Wholesale Tokenized Settlement Fit Diagnostic — OpenChainGraph compute node (agent_guardrail_mandate). Runs deterministically in-browser; zero PII, zero egress. Exports an AP2 artifact with execution_hash for chain provenance. Output feeds: art-57-deposit-token-compliance-validator, art-58-cross-...
AI agents invoke run_tokenized_settlement_fit to trigger actions in Ainumbers Mcp Apps. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.
| 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.
While described as 'read-only' in server metadata, the tool's actual operation is Execute-category because it: (1) runs deterministic computations on a 'compute node' with specific agent guardrails, (2) produces cryptographic artifacts and hashes for chain provenance, (3) feeds critical compliance validators that control financial settlement flows.
From the tool's definition Runs deterministically in-browser compute node execution with deterministic settlement diagnostics that feed multiple downstream validators and compliance checkers.
Attacks that exploit this kind of access
Wholesale Tokenized Settlement Fit Diagnostic — OpenChainGraph compute node (agent_guardrail_mandate). Runs deterministically in-browser; zero PII, zero egress. Exports an AP2 artifact with execution_hash for chain provenance. Output feeds: art-57-deposit-token-compliance-validator, art-58-cross-network-settlement-validator, art-59-settlement-asset-finality-classifier, 505-tokenized-collateral-eligibility-checker, 509-canton-party-allowlist-validator, cry-05-agent-action-audit-trail-aggregator. Open at: https://ainumbers.co/chaingraph/art-56-tokenized-settlement-fit-diagnostic.html. It is categorised as a Execute tool in the Ainumbers Mcp Apps MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
run_tokenized_settlement_fit 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 run_tokenized_settlement_fit: 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.
run_tokenized_settlement_fit is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the run_tokenized_settlement_fit 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 run_tokenized_settlement_fit. 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.
run_tokenized_settlement_fit 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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