ololand-forensic-qoe-lapping-check — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited ololand-forensic-qoe-lapping-check (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
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Follow the OloLand command instructions below when the user asks for /lapping-check or the equivalent workflow in Codex.
Lapping is one of the oldest receivables-fraud schemes: customer A's payment is applied to customer B's overdue invoice; later, customer C's payment is applied to A; etc. The cycle hides bad debts and (in more aggressive variants) fictitious revenue. Detection requires looking at the timing and pattern of cash applications, not just totals.
/lapping-check <deal_id>deal_id (required) — The deal to test. Requires AR aging schedule + cash receipts journal with customer-level detail and date stamps.analyze_forensic_qoe(deal_id) and extract the lapping-detection section from the full battery. Do not pass a primitives argument. If AR aging or cash-receipt detail is missing, classify the result as a diligence gap rather than a clean finding.For each detected cycle:
Lapping is invisible to standard AR aging reviews because aging looks correct on the surface — the application is wrong, not the totals. Big-4 QoE catches lapping by tracing customer-to-cash. OloLand's lapping detector runs the same trace deterministically, in seconds, on the GL + AR aging exports already in the data room.
/lapping-check deal_acme_2026~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.