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-oodagit 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-ooda)<a href="https://agentmods.dev/skills/tjboudreaux/cc-thinking-skills/thinking-ooda"><img src="https://agentmods.dev/badge/skills/tjboudreaux/cc-thinking-skills/thinking-ooda/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-ooda"><img src="https://agentmods.dev/badge/skills/tjboudreaux/cc-thinking-skills/thinking-ooda.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 | $0.00041 | $0.00681 |
| Opus 5 | $0.00020 | $0.00341 |
| Sonnet 5 | $0.00008 | $0.00136 |
| Haiku 4.5 | $0.00004 | $0.00068 |
Grade A, and why
thinking-ooda 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 11d 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 — 47 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OODA Loop
Core rule: For reversible moves under time pressure, act on ~70% confidence, then immediately re-observe. Cycle faster than the situation compounds; a late perfect plan loses to a fast loop.
When to Use
- Incident response, outage, or ongoing degradation where state is still moving.
- Debugging a moving target (intermittent failure, live traffic shift).
- Any time-bounded decision where waiting for full certainty costs more than a reversible action.
When NOT to Use
- The situation is static and you have time — deliberate analysis or a hypothesis differential wins.
- The next action is irreversible or high blast-radius — raise the evidence bar; 70% is not enough.
- You can cheaply localize the cause (read the failing diff, log, or metric) — test that hypothesis directly instead of looping in the dark.
- There is no time pressure and no changing environment — OODA adds churn without value.
Procedure
- Observe (time-boxed): gather the cheapest high-signal state now — metrics, logs, alerts, recent deploys/config, and feedback from the last action. Cap the window; do not collect forever.
- Orient: match observations to a pattern and form ≥2 candidate explanations. Update or discard the mental model when data contradicts it; refuse single-hypothesis lock.
- Decide: pick one reversible action that tests the leading hypothesis. State confidence (~70% threshold for reversible moves), the predicted effect, the observation you will check next, and a time box for that check.
- Act: execute once, decisively, with a known rollback or degrade path.
- Re-observe immediately: compare outcome to prediction within the time box; feed the result into the next Observe. Loop until stable or until the next move is no longer reversible enough for this skill.
- Stop condition: exit the loop when the system is stable, the remaining work is static analysis, or the next step requires irreversible commitment — then switch method.
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.
- 11d ago First seen · 47 lines · 41 tokens per session scan A b5120a4734a5
thinking-ooda is a skill published in the GitHub repository tjboudreaux/cc-thinking-skills (1,300 stars, last pushed 1mo ago), licensed MIT. It adds 41 tokens to every session and 681 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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