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 deciqAI/knowledge-skills --skill logical-fallaciesgit clone --depth 1 https://github.com/deciqAI/knowledge-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/deciqai/knowledge-skills/logical-fallacies)<a href="https://agentmods.dev/skills/deciqai/knowledge-skills/logical-fallacies"><img src="https://agentmods.dev/badge/skills/deciqai/knowledge-skills/logical-fallacies/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/deciqai/knowledge-skills/logical-fallacies"><img src="https://agentmods.dev/badge/skills/deciqai/knowledge-skills/logical-fallacies.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00104 | $0.02172 |
| Opus 5 | $0.00052 | $0.01086 |
| Sonnet 5 | $0.00021 | $0.00434 |
| Haiku 4.5 | $0.00010 | $0.00217 |
Grade A, and why
logical-fallacies 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 9d 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 — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Logical Fallacies
Overview
A fallacy is an argument that looks like it works but doesn't. The test is not whether the conclusion is true — it's whether the inference from premises to conclusion is valid. This skill covers two layers: the classical taxonomy (Aristotle's 13, c. 350 BCE — verbal and structural errors) and the modern cognitive map (Tversky-Kahneman 1983 — errors competent reasoners commit automatically before any sophist arrives).
Composes with neighbors: critical-thinking audits evidence quality and framing; first-principles attacks premises; mece catches decomposition errors that masquerade as false-dichotomy or composition fallacies.
When to Use
- An argument feels persuasive but you cannot articulate why
- A claim is supported entirely by authority, popularity, emotion, or anecdote
- You're about to decide based on a single argument or analogy
- A debate is moving fast ("everyone knows Y") — speed is the sophist's friend
- You catch yourself reasoning emotionally ("this has to be true because…")
- You're weighing an AI hype or AI-adoption claim ("a lab CEO said it's near," "it passed the benchmark so it's intelligent," "doom vs. utopia")
When NOT to use: casual small talk with low stakes; conclusion is empirically verifiable (just check the data); you're tempted to name a fallacy to dismiss an opponent rather than find truth (that is itself the fallacy fallacy).
Coaching Novices (Adaptive Front Door)
- Engine mode: user has a concrete argument → run The Process directly.
- Coach mode: user signals unfamiliarity or has no concrete case → guide step by step.
In Coach mode, respond one step at a time. Each [WAIT] is a hard stop — output only that step's question, then stop.
- One-line what-it-is: some arguments sound right but don't earn their conclusion — this is a checklist for finding that gap, including in your own thinking.
- Check fit against When to Use / When NOT to use. If data can answer it, say so.
- Elicit their real argument — ask for a concrete case (something someone said, an article they're suspicious of). > [WAIT — do not advance until user responds]
- Walk through the Audit one pass per turn: pose the question, wait for their answer, surface what they missed. > [WAIT — do not advance until user responds]
- Close by naming the one fallacy they found and what changes about the conclusion now that they've seen it. > [WAIT — do not advance until user responds]
What ships with it
3 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.
- 9d ago First seen · 119 lines · 104 tokens per session scan A 90d635af9c64
logical-fallacies is a skill published in the GitHub repository deciqAI/knowledge-skills (10 stars, last pushed 10d ago), licensed MIT. It adds 104 tokens to every session and 2,172 once invoked, about $0.0005 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 2026-09-03.
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