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.
git 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/plugins/ololand-ai/ololand-plugins/ololand-forensic-qoe)<a href="https://agentmods.dev/plugins/ololand-ai/ololand-plugins/ololand-forensic-qoe"><img src="https://agentmods.dev/badge/plugins/ololand-ai/ololand-plugins/ololand-forensic-qoe.svg" alt="Measured on agentmods" height="20"></a>Grade A, and why
ololand-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 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.
What it actually says
{
"name": "ololand-forensic-qoe",
"version": "0.6.3",
"description": "Forensic Quality-of-Earnings primitives as a standalone Claude plugin: Beneish M-Score, Benford's Law, EBITDA bridge, journal-entry testing, lapping detection, working-capital deep dive, and sourced covenant, cross-default, and MAC/MAE clause analysis. Wraps OloLand's deterministic forensic engines as the Pre-LOI Forensic Screen and Full QoE reports — included in OloLand Pro and above. Positioned against Big-4 QoE ($150-500K, 4-8 weeks).",
"author": {
"name": "OloLand",
"email": "[email protected]",
"url": "https://ololand.ai"
},
"homepage": "https://ololand.ai/qoe",
"repository": "https://github.com/ololand-ai/ololand-plugins",
"license": "Apache-2.0",
"keywords": [
"forensic",
"qoe",
"quality-of-earnings",
"beneish",
"benford",
"ebitda-bridge",
"lapping",
"journal-entry-testing",
"covenant-analysis",
"conflict-detection",
"due-diligence",
"private-equity",
"m-and-a",
"pre-loi"
]
}
What it installs
The manifest is a name and a version. 10 skills, 8 commands travel with it, and installing the plugin installs all of them — 1,075 tokens a session between them. Each is measured on its own page, and each can be installed alone.
- Skill ololand-forensic-qoe-forensic-screen A 89 tokens
- Skill ololand-forensic-qoe-conflicts A 120 tokens
- Skill ololand-forensic-qoe-verify A 165 tokens
- Skill ololand-forensic-qoe-benford A 49 tokens
- Skill ololand-forensic-qoe-ebitda-bridge A 65 tokens
- Skill ololand-forensic-qoe-journal-test A 50 tokens
- Skill ololand-forensic-qoe-lapping-check A 57 tokens
- Skill ololand-forensic-qoe-beneish A 52 tokens
- Skill forensic-qoe A 64 tokens
- Skill ololand-forensic-qoe-legal-risk A 47 tokens
- Command forensic-screen A 62 tokens
- Command conflicts A 95 tokens
- Command ebitda-bridge A 34 tokens
- Command beneish A 26 tokens
- Command benford A 24 tokens
- Command journal-test A 24 tokens
- Command lapping-check A 31 tokens
- Command legal-risk A 21 tokens
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 · 30 lines scan A 613cfb6cc441
ololand-forensic-qoe is a plugin published in the GitHub repository ololand-ai/ololand-plugins (0 stars, last pushed 2d ago), licensed Apache-2.0. Its token cost is not measured: this kind of file is read by the harness, not the model. 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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