive all-skill, all-agent installation:
npx skills add tjboudreaux/cc-thinking-skills --allInstall all 28 skills from the immutable release:
gh skill install tjboudreaux/cc-thinking-skills --all --pin v1.0.0The pin makes the source reproducible. Without --pin, GitHub Skills resolves the latest release before falling back to default-branch HEAD.
ClawHub publishes each skill separately. Install the recommended model router with OpenClaw:
openclaw skills install @tjboudreaux/thinking-model-routerOr use the standalone ClawHub CLI:
npx clawhub install @tjboudreaux/thinking-model-routerBrowse the full 28-skill ClawHub catalog and replace thinking-model-router with any listed skill slug.
Claude Code users can install the native plugin wrapper:
# Add the marketplace
/plugin marketplace add tjboudreaux/cc-thinking-skills
# Install the plugin
/plugin install thinking-skills@thinking-skills-marketplaceUse the pinned GitHub Skills command above for an installed catalog that Copilot can consume. The Awesome Copilot submission has passed automated intake but is still awaiting maintainer review, so it does not yet have a marketplace install command.
To load the released plugin wrapper directly in Copilot CLI:
git clone --branch v1.0.0 --depth 1 https://github.com/tjboudreaux/cc-thinking-skills.git
copilot --plugin-dir ./cc-thinking-skillsSkillsMP is a discovery directory. From an individual skill page, install that skill through the shared Skills CLI:
npx skills add https://github.com/tjboudreaux/cc-thinking-skills --skill thinking-model-routerReplace thinking-model-router with the skill slug you selected, or omit --skill to choose interactively.
The officialskills.sh submission is still under review. There is no officialskills.sh install command until that listing is accepted; use skills.sh, GitHub Skills, ClawHub, or the source-copy fallback in the meantime.
Clone the repository once:
git clone https://github.com/tjboudreaux/cc-thinking-skills.gitFor agents using the shared project-level Agent Skills location:
mkdir -p /path/to/project/.agents/skills
cp -R cc-thinking-skills/skills/* /path/to/project/.agents/skills/For Claude Code, copy to the global or project-specific Claude skills directory:
mkdir -p ~/.claude/skills /path/to/project/.claude/skills
cp -R cc-thinking-skills/skills/* ~/.claude/skills/
# Or:
cp -R cc-thinking-skills/skills/* /path/to/project/.claude/skills/Other clients should use the skills directory documented by that client.
For Claude Code testing or development:
claude --plugin-dir ./cc-thinking-skillsOnce installed, ask your compatible agent to invoke a skill by name, or use the client's documented skill command. 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 probabilistic reasoning to evaluate this hypothesis
> Use the theory of constraints to find our bottleneck
| Surface | Route | Status |
|---|---|---|
| skills.sh | Listing · refresh issue | submitted |
| GitHub Skills / Awesome Copilot | v1.0.0 release · Awesome Copilot intake | verified (direct install); submitted (Awesome Copilot) |
| SkillsMP | Repository listing | sync pending |
| ClawHub | Publisher catalog · v1.0.0 listing | verified |
| officialskills.sh | officialskills.sh · upstream PR | submitted |
All 28 shipped 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-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-opportunity-cost |
Evaluate choices by what you give up | Resource allocation, prioritization |
| Skill | Description | Best For |
|---|---|---|
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-ooda |
Rapid decision-making for dynamic situations | Incident response, competitive scenarios |
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-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-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-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 evidence base: Historical coverage is heterogeneous and remains provisional. The corrected
portfolio-v1gate made zero model calls because power, dataset, and judge-calibration requirements were not met. - The headline result: Zero skills currently hold a robust, replicated ELEVATE verdict. All 28 shipped skills are manual-only; none is proven to improve model accuracy.
- The closest historical candidate:
thinking-scientific-methodrecorded a provisional +4.0pp fault-localization lift in its larger-N July artifact. Although its recomputed McNemar result was significant, the effect is below the predeclared +5pp utility margin and the study has scoring, control, denominator, and raw-archive defects. It is directional evidence only, not ELEVATE. - What that means for you: Treat these skills as structured-reasoning scaffolds, not guaranteed accuracy improvements. The audit preserves the useful frameworks while keeping unsupported performance claims out of the product.
Read the evidence yourself:
- Decision-ready audit — catalog dispositions, study citations, and explicit evidence gaps.
- Canonical evidence registry — machine-readable authority for counts, claims, and product dispositions.
The shipped catalog now contains 28 skills. Eleven unsupported or overlapping skills were removed at the evidence-backed cutover; their unique mechanisms were absorbed into surviving skills and their historical evidence remains preserved.
This collection includes a small, outcome-focused harness:
The evals/ directory contains the current harness:
- Structural validation for frontmatter, catalog metadata, and format checks
- Routing evals for skill discoverability and false-positive control
- Generic objective evals with exact, boolean, abstention, numeric, probability, and strict file-localization scorers
- Generic blind pairwise evals for rubric-based comparisons
- Evidence registry checks that fail closed when provenance or confirmatory gates are incomplete
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
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
Estimate uncertainty, update priors with evidence, and expose assumptions and calibration.
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 is a portable catalog of 28 reusable mental-model and critical-thinking frameworks in the Agent Skills format. Each one gives a compatible AI agent a structured method — such as first-principles reasoning, probabilistic updating, or the theory of constraints — for analyzing a specific kind of problem. You can invoke them by name in Claude Code, GitHub Copilot, Codex, Cursor, and other Agent Skills-compatible tools.
Use npx skills add tjboudreaux/cc-thinking-skills for interactive installation, or add --all for a non-interactive all-skill, all-agent install. GitHub Skills users can run gh skill install tjboudreaux/cc-thinking-skills --all --pin v1.0.0; an unpinned install resolves the latest release before default-branch HEAD. Claude Code users can instead use the native plugin marketplace commands above. The clone/copy fallback supports .agents/skills/, .claude/skills/, or another client-documented skills directory.
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 28. 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 compatible agents 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.jsagent-skills skills-sh github-copilot codex cursor claude-code claude anthropic ai skills claude-code-skills mental-models critical-thinking decision-making problem-solving ai-reasoning systems-thinking first-principles probabilistic-reasoning uncertainty-estimation cognitive-bias strategic-thinking frameworks triz ooda pre-mortem socratic-method theory-of-constraints cynefin jobs-to-be-done red-team
- Agent Skills specification
- 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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