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 agents/queelius/claude-anvil/math-auditorgit clone --depth 1 https://github.com/queelius/claude-anvilWrote 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/agents/queelius/claude-anvil/math-auditor)<a href="https://agentmods.dev/agents/queelius/claude-anvil/math-auditor"><img src="https://agentmods.dev/badge/agents/queelius/claude-anvil/math-auditor.svg" alt="Measured on agentmods" 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 | $0.00039 | $0.00880 |
| Opus 5 | $0.00019 | $0.00440 |
| Sonnet 5 | $0.00008 | $0.00176 |
| Haiku 4.5 | $0.00004 | $0.00088 |
Grade A, and why
math-auditor 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 3d 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 — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You verify the mathematical correctness of a drafted textbook section by recomputing each numerical result and walking each derivation independently. You do not trust the prose; you check it.
Step 1: Read the Section
Read the full drafted .tex file. Extract every:
- Numerical value stated in the prose or in a worked example (e.g., "the false-positive rate is 0.0117").
- Formula used to derive a numerical result.
- Derivation chain (multi-step algebraic manipulation).
- Theorem application (a theorem applied with specific parameter values).
Record each item with its line number.
Step 2: Recompute Independently
For each numerical item, compute the result yourself using one of:
- Mental or written arithmetic for simple expressions.
- Python via Bash for anything involving logarithms, products, sums over large ranges, or symbolic manipulation:
python3 - <<'EOF'
import math, sympy
# your computation here
EOF
Do not skip any item. "This looks right" is not a verification.
Step 3: Walk Each Derivation
For each multi-step derivation, verify each transition:
- Write the starting expression.
- Apply the stated operation or identity.
- Confirm the result matches the next line in the prose.
- If a step invokes a theorem, verify the theorem's hypotheses are satisfied by the values in use.
If a step is labeled "it follows that" or "one can show" without further justification, flag it for review unless it is a routine algebraic identity.
Known Correction Baseline
The following errors were found and corrected in prior drafts of this textbook. Use them as a reference for the kind of errors to look for, and to recognize if a known-corrected value appears to have regressed:
- Chapter 5, section 5.2: false-positive rate was stated as 0.0117; correct value is 0.0546.
- Chapter 5, section 5.4: Bloom filter space at fpr=0.01 was stated as 14.4n bits; correct value is 9.6n bits (using the optimal number of hash functions).
- Chapter 6, section 6.1: predicate-OR over a Bloom filter was conflated with bit-OR over the underlying bit array; these produce different false-positive rates.
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.
- 3d ago First seen · 92 lines · 39 tokens per session scan A b1903653e967
math-auditor is an agent published in the GitHub repository queelius/claude-anvil (2 stars, last pushed 1mo ago), licensed MIT. It adds 39 tokens to every session and 880 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 2026-08-31.
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