Builds a deterministic sampling frame over historical AML alert dispositions for independent-validator review, plus a reviewer workload allocation. The statistical core (sample size, deterministic interval selection over your declared population hash) is not reimplemented here — it reuses the shipped attribute-sampling-plan kernel's calculation directly, the same systematic-sampling convention SOX 404 / ICFR control testing already uses. No randomness, so any reviewer can replay the exact same sample from the same declared inputs. This tool adds only the AML-specific layer: labeling the frame as a disposition sample and fanning the selected indices out round-robin across your reviewer roster.
Copy this paragraph into Claude, OpenClaw, or any MCP-aware agent to run this exact tool, with this sample, and verify the artifact.
Run the AINumbers MCP tool `plan_aml_disposition_sample`. Task: Build a deterministic sampling frame over an AML consent-order lookback's historical alert dispositions for independent-validator review, plus a reviewer workload allocation.
Synthetic sample input (policy_parameters): {"confidence_level":95,"disposition_population_size":1000,"tolerable_deviation_rate":5,"expected_deviation_rate":0,"disposition_population_hash":"abc123","reviewer_roster":["reviewer_1"]}
Verify before trusting: call `verify_execution_hash` on mcp.ainumbers.co (https://mcp.ainumbers.co/mcp) with the returned execution_hash.
Return the ledger link https://ledger.ainumbers.co/ so a human can re-verify without contacting us.
PII rule: All inputs are processed locally in your browser. No data is transmitted. Do not enter real personal data — use synthetic or anonymised inputs only.
Open the tool with the sample prefilled: https://ainumbers.co/chaingraph/art-471-disposition-sampling-frame.html#p=v1.H4sIAAAAAAAA_wG7AET_eyJjb25maWRlbmNlX2xldmVsIjo5NSwiZGlzcG9zaXRpb25fcG9wdWxhdGlvbl9zaXplIjoxMDAwLCJ0b2xlcmFibGVfZGV2aWF0aW9uX3JhdGUiOjUsImV4cGVjdGVkX2RldmlhdGlvbl9yYXRlIjowLCJkaXNwb3NpdGlvbl9wb3B1bGF0aW9uX2hhc2giOiJhYmMxMjMiLCJyZXZpZXdlcl9yb3N0ZXIiOlsicmV2aWV3ZXJfMSJdfYN-vE27AAAA