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 flonat/flonat-research --skill math-proofgit clone --depth 1 https://github.com/flonat/flonat-researchWrote 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/flonat/flonat-research/math-proof)<a href="https://agentmods.dev/skills/flonat/flonat-research/math-proof"><img src="https://agentmods.dev/badge/skills/flonat/flonat-research/math-proof/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/flonat/flonat-research/math-proof"><img src="https://agentmods.dev/badge/skills/flonat/flonat-research/math-proof.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Anti-Refusal · line 145 Skill instructs the agent to omit warnings, disclaimers, or ethical commentary. Stripping safety caveats hides risk from the user and is a common jailbreak preamble.Fix: Remove instructions that suppress warnings, disclaimers, or ethical commentary. Let the agent surface safety-relevant caveats to the user.
- medium Excessive Agency · line 125 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00068 | $0.02516 |
| Opus 5.5 | $0.00027 | $0.01006 |
| Sonnet 5.5 | $0.00014 | $0.00503 |
| Haiku 4.5 | $0.00007 | $0.00252 |
Grade A, and why
math-proof 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 1mo 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 — 168 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Author: Moran Koren, Ben-Gurion University of the Negev ([email protected]). Part of the Theorist Toolbox.
Math proof
Write rigorous mathematical proofs suitable for peer-reviewed academic papers. Every step should be explicit enough that a reader can verify it without filling in gaps. The proof must be a complete proof, not a proof outline — each step should be carefully explained and documented.
Trigger phrases
math-proof- "prove this"
- "show analytically"
- "derive this result"
- "justify mathematically"
- "write a proof"
- "expand this proof"
Core principles
No gaps between steps
Every transition from one equation to the next must be justified. If you use the quotient rule, say so. If you substitute a definition, point to which definition. If a sign is negative, explain why. The reader should never need to work out an intermediate step on their own.
Bad: $$\frac{d}{d\rho}\frac{n_G}{n_B} = \frac{2q-1}{n_B^2} > 0.$$
Good: We compute $\frac{d}{d\rho}(n_G/n_B)$ using the quotient rule. First, the derivatives: $$\frac{dn_G}{d\rho} = q, \qquad \frac{dn_B}{d\rho} = 1-q.$$ Applying the quotient rule: $$\frac{d}{d\rho}\frac{n_G}{n_B} = \frac{q \cdot n_B - (1-q) \cdot n_G}{n_B^2}.$$ Expanding the numerator: $$q[\rho + (1-\rho)q] - (1-q)[\rho + (1-\rho)(1-q)] = \rho(2q-1) + (1-\rho)(2q-1) = 2q-1.$$ Since $q > 1/2$, this is positive.
State what you want to show before showing it
Open each step with a sentence explaining the goal: "We want to show that $t$ decreases with $\rho$." Then deliver the proof. The reader should know where you are headed before wading into algebra.
Sign every term
When a derivative or expression appears, immediately state its sign and why. Do not leave sign determination as an exercise. If a quantity is negative because it is a log of a number less than 1, say so explicitly.
Bridge definitions to usage
When you define a quantity (like a threshold $t$) and then use it in a derivative, explain the connection. Do not jump from "$Y \geq$ [some expression]" to "$t(K,\rho) =$ [formula]" without a sentence like: "Define $t(K,\rho)$ as the minimum number of yes votes required for allocation, i.e., the smallest integer $Y$ satisfying this inequality."
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.
- 1mo ago First seen · 168 lines · 68 tokens per session scan A 683b1aa424f5
math-proof is a skill published in the GitHub repository flonat/flonat-research (147 stars, last pushed 28d ago), licensed MIT. It adds 68 tokens to every session and 2,516 once invoked, about $0.0003 per session on Opus 5.5. 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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