AI Risk Impact Assessment Validator — OpenChainGraph compute node (compliance_mandate). Runs deterministically in-browser; zero PII, zero egress. Exports an AP2 artifact with execution_hash for chain provenance. Consumes upstream artifacts from: art-171-iso42001-aims-clause-conformance. Output fe...
AI agents call validate_ai_impact_assessment to retrieve information from Ainumbers Mcp Apps without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
compute | string | — | Compute mode (v0.4 Compute Binding). "auto" (default) = server for gpu:false nodes with registered kernels; "server" = force server-side; "browser" = always ret |
parent_hashes | array | — | execution_hash values from upstream ChainGraph AP2 artifacts to chain from (sets chain.parent_hashes in the export). |
parent_tool_ids | array | — | tool_id values matching parent_hashes, in the same order. |
policy_parameters | object | — | Input parameters for this tool's decision function. For gpu:false nodes with a registered kernel, these are computed server-side when compute is "auto" or "serv |
Parameters from the server's own tool schema.
The tool is described as a validator/assessment tool that runs deterministically with zero egress and zero PII. It consumes upstream artifacts and produces output artifacts (exports an AP2 artifact with execution_hash), but the server description explicitly states 'Read-only, no auth, zero PII.' The tool validates and classifies AI risk impact assessments without modifying external state.
From the tool's definition Runs deterministically in-browser; zero PII, zero egress. Read-only, no auth, zero PII.
Attacks that exploit this kind of access
AI Risk Impact Assessment Validator — OpenChainGraph compute node (compliance_mandate). Runs deterministically in-browser; zero PII, zero egress. Exports an AP2 artifact with execution_hash for chain provenance. Consumes upstream artifacts from: art-171-iso42001-aims-clause-conformance. Output feeds: art-173-ai-system-governance-classifier. Open at: https://ainumbers.co/chaingraph/art-172-ai-risk-impact-assessment-validator.html. It is categorised as a Read tool in the Ainumbers Mcp Apps MCP Server, which means it retrieves data without modifying state.
validate_ai_impact_assessment accepts 4 parameters: compute, parent_hashes, parent_tool_ids, policy_parameters. The full parameter table on this page comes from the server's own tool schema.
Register the Ainumbers Mcp Apps MCP server in PolicyLayer and add a rule for validate_ai_impact_assessment: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Ainumbers Mcp Apps. Nothing to install.
validate_ai_impact_assessment is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the validate_ai_impact_assessment rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for validate_ai_impact_assessment. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
validate_ai_impact_assessment is provided by the Ainumbers Mcp Apps MCP server (postoaklabs/ainumbers-mcp-apps). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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