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 human-avatar/skills-for-humanity --skill s4h-logic-councilgit clone --depth 1 https://github.com/human-avatar/skills-for-humanityWrote 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/human-avatar/skills-for-humanity/s4h-logic-council)<a href="https://agentmods.dev/skills/human-avatar/skills-for-humanity/s4h-logic-council"><img src="https://agentmods.dev/badge/skills/human-avatar/skills-for-humanity/s4h-logic-council/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/human-avatar/skills-for-humanity/s4h-logic-council"><img src="https://agentmods.dev/badge/skills/human-avatar/skills-for-humanity/s4h-logic-council.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 | $0.00147 | $0.02021 |
| Opus 5 | $0.00073 | $0.01010 |
| Sonnet 5 | $0.00029 | $0.00404 |
| Haiku 4.5 | $0.00015 | $0.00202 |
Grade A, and why
s4h-logic-council 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 — 190 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Logic Council
A single reviewer catches some flaws in reasoning. A council catches more — because different reasoning frameworks find different failure modes. Formal logic catches invalid inferences. Systems thinking catches missing feedback loops. Bayesian reasoning catches base-rate neglect. First principles reasoning catches assumptions dressed as facts. Adversarial logic catches the strongest counter-argument you haven't faced yet.
Run all five. Let them disagree. The synthesis tells you where your reasoning is load-bearing and where it's hollow.
The Five Reasoning Frameworks
1. Formal Logic
Tests deductive structure. Are premises stated? Do they support the conclusion? Are necessary and sufficient conditions correctly identified? Finds: invalid inferences, unstated assumptions doing hidden work, conclusions that overreach their premises, equivocation across terms.
2. Systems Thinking
Treats the problem as a system with feedback loops, delays, and emergent properties. Asks: what happens over time? What non-linear effects appear at scale? What second and third-order consequences has the reasoning ignored? Finds: linear thinking applied to non-linear systems, missing feedback loops, unintended consequences, solutions that fix the proximate cause while worsening the root cause.
3. Bayesian Reasoning
Evaluates probabilistic claims and evidence. Asks: what are the base rates? How much should this evidence actually update our beliefs? Is confidence calibrated to evidence? Finds: base-rate neglect, overconfidence from anecdote, underweighted prior probability, failure to consider how likely the evidence would be under alternative hypotheses.
4. First Principles
Strips away assumptions and rebuilds from fundamentals. Asks: what do we actually know is true, vs what are we taking for granted? Is the problem framed correctly, or has the framing inherited constraints that don't belong? Finds: assumptions treated as facts, inherited framings that foreclose better solutions, analogies stretched past their breaking point.
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 · 190 lines · 147 tokens per session scan A 8b9411cf0f53
s4h-logic-council is a skill published in the GitHub repository human-avatar/skills-for-humanity (223 stars, last pushed 1mo ago), licensed MIT. It adds 147 tokens to every session and 2,021 once invoked, about $0.0007 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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