zkproofport-ai

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

With no annotations provided, the description carries the full burden. It discloses that this is a POST request to /api/v1/prove and mentions the server returns 'nonce and TEE key information,' which adds useful behavioral context. However, it doesn't cover potential errors, rate limits, authentication needs, or what happens if inputs are invalid, leaving gaps for a mutation tool.

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

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

The description is efficiently structured with three sentences: it states the purpose, specifies the HTTP method and endpoint, and provides a critical prerequisite. Every sentence adds value without redundancy, making it front-loaded and concise.

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

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

Given no annotations and no output schema, the description is moderately complete. It covers the purpose, usage sequence, and some behavioral details (POST request, return info), but lacks information on error handling, response format beyond high-level mentions, or security considerations. For a tool with 2 parameters and mutation behavior, this is adequate but has clear gaps.

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

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

Schema description coverage is 100%, so the schema already documents both parameters thoroughly. The description adds minimal value beyond the schema by noting that inputs come from prepare_inputs and can be a JSON string or structured object, but this is largely implied by the schema's anyOf type. Baseline 3 is appropriate as the schema does the heavy lifting.

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

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

The description clearly states the action ('Request a challenge from the server') and the resource ('server'), specifying it's part of a step-by-step flow. It distinguishes from siblings by mentioning prepare_inputs as a prerequisite, but doesn't explicitly differentiate from other tools like submit_proof or verify_proof that might also interact with the server.

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

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

The description provides explicit guidance on when to use this tool: 'Step 2 of the step-by-step flow (after prepare_inputs)' and 'You MUST call prepare_inputs first to get the inputs parameter.' It clearly defines the prerequisite and sequence, which helps distinguish it from alternatives like generate_proof or submit_proof.

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