Claude Code Thinking Skills is a catalogue of 28 portable skills that give coding agents structured procedures for reasoning about decisions, diagnosis, risk, strategy, and related problems. It is intended for Claude Code, GitHub Copilot, Codex, Cursor, and other tools that support Agent Skills.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add tjboudreaux/cc-thinking-skills --skill thinking-kepner-tregoegit clone --depth 1 https://github.com/tjboudreaux/cc-thinking-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/tjboudreaux/cc-thinking-skills/thinking-kepner-tregoe)<a href="https://agentmods.dev/skills/tjboudreaux/cc-thinking-skills/thinking-kepner-tregoe"><img src="https://agentmods.dev/badge/skills/tjboudreaux/cc-thinking-skills/thinking-kepner-tregoe/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/tjboudreaux/cc-thinking-skills/thinking-kepner-tregoe"><img src="https://agentmods.dev/badge/skills/tjboudreaux/cc-thinking-skills/thinking-kepner-tregoe.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00037 | $0.00736 |
| Opus 5 | $0.00018 | $0.00368 |
| Sonnet 5 | $0.00007 | $0.00147 |
| Haiku 4.5 | $0.00004 | $0.00074 |
Grade A, and why
thinking-kepner-tregoe scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 13d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 45 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Kepner-Tregoe Analysis
Core rule: Diagnose deviations by testing causes against both IS and IS-NOT. Compare consequential choices by screening MUSTs, weighting WANTs, and exposing adverse consequences before selecting.
When to Use
- A defect affects some objects, places, times, or cohorts but not comparable others.
- Several candidate causes remain and the contrast boundary can discriminate them.
- A consequential option choice has explicit non-negotiables, competing objectives, and risks that should be compared consistently.
When NOT to Use
- A uniform failure has no meaningful IS-NOT contrast, or the cause is already confirmed.
- One cheap observation settles the cause or one option plainly dominates every requirement.
- The criteria cannot be made operational; clarify them before assigning weights.
- The task is forward failure discovery for a planned change rather than diagnosis or option selection.
Procedure
- Choose the mode. Use Problem Analysis for a deviation from expected behavior; use Decision Analysis for a choice among options. State the target and do not mix scores with causal evidence.
- Frame the target. For a deviation, record object, defect, location, time, extent, and impact. For a choice, state the decision, alternatives, constraints, and deadline.
- Problem Analysis — build IS/IS-NOT. For WHAT, WHERE, WHEN, and EXTENT, record IS, closest comparable IS-NOT, and the distinction unique to the IS side. List changes near the first occurrence.
- Problem Analysis — difference-test causes. Generate candidates from distinctions and changes. A candidate survives only if it explains both IS and IS-NOT. Run the cheapest discriminating check; stop when one verified cause explains the full boundary.
- Decision Analysis — screen and score. Define pass/fail MUSTs and weighted WANTs (1–10 importance) before scoring. Eliminate options that fail any MUST; score survivors against each WANT and calculate weighted totals using the same scale.
- Decision Analysis — test downside and sensitivity. For leading options, list adverse consequences with probability × impact and identify assumptions or weight changes that would reverse the ranking. Do not let a high total conceal a ruinous failure mode.
- Decide or expose the gap. Return the verified cause or highest-ranked acceptable option, the evidence/score behind it, residual risk, and next verification. If no cause verifies or no option passes MUSTs, return open/none rather than force a winner.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 13d ago First seen · 45 lines · 37 tokens per session scan A 0e109e099804
thinking-kepner-tregoe is a skill published in the GitHub repository tjboudreaux/cc-thinking-skills (1,306 stars, last pushed 1mo ago), licensed MIT. It adds 37 tokens to every session and 736 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
performance-profiling
Guide performance profiling with Instruments, diagnose hangs, memory issues, slow launches, and energy drain. Use when reviewing app performance or investigating specific bottlenecks.
swiftui-debugging
Diagnose SwiftUI performance issues including unnecessary re-renders, view identity problems, and slow body evaluations. Use when SwiftUI views are slow, janky, or re-rendering too often.
debug-menu
Generates a developer debug menu with feature flag toggles, environment switching, network log viewer, cache clearing, crash trigger, and diagnostic info export. Only included in DEBUG builds. Use when user wants a debug panel, dev tools menu, or shake-to-debug functionality.
error-monitoring
Generates protocol-based error/crash monitoring with swappable providers (Sentry, Crashlytics). Use when user wants to add crash reporting, error tracking, or production monitoring.
logging-setup
Generates structured logging infrastructure using os.log/Logger to replace print() statements. Use when user wants to add proper logging, replace print statements, or set up app logging.
dead-code-detector
Detect unused/unreachable code in polyglot codebases (Python, TypeScript, Rust). TRIGGERS - dead code, unused functions, unused imports.