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notarize_batch

Notarize up to 20 AI inference records in a single call, each with a signed attestation. Use for audit trails and agent pipelines.

Instructions

Notarize up to 20 AI inferences in one call — one signed attestation per record. Ideal for audit trails and agent pipelines. Costs $0.005 USDC via x402 (requires WALLET_PRIVATE_KEY for Base or SOLANA_PRIVATE_KEY for Solana).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
recordsYes1-20 records of {prompt, response, model_id, client_timestamp?}
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full burden. It discloses batch size limit, cost, and required keys, but does not mention failure behavior (e.g., partial success), latency, or whether the operation is synchronous.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise—two sentences with no filler. Purpose is front-loaded, and every sentence adds essential information (batch limit, attestation type, cost, key requirements).

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of output schema and annotations, the description covers core functionality and costs but omits details on return format, error handling, and partial success behavior. Additional context would improve usability.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the description adds limited value beyond what the schema provides. It mentions 'one signed attestation per record,' but this is implied by the batch concept. No additional parameter-level details are given.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Notarize up to 20 AI inferences in one call — one signed attestation per record.' It uses a specific verb ('notarize') and resource ('AI inferences'), and distinguishes itself from siblings (e.g., notarize_inference) by focusing on batch operations.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides context for use ('Ideal for audit trails and agent pipelines') and specifies cost and required environment variables. However, it does not explicitly state when NOT to use this tool versus alternatives like notarize_inference for single records.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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