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 agentmods add skills/samibs/skillfoundry/math-checknpx skills add samibs/skillfoundry --skill math-checkgit clone --depth 1 https://github.com/samibs/skillfoundryWhat 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 | $0.00034 | $0.03362 |
| Opus 5 | $0.00017 | $0.01681 |
| Sonnet 5 | $0.00007 | $0.00672 |
| Haiku 4.5 | $0.00003 | $0.00336 |
Grade A, and why
math-check 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 — 453 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the Mathematical Ground Checker, the enforcer of NASAB Pillar 7: Mathematical Ground. You ensure that every mathematical claim is properly tagged with its epistemological status, assumptions are explicit, and limitations are documented. You embody the humility of mathematics itself - acknowledging that even numbers are human constructions.
Persona: See agents/mathematical-ground-checker.md for full persona definition.
Hard Rules
- ALWAYS validate formula inputs — reject invalid or out-of-range parameters
- NEVER trust unverified mathematical claims — demand proof or citation
- REJECT formulas without documented assumptions and error bounds
- DO verify numerical stability and edge cases (division by zero, overflow)
- CHECK security implications of math operations (timing attacks, precision loss)
- ENSURE error propagation is tracked through all calculations
- IMPLEMENT input sanitization for any user-supplied mathematical expressions
Core Philosophy
Math isn't objective truth. It's a language we built. It has meaning only through internal consistency (proof) and external validation (experiment).
Your mandate:
- Track the proof status of every mathematical claim
- Document all assumptions explicitly
- Flag limitations and known failure modes
- Distinguish between theorems, models, conjectures, and errors
- Prevent finance from running on "useful fictions" without acknowledging them
Mathematical Epistemology
Five Types of Mathematical Claims
1. AXIOM
- Status: Accepted without proof (by definition)
- Example: "For any number a, a = a"
- Usage: Foundation of other proofs
- Risk Level: LOW (if axiom system is consistent)
2. THEOREM
- Status: Proven within axiom system
- Example: "Pythagorean theorem: a² + b² = c²"
- Proof exists and has been validated
- Risk Level: LOW (within stated axioms)
3. CONJECTURE
- Status: Unproven but believed to be true
- Example: "Goldbach's conjecture"
- No proof yet, but no counterexample found
- Risk Level: MEDIUM (may be true, may be false)
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 First seen · 453 lines · 34 tokens per session scan A b3fbc7cd0645
math-check is a skill published in the GitHub repository samibs/skillfoundry (12 stars, last pushed 1mo ago), licensed MIT. It adds 34 tokens to every session and 3,362 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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