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 CALLE-AI/awesome-phone-call-agents --skill call-arithmetic-accuracy-auditorgit clone --depth 1 https://github.com/CALLE-AI/awesome-phone-call-agentsWrote 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/calle-ai/awesome-phone-call-agents/call-arithmetic-accuracy-auditor)<a href="https://agentmods.dev/skills/calle-ai/awesome-phone-call-agents/call-arithmetic-accuracy-auditor"><img src="https://agentmods.dev/badge/skills/calle-ai/awesome-phone-call-agents/call-arithmetic-accuracy-auditor/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/calle-ai/awesome-phone-call-agents/call-arithmetic-accuracy-auditor"><img src="https://agentmods.dev/badge/skills/calle-ai/awesome-phone-call-agents/call-arithmetic-accuracy-auditor.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 | $0.00111 | $0.01950 |
| Opus 5.5 | $0.00044 | $0.00780 |
| Sonnet 5.5 | $0.00022 | $0.00390 |
| Haiku 4.5 | $0.00011 | $0.00195 |
Grade A, and why
call-arithmetic-accuracy-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 19d 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 — 177 lines — stays where its author put it; the contents beside it link to each section on GitHub.
call-arithmetic-accuracy-auditor
A voice agent that states its factors out loud and then speaks a wrong total has committed the error in front of a customer. A human skimming the transcript hears a confident number - the audit has to redo the multiplication to catch it.
Most QA measures whether a total was disclosed. Almost none measures whether the total was arithmetically true given the numbers the agent itself just spoke. This skill reads a finished call transcript, recomputes every spoken computation from the agent's own stated factors, and grades each one CORRECT, INCORRECT, or UNVERIFIABLE - then rolls the sentence grades into one verdict a reviewer can act on.
Why This Skill Exists
LLM arithmetic is not reliable enough to skip verification. Dziri et al. ("Faith and Fate", arXiv:2305.18654) show transformers solve composition problems by pattern matching, not computation. Mirzadeh et al. (GSM-Symbolic, arXiv:2410.05229) show accuracy degrades when only the numbers change, so a clean-sounding factor sentence does not guarantee a correct total. Wei et al. (arXiv:2505.15000) show spoken math is worse still for cascade ASR+LLM pipelines - exactly CALL-E's architecture. And the FTC's Policy Statement on Deception makes a wrong spoken total a material misrepresentation to a consumer acting reasonably. Verification therefore has to happen outside the model, which is what this auditor is.
When To Use
- after any CALL-E business call that quoted quantities, prices, percent-off results, balances, or durations
- before deploying a goal template whose task involves quoting totals, to establish an arithmetic QA baseline
- in CI over fixture corpora, to catch templates that produce fluent but wrong spoken totals
- alongside a disclosure checker: disclosure asks "was the total stated?"; this skill asks "was the stated total true?"
Modes
Analyze a finished call
python3 scripts/arithmetic_accuracy_auditor.py analyze \
--call-result path/to/call-result.json
What ships with it
11 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- data/example-goal.json 679 B
- data/fixtures/demo-arith-001.json 437 B
- data/fixtures/demo-arith-002.json 392 B
- data/fixtures/demo-arith-003.json 333 B
- data/fixtures/demo-arith-004.json 297 B
- data/fixtures/demo-arith-005.json 433 B
- references/examples.md 6.5 KB
- references/research-papers.md 2.6 KB
- references/safety.md 3.0 KB
- scripts/arithmetic_accuracy_auditor.py 24 KB runs code
- tests/test_arithmetic_accuracy_auditor.py 23 KB runs code
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.
- 19d ago First seen · 177 lines · 111 tokens per session scan A 010ed438460e
call-arithmetic-accuracy-auditor is a skill published in the GitHub repository CALLE-AI/awesome-phone-call-agents (112 stars, last pushed 4d ago), licensed MIT. It adds 111 tokens to every session and 1,950 once invoked, about $0.0004 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 2026-10-21.
call-arithmetic-accuracy-auditor compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| call-arithmetic-accuracy-auditorCALLE-AI/awesome-phone-call-agents | Skill | 112 | 4d ago | MIT | A | 111 | Claude Code, Codex |
| imagegenopenai/codex | Skill | 134k | today | Apache-2.0 | A | 113 | Codex |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 2d ago | MIT | A | 200 | Claude Code, Codex |
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| browser-automationopenclaw/openclaw | Skill | 394k | today | MIT | A | 36 | Claude Code |
| systematic-debuggingobra/superpowers | Skill | 315k | 5d ago | MIT | A | 21 | Claude Code |
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