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 ololand-ai/ololand-plugins --skill cmd-benfordgit clone --depth 1 https://github.com/ololand-ai/ololand-pluginsWrote 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/ololand-ai/ololand-plugins/cmd-benford)<a href="https://agentmods.dev/skills/ololand-ai/ololand-plugins/cmd-benford"><img src="https://agentmods.dev/badge/skills/ololand-ai/ololand-plugins/cmd-benford/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/ololand-ai/ololand-plugins/cmd-benford"><img src="https://agentmods.dev/badge/skills/ololand-ai/ololand-plugins/cmd-benford.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 | $0.00048 | $0.00798 |
| Opus 5.5 | $0.00019 | $0.00319 |
| Sonnet 5.5 | $0.00010 | $0.00160 |
| Haiku 4.5 | $0.00005 | $0.00080 |
Grade A, and why
ololand-forensic-qoe-benford 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 17d 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 — 60 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Codex wrapper for /benford
Follow the OloLand command instructions below when the user asks for /benford or the equivalent workflow in Codex.
Benford's Law
Benford's Law describes a logarithmic first-digit distribution in suitable naturally-occurring datasets. Deviations are investigation prompts, not proof of fabricated transactions or fraud; conformity does not establish that transactions are legitimate.
Usage
/benford <deal_id>
/benford <supplied transaction list or GL file>
Arguments
- Supply either a
deal_idfor the deal-scoped forensic workflow or a transaction list/GL file for the standalone tool.run_benfordacceptstransactions, not a deal or dataset identifier; each transaction dictionary needs anamountfield. - Preserve signed transaction amounts. Negative amounts are evaluated by absolute magnitude; zero and unusable values are ignored. Do not drop valid credits/reversals merely because their amounts are negative.
- Use the returned usable
sample_size,minimum_required, andstatus; a file's raw row count is not the tested population or a guarantee of statistical reliability.
Execution
- If the user supplied a transaction list or GL file, parse it into transaction dictionaries using the current tool schema and call
run_benford(transactions). The standalone tool analyzes only that supplied payload; it does not fetch the deal's data room. If the user supplied onlydeal_id, callanalyze_forensic_qoe(deal_id)and extract the returned Benford section. Do not pass aprimitivesargument or invent a transaction-fetch endpoint. - Inspect the returned
statusand usable sample size before interpretation.insufficient_sample, unavailable, unreliable, or uncomputed results are explicit gaps, not conformity or passing tests. Do not report placeholder zero distributions from an insufficient-sample response as measured results. - For computed results, report the returned observed/expected first-digit distributions,
chi_square, Mean Absolute Deviation (mad),conformity, andmost_deviant_digitwhen present. Preserve the response's scope and limitations. - The current standalone
run_benfordresponse does not returnp_value, account-level flags, or ranked contributing transactions. Do not invent or back-calculate these and attribute them to the service. Account-specific findings or transaction follow-ups require separate actual source evidence.
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.
- 17d ago Changed · +4 lines · -1 tokens per session 74512bda244b
- 1mo ago First seen · 56 lines · 49 tokens per session scan A 6f92676299fd
ololand-forensic-qoe-benford is a skill published in the GitHub repository ololand-ai/ololand-plugins (0 stars, last pushed 3d ago), licensed Apache-2.0. It adds 48 tokens to every session and 798 once invoked, about $0.0002 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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