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 forensic-qoegit 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/forensic-qoe)<a href="https://agentmods.dev/skills/ololand-ai/ololand-plugins/forensic-qoe"><img src="https://agentmods.dev/badge/skills/ololand-ai/ololand-plugins/forensic-qoe/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/forensic-qoe"><img src="https://agentmods.dev/badge/skills/ololand-ai/ololand-plugins/forensic-qoe.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 | $0.00064 | $0.00710 |
| Opus 5.5 | $0.00026 | $0.00284 |
| Sonnet 5.5 | $0.00013 | $0.00142 |
| Haiku 4.5 | $0.00006 | $0.00071 |
Grade A, and why
forensic-qoe 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 — 53 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Forensic Quality of Earnings
Use deterministic OloLand tools for forensic checks. Do not infer forensic conclusions from prose alone — the verifier-stack premise is that every QoE conclusion comes from a tool with a documented methodology and inputs.
Minimum screen — always run before IC
Each of these is available as an MCP tool / /-command in this plugin:
| Procedure | When required | Tool / command |
|---|---|---|
| Beneish M-Score | Every target. Earnings-manipulation probability. | /cmd-beneish |
| Benford distribution review | When suitable transaction-level GL data is available. Reviews digit conformity; deviations require investigation. | /cmd-benford |
| EBITDA bridge and adjustment quality | Every target. Walks from reported EBITDA to QoE-adjusted EBITDA with explicit adjustment categories. | /cmd-ebitda-bridge |
| Revenue quality deep dive | Whenever invoice-level or revenue-by-customer detail is available. | manual + tool stack |
| Working capital anomaly review | Every target. DSO/DIO/DPO trends + seasonality. | manual + tool stack |
| Journal entry testing | Whenever transaction-level data is available. Tests journal entries against fraud patterns (round numbers, period-end clustering, manual entries from privileged users). | /cmd-journal-test |
| Lapping detection | Whenever AR aging and cash receipts can be reconciled. | /cmd-lapping-check |
When inputs are missing
State the limitation explicitly. Do not fabricate a conclusion from incomplete data:
- "Benford's review requires transaction-level GL data. The data room contains only summary financials; this procedure was not run."
- "Lapping detection requires AR aging matched with cash receipts. AR aging was provided; cash receipts were not. Procedure deferred."
A QoE that skips a procedure because the data is missing is not a QoE failure — but the IC memo must surface the gap as a diligence condition.
Output format
For Benford, preserve signed transaction amounts: the standalone tool evaluates negative amounts by absolute magnitude and ignores zero/unusable values. Use only returned sample size, status, distributions, χ², MAD, and conformity; the current standalone response does not supply a p-value or account/transaction rankings. Do not infer fraud, a clean bill of health, or computed results from an insufficient-sample response.
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 · +7 lines fdd9335fead7
- 1mo ago First seen · 46 lines · 64 tokens per session scan A 55ce11129207
forensic-qoe is a skill published in the GitHub repository ololand-ai/ololand-plugins (0 stars, last pushed 3d ago), licensed Apache-2.0. It adds 64 tokens to every session and 710 once invoked, about $0.0003 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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