OpenChainGraph Suite · ART-172 · AI Governance

AI Risk Impact Assessment Validator

Validates ISO 42005-style AI impact-assessment completeness: intended use, affected stakeholders, risk treatment, monitoring plan, approval, risk categories, and data sources. Returns completeness score (0–100) and gap list. Middle node of the ai-management-system-conformance chain. Zero network.

ISO/IEC 42005 AI Impact Assessment Zero PII W3C VC §13.11 v0.5.0
🔒 All inputs are processed locally in your browser. No data is transmitted. Do not enter real personal data — use synthetic or anonymised inputs only.
Scope
Middle node of ai-management-system-conformance chain (art-171→172→173). ISO/IEC 42005 defines AI impact assessment for AI systems. This tool validates completeness across seven required elements: intended use documentation, affected stakeholder identification, risk treatment definition, monitoring plan, approval documentation, risk category identification, and data source listing. Feeds system governance classifier (art-173).
Presets
System Description
Stakeholder & Risk Coverage
Documentation & Controls
Validation Results







  

    
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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 `validate_ai_impact_assessment`. Task: Validate ISO 42005-style AI impact-assessment completeness across seven required elements: intended use, affected stakeholders, risk treatment, monitoring plan, approval documentation, risk categories, and data sources.
Call it with arguments: {"policy_parameters":{"assessment":{"intended_use":"Customer credit scoring system for retail banking","affected_stakeholders":["retail_customers","credit_officers","compliance_team"],"risk_treatment_defined":true,"monitoring_plan":"Monthly bias audits and quarterly accuracy reviews with documented escalation procedure","approval_documented":true,"risk_categories":["bias","accuracy","privacy","security"],"data_sources_listed":true}}}
Verify before trusting: call `verify_execution_hash` on mcp.ainumbers.co (https://mcp.ainumbers.co/mcp) with the parameter `claimed_hash` set to the returned `execution_hash`, passing the full artifact the run returned (the object containing `policy_parameters` + `output_payload` + `execution_hash`; equivalently `policy_parameters` + `output_payload` with `claimed_hash`), not the bare hash string.
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-172-ai-risk-impact-assessment-validator.html#p=v1.H4sIAAAAAAAA_wGfAWD-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