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 of behavioral disclosure. It effectively describes the tool's behavior as handling three steps in a single call, which implies a streamlined but less customizable approach. It also mentions the return format ('Full ProofResult with proof bytes, public inputs, and timing information') and hints at a separate verification step ('Use verify_proof separately to verify on-chain'), though it doesn't cover aspects like error handling, rate limits, or authentication requirements.

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 well-structured with clear sections (purpose, usage guidelines, circuits, returns) and uses bullet points for circuits. It is front-loaded with the core functionality and usage advice. However, the 'CIRCUITS' section is somewhat redundant with the schema's enum for 'circuit', and the separation into multiple paragraphs slightly reduces conciseness, though all content is relevant.

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 the tool's complexity (handling multiple circuits and steps) and the absence of annotations and output schema, the description does a good job of covering key aspects: purpose, usage, circuit details, and return information. It mentions sibling tools for alternatives and verification, but could benefit from more on error cases, performance, or security considerations to be fully complete for such a multifaceted tool.

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 all six parameters thoroughly. The description adds minimal parameter-specific information beyond the schema, such as noting that 'scope' defaults to 'proofport' if omitted (which is also in the schema) and listing circuit names in a separate 'CIRCUITS' section. It provides some context for circuit usage but doesn't significantly enhance parameter understanding beyond the schema's comprehensive descriptions.

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 tool's purpose as 'All-in-one ZK proof generation' with specific verbs ('prepare inputs, request challenge, and submit proof') and distinguishes it from sibling tools by contrasting with 'prepare_inputs, request_challenge, and submit_proof individually.' It explicitly names the resource (ZK proof) and the three-step process it handles.

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 ('Use this when you want the simplest path to a proof') and when to use alternatives ('For fine-grained control over each step, use prepare_inputs, request_challenge, and submit_proof individually'). It names specific sibling tools as alternatives, offering clear context for selection.

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