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-theory-of-constraintsgit 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-theory-of-constraints)<a href="https://agentmods.dev/skills/tjboudreaux/cc-thinking-skills/thinking-theory-of-constraints"><img src="https://agentmods.dev/badge/skills/tjboudreaux/cc-thinking-skills/thinking-theory-of-constraints/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-theory-of-constraints"><img src="https://agentmods.dev/badge/skills/tjboudreaux/cc-thinking-skills/thinking-theory-of-constraints.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 | $0.00744 |
| Opus 5 | $0.00018 | $0.00372 |
| Sonnet 5 | $0.00007 | $0.00149 |
| Haiku 4.5 | $0.00004 | $0.00074 |
Grade A, and why
thinking-theory-of-constraints 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 12d 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 — 56 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Theory of Constraints
A throughput-limited system has one binding constraint. Improve only that constraint; local optimization of non-constraints wastes effort and often grows WIP.
When to Use
- Latency or throughput goal where one stage dominates time or rate.
- Work piles up before one stage; downstream idles.
- Adding capacity/workers elsewhere does not raise end-to-end output.
- Need ordered plan: exploit cheaply before spending to elevate.
When NOT to Use
- Load is spread; no stage dominates—use systems for interactions.
- Problem is correctness/fault, not flow rate—debug the fault.
- Bottleneck hops every run due to coupling/contention without a stable stage—systems or concurrency design, not five focusing steps.
- Constraint already known and a cheap fix is ready—apply it without ceremony.
Procedure
- Define the flow and goal. Name the unit of work (request, job, PR, record) and the metric that matters (end-to-end rate or latency).
- Identify the constraint with evidence. Compare stages on utilization, queue/wait, and throughput. Constraint signals: near-100% use, longest queue, lowest stage rate, work piles here, more input does not raise system output. Prefer measured rates over opinions. If two candidates tie, pick the one whose improvement would raise system throughput first.
- Exploit (no major spend). Maximize constraint output: cut idle, drop nonessential work on the constraint, reduce rework/setup, protect its time, improve quality at the constraint so output is not wasted. Estimate gain before spending.
- Subordinate non-constraints. Pace upstream to constraint rate; do not flood WIP. Make other stages serve the constraint (readiness, clarity, immediate pull). Reject local utilization targets that grow queues before the constraint.
- Elevate only if still short. After exploit is maxed, invest to raise constraint capacity (people, tooling, sharding, parallel path). Choose cheapest adequate elevation.
- Recheck (prevent inertia). After elevation or large exploit, remeasure all stages—the constraint often moves. Return to step 2. Do not keep optimizing the old constraint.
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.
- 12d ago First seen · 56 lines · 37 tokens per session scan A 0a5c64afacbd
thinking-theory-of-constraints 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 744 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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