What is ololand-forensic-qoe-benford?

A Benford's Law test for general-ledger transactions. Benford's Law describes the expected frequency of leading digits in many naturally occurring datasets.

Use it to examine the first digits of at least 1,000 ledger line items and compare the observed distribution with the expected one.

Large departures from that pattern can flag transactions that may have been fabricated or selectively entered, although they are not proof of fraud.

ololand-forensic-qoe-benford — Skill for Claude Code by ololand-ai

Install

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.

Any agent

npx skills add ololand-ai/ololand-plugins --skill cmd-benford

Clone the repo

git clone --depth 1 https://github.com/ololand-ai/ololand-plugins

Made for: Claude Code.

Or install ololand-forensic-qoe, the plugin that ships this one along with the rest of its 10 skills, 8 commands.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/ololand-ai/ololand-plugins/cmd-benford.svg)](https://agentmods.dev/skills/ololand-ai/ololand-plugins/cmd-benford)

Your own site

<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="Measured on agentmods" height="20"></a>

Per session 49 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 567 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

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	$0.00049	$0.00567
Opus 5	$0.00024	$0.00283
Sonnet 5	$0.00010	$0.00113
Haiku 4.5	$0.00005	$0.00057

Measured 4d ago against content hash 6f92676299fd, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

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 4d 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.

plugins/ololand-forensic-qoe/skills/cmd-benford/SKILL.md · 56 lines

How it starts

The opening of the file, as written. The whole thing — 56 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 states that in many naturally-occurring datasets, the leading digit follows a logarithmic distribution: ~30% start with 1, ~17% with 2, etc. Significant deviation from this distribution is a classic forensic indicator of fabricated or selectively-entered transactions.

Usage

/benford <deal_id>

Arguments

deal_id (required) — The deal whose GL transactions to test. Requires uploaded GL export with at least 1,000 line items for statistical validity.

Execution

If the user supplied a transaction list or GL file, parse it into transaction dictionaries and call run_benford(transactions). If the user supplied only deal_id, call analyze_forensic_qoe(deal_id) and extract the Benford section from the full battery. Do not pass a primitives argument.
The engine pulls all GL transactions from the deal's data room (or from forensic_extraction_service if extraction has been run).
Computes observed first-digit distribution and compares to Benford expected via χ² goodness-of-fit and Mean Absolute Deviation (MAD).
Flags account categories with the most significant deviations.

Interpretation

MAD < 0.012 — close conformity (green)
0.012 ≤ MAD < 0.015 — acceptable conformity (yellow)
MAD ≥ 0.015 — non-conformity (red — investigate the high-deviation accounts)

Output

For each account category that deviates significantly from Benford expected:

Observed vs. expected first-digit distribution (table + chart)
χ² statistic and p-value
Top transactions contributing to the deviation
Suggested follow-up: which specific journal entries to examine

Why this matters

Benford's Law is the deterministic statistical test most commonly cited in fraud forensics literature. It cannot be evaded by altering totals — it operates on the digit-level distribution of every transaction. Pre-LOI screening with Benford catches the deals where journal entries have been manipulated before you commit to fieldwork.

Read the full file on GitHub · 56 lines

Changes

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.

4d ago First seen · 56 lines · 49 tokens per session scan A 6f92676299fd

Subscribe to this mod's changes

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 49 tokens to every session and 567 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 2026-09-03.

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