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-journal-testgit 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-journal-test)<a href="https://agentmods.dev/skills/ololand-ai/ololand-plugins/cmd-journal-test"><img src="https://agentmods.dev/badge/skills/ololand-ai/ololand-plugins/cmd-journal-test.svg" alt="Measured on agentmods" 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 | $0.00050 | $0.00512 |
| Opus 5 | $0.00025 | $0.00256 |
| Sonnet 5 | $0.00010 | $0.00102 |
| Haiku 4.5 | $0.00005 | $0.00051 |
Grade A, and why
ololand-forensic-qoe-journal-test 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.
How it starts
The opening of the file, as written. The whole thing — 46 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Codex wrapper for /journal-test
Follow the OloLand command instructions below when the user asks for /journal-test or the equivalent workflow in Codex.
Journal-Entry Testing
Detects anomalous journal-entry patterns that frequently accompany earnings management or fraud: period-end concentration spikes, round-number frequency above baseline, entries posted by users without authority, weekend/holiday postings, and reversing entries that don't reverse.
Usage
/journal-test <deal_id>
Arguments
deal_id(required) — The deal to test. Requires GL export with timestamps, posting user IDs, and account codes.
Execution
- Call
analyze_forensic_qoe(deal_id)and extract the journal-entry testing section from the full battery. Do not pass aprimitivesargument. If GL timestamps or posting-user fields are missing, classify the result as a diligence gap rather than a clean finding. - The engine runs five tests:
- Period-end concentration — what % of revenue/expense entries land in the last 5 business days of the quarter? Compare to baseline.
- Round-number frequency — what % of entries end in
,000or,500? Above-baseline rates suggest estimation rather than transaction. - Posting authority — entries posted by users not in the standard authorization list.
- Weekend/holiday entries — material entries posted outside business hours.
- Reversing-entry anomalies — entries flagged "reversing" that never reverse, or that reverse in a different period.
- Returns flagged entries with severity scoring and a list of the top 20 most anomalous postings.
Why this matters
Journal-entry testing is the deepest forensic primitive in the QoE arsenal — and the one Big-4 charges the most for. Public-company audit literature (Center for Audit Quality) identifies anomalous JE patterns as the highest-yield fraud indicator. Surfacing them pre-LOI tells you whether the underlying books are reliable enough to bid on.
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 · 46 lines · 50 tokens per session scan A 0b3a287c93a3
ololand-forensic-qoe-journal-test is a skill published in the GitHub repository ololand-ai/ololand-plugins (0 stars, last pushed 2d ago), licensed Apache-2.0. It adds 50 tokens to every session and 512 once invoked, about $0.0003 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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