Borrowing it
Nothing to install: this file belongs to Alexander-M-Dickerson/ai-asset-pricing. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Alexander-M-Dickerson/ai-asset-pricing/main/.claude/skills/audit-math/SKILL.mdgit clone --depth 1 https://github.com/Alexander-M-Dickerson/ai-asset-pricingWrote 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/alexander-m-dickerson/ai-asset-pricing/audit-math)<a href="https://agentmods.dev/skills/alexander-m-dickerson/ai-asset-pricing/audit-math"><img src="https://agentmods.dev/badge/skills/alexander-m-dickerson/ai-asset-pricing/audit-math/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/alexander-m-dickerson/ai-asset-pricing/audit-math"><img src="https://agentmods.dev/badge/skills/alexander-m-dickerson/ai-asset-pricing/audit-math.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00018 | $0.02241 |
| Opus 5.5 | $0.00007 | $0.00896 |
| Sonnet 5.5 | $0.00004 | $0.00448 |
| Haiku 4.5 | $0.00002 | $0.00224 |
Grade A, and why
audit-math 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 2mo 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 — 182 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Audit Math Skill
Structured adversarial audit of mathematical content: proofs, derivations, definitions, assumptions, and formal environments. Works on any section containing formal math.
Examples
/audit-math appendix-a-- full audit of Appendix A/audit-math methodology-- audit math content in the methodology section/audit-math 200-450-- audit specific line range in main.tex
Input
The user provides one of:
- A section key (e.g.,
appendix-a,methodology,results) - A line range (e.g.,
200-450) - If omitted, scans main.tex for sections containing formal environments and audits the first one found
Workflow
Step 1: Load Context
- Read
.claude/rules/notation-protocol.mdfor custom commands, core variables, subscript conventions, theorem environment numbering, and math writing rules (if it exists) - Read
guidance/paper-context.mdfor key labels, formal environment ordering, and canonical results (if it exists) - Read
.claude/rules/academic-writing.mdfor cross-reference style rules and terminology - Extract the target section from
main.texusing%% BEGIN/ENDmarkers (or line range)
Step 2: Inventory Formal Environments
Build a registry of every formal environment in the target section:
- Definitions (
\begin{definition}) - Assumptions (
\begin{assumption}) - Lemmas (
\begin{lemma}) - Propositions (
\begin{proposition}) - Corollaries (
\begin{corollary}) - Theorems (
\begin{theorem}) - Proofs (
\begin{proof}) - Remarks (
\begin{remark})
For each, record: label, name (from [...] bracket), line number, and which assumptions/results it references.
If notation-protocol.md registers environment numbering, cross-check against it. Flag any missing or extra environments, misordered labels, or mismatched names.
Step 3: Assumption Dependency Audit
For each lemma, proposition, corollary, and theorem:
- List the assumptions explicitly invoked in the statement (e.g., "Under Assumptions \ref{assum:iid} and \ref{assum:overlap}")
- List the assumptions actually used in the proof
- Flag hidden dependencies: assumptions used in the proof but not stated in the result
- Flag unused declarations: assumptions stated in the result but never invoked in the proof
- Flag implicit prerequisites: does the result depend on an earlier definition or lemma not cited?
- Check that assumption references use
\ref{assum:...}(not prose descriptions like "the independence assumption")
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.
- 2mo ago First seen · 182 lines · 18 tokens per session scan A 0e8d231e1ff9
audit-math is a skill published in the GitHub repository Alexander-M-Dickerson/ai-asset-pricing (59 stars, last pushed 6mo ago), licensed MIT. It adds 18 tokens to every session and 2,241 once invoked, about $0.0001 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 2026-08-30.
audit-math compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| audit-mathAlexander-M-Dickerson/ai-asset-pricing | Skill | 59 | 6mo ago | MIT | A | 18 | Claude Code |
| instrument-data-to-allotropeanthropics/knowledge-work-plugins | Skill | 35k | 2d ago | Apache-2.0 | A | 123 | Claude Code |
| exploratory-data-analysisK-Dense-AI/scientific-agent-skills | Skill | 56k | 4d ago | MIT | A | 83 | Claude Code |
| matlabK-Dense-AI/scientific-agent-skills | Skill | 56k | 4d ago | MIT | A | 44 | Claude Code |
| phylogeneticsK-Dense-AI/scientific-agent-skills | Skill | 56k | 4d ago | MIT | A | 71 | Claude Code, Codex |
| research-engineerdavila7/claude-code-templates | Skill | 33k | yesterday | MIT | A | 43 | Claude Code, Codex |
| mapping-to-snomedmaziyarpanahi/openmed | Skill | 5.8k | yesterday | Apache-2.0 | A | 205 | Claude Code |