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-systemsgit 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-systems)<a href="https://agentmods.dev/skills/tjboudreaux/cc-thinking-skills/thinking-systems"><img src="https://agentmods.dev/badge/skills/tjboudreaux/cc-thinking-skills/thinking-systems/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-systems"><img src="https://agentmods.dev/badge/skills/tjboudreaux/cc-thinking-skills/thinking-systems.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 | $0.00039 | $0.00971 |
| Opus 5 | $0.00019 | $0.00485 |
| Sonnet 5 | $0.00008 | $0.00194 |
| Haiku 4.5 | $0.00004 | $0.00097 |
Grade A, and why
thinking-systems 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 10d 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 — 70 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Systems Mapping and Leverage
Treat the problem as structure and interaction, not isolated parts. Map boundary, stocks/flows, loops/delays, and recurring patterns; intervene at the highest feasible leverage after a side-effect check.
When to Use
- Symptom spans services/components; single-stack fixes fail or bounce.
- A change in one place breaks another; behavior is emergent.
- Problem recurs despite local fixes (structure, not only symptom).
- Need to rank interventions when parameter/buffer tweaks do not stick.
When NOT to Use
- Single-component linear bug with clear stack/diff—trace and fix.
- Throughput limited by one obvious stage—use theory-of-constraints.
- Decision is a consequence chain of one proposed action—use second-order.
- Approach selection (plan vs probe vs stabilize)—use cynefin first.
Procedure
- Bound the system. Name purpose, actors, boundary, and in/out flows. Exclude noise outside the decision horizon; include any path that can feed the symptom.
- Map stocks and flows. List accumulating stocks (queue depth, debt, cache size, WIP) and the rates that fill/drain them. Note what changes slowly even when flows jump.
- Find feedback and delays. For each candidate loop: classify reinforcing (amplifies) vs balancing (resists); mark same-direction (+) vs opposite (-) links; name delays (TTL, deploy lag, metric lag, ramp-up). Even count of opposite links → reinforcing; odd → balancing. Long delay + strong correction → overshoot risk.
- Match recurring structure when problems return. Check only if recurrence or policy resistance is present; do not force a pattern:
- Fixes That Fail — quick fix, delayed worse side effect
- Shifting the Burden — workaround starves fundamental fix
- Limits to Growth — growth hits a balancing constraint
- Tragedy of the Commons — local optima deplete a shared stock
- Escalation — mutual reaction spiral
- Success to the Successful — advantage compounds via allocation
- Growth and Underinvestment — capacity lags demand until crisis If none fits after a genuine pass, keep the from-scratch map.
- Trace symptom to structure. Walk upstream along flows and loops; separate proximate symptom from structural driver (interaction, delay, wrong goal, missing info).
- Rank interventions by leverage, then side effects. Prefer higher feasible class: goals/paradigm → rules/information → loop structure (gain, balancing add, delay shorten) → stock/flow topology → buffers/parameters. For each candidate: feasibility, blast radius, delayed reversal risk. Prefer moves that cut harmful reinforcing gain or strengthen needed balancing loops without creating a new commons/escalation.
- Stop. Commit highest feasible intervention plus watch signals for loop/delay response. Re-map only if the structure changes or the intervention fails its watch.
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.
- 10d ago First seen · 70 lines · 39 tokens per session scan A 0c8b5259eded
thinking-systems is a skill published in the GitHub repository tjboudreaux/cc-thinking-skills (1,293 stars, last pushed 1mo ago), licensed MIT. It adds 39 tokens to every session and 971 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.
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