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-probabilisticgit 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-probabilistic)<a href="https://agentmods.dev/skills/tjboudreaux/cc-thinking-skills/thinking-probabilistic"><img src="https://agentmods.dev/badge/skills/tjboudreaux/cc-thinking-skills/thinking-probabilistic/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-probabilistic"><img src="https://agentmods.dev/badge/skills/tjboudreaux/cc-thinking-skills/thinking-probabilistic.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 | $0.00048 | $0.01026 |
| Opus 5 | $0.00024 | $0.00513 |
| Sonnet 5 | $0.00010 | $0.00205 |
| Haiku 4.5 | $0.00005 | $0.00103 |
Grade A, and why
thinking-probabilistic 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 — 56 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Probabilistic Thinking
Core rule: State beliefs as numbers and ranges, not vibes. Anchor on a base rate, update with an explicit likelihood, and bound unknowns by factoring them — never invent false precision.
When to Use
- Timeline, effort, or outcome forecasts where the true value is uncertain.
- Risk sizing for a change, migration, deploy, or launch.
- Any moment you are about to state a confident single number you cannot actually know.
- New evidence arrives and a prior estimate should move.
When NOT to Use
- The quantity is measurable or look-up-able — measure or look it up.
- The decision is invariant across the whole plausible range — skip the estimate and act.
- There is no real reference class and you would invent a base rate — label it a guess, not a calibrated forecast.
- You only need a binary gate and already have a decisive observation — do not pad with ceremony.
Procedure
- Define a checkable claim: outcome + timeframe + unit. Prefer a falsifiable statement over vague language ("likely").
- Lock a prior and challenge it: name a reference-class base rate and at least one credible alternative path/hypothesis with its rate. Pull the prior toward the base rate unless you write a concrete reason for deviation. Then state the strongest evidence-based case that your chosen prior or range is wrong, what estimate it supports, and revise if that countercase survives. Convert vague words to numbers (e.g. "likely" ≈ 65–80%).
- Express a range, not a point: give at least one confidence interval (50% and 80% preferred). Assume overconfidence; widen intervals when the outside view is thin.
- Update prior → likelihood → posterior when evidence arrives:
- Prior odds = p / (1 − p).
- Likelihood ratio LR = P(E|H) / P(E|¬H). LR > 1 supports H; LR = 1 is noise; LR < 1 undermines H.
- Posterior odds = prior odds × LR (multiply even when LR < 1); p = odds / (1 + odds).
- Strength bands for distance from 1: weak ~1.5–3×, moderate 3–10×, strong 10–100×, definitive 100×+.
- Yesterday's posterior is today's prior for the next evidence. For rare events, start from the base rate — vivid positives still leave most mass on false alarms.
- Fermi-bound unmeasured quantities (only when you need a magnitude you cannot measure/look up):
- Decompose: Quantity = Factor₁ × Factor₂ × … (or sum of components).
- Bound each factor with a range; use one-significant-figure geometric means for order-of-magnitude.
- Multiply; report "~X within 3–5×"; sanity-check whether a 10× error would change the decision; replace any factor that is actually lookup-able.
- Skip Fermi when the number is cheaply measurable, when the decision needs tighter than ~3–5× precision, or when every factor is pure invention.
- State the final estimate for checking: claim, range/CIs, key uncertainties, and the observation that would prove it wrong. Stop when the decision is stable across the remaining range or the next update needs new evidence you do not have.
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 · 56 lines · 48 tokens per session scan A e597f111923e
thinking-probabilistic is a skill published in the GitHub repository tjboudreaux/cc-thinking-skills (1,293 stars, last pushed 1mo ago), licensed MIT. It adds 48 tokens to every session and 1,026 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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