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 TheGoat395/Codex-Skills --skill logical-thinkinggit clone --depth 1 https://github.com/TheGoat395/Codex-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/thegoat395/codex-skills/logical-thinking)<a href="https://agentmods.dev/skills/thegoat395/codex-skills/logical-thinking"><img src="https://agentmods.dev/badge/skills/thegoat395/codex-skills/logical-thinking.svg" alt="Measured on agentmods" height="20"></a>- 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 | $0.00010 | $0.00946 |
| Opus 5 | $0.00005 | $0.00473 |
| Sonnet 5 | $0.00002 | $0.00189 |
| Haiku 4.5 | $0.00001 | $0.00095 |
Grade A, and why
logical-thinking 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 2d 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 — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Logical Thinking
Produce the strongest conclusion the available premises warrant, including unknown, conditional, or no conclusion when appropriate. Logical rigor means choosing the right inference system, preserving meaning and scope, checking each decisive step, and refusing to strengthen the result beyond its proof obligations.
Scale the proof to the question
Adapt the inference family; do not impose a universal template. Preserve meaning, units, scope and quantifiers. Test whether premises can hold while the conclusion fails; use decisive calculations, solvers, tests or observations. Correlated self-review is not independent verification.
For consequential, multi-step, ambiguous or contested inference, read proof and verification plus the applicable family below for maps, step checks, conclusion types and adversarial tests. Simple entailment/calculation remains direct.
Use conditional or unknown when warranted. Proven, must, causes, always and impossible require their own proof burden.
Normalize the problem
Before inference, identify:
- exact question and candidate conclusion;
- premises, observations, rules, and documentation;
- source/status of each premise: given, observed, documented, inferred, assumed, or disputed;
- definitions, entities, variables, units, timeframe, version, and domain;
- quantifiers and modal force: all, some, none, must, may, usually, likely;
- knowledge regime: closed world, open world, or incomplete real-world evidence;
- hidden premises required to connect the stated information.
Resolve semantic ambiguity before formalizing. Do not create precision by translating an unclear sentence into symbols without deciding what the sentence means.
Choose the inference family
| Family | Appropriate question | Valid conclusion form |
|---|---|---|
| Deductive | Must the conclusion follow? | entailed, contradicted, or unknown |
| Defeasible/informal | Is the argument presumptively reasonable? | supported unless a critical exception succeeds |
| Inductive | How strongly do observations generalize? | scoped probability or empirical support |
| Abductive | Which explanation best accounts for the evidence? | best current explanation, not proof |
| Causal | What would happen under intervention or counterfactual change? | association, intervention effect, or counterfactual claim |
| Probabilistic | How should uncertainty update? | posterior or calibrated range under assumptions |
| Documentary/rule | What does an authority establish here? | governing, permitted, required, documented, or unresolved applicability |
| Decision | Which action is preferable under uncertainty? | recommendation conditional on goals and tradeoffs |
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2d ago Changed · -78 lines · -57 tokens per session 7524aaed2054
- 8d ago First seen · 154 lines · 67 tokens per session scan A f17c1b0fcfa5
logical-thinking is a skill published in the GitHub repository TheGoat395/Codex-Skills (122 stars, last pushed 2d ago), licensed MIT. It adds 10 tokens to every session and 946 once invoked, about $0.0001 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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