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 key behaviors: it's an on-chain verification, extracts verification info automatically, and returns { valid: true } if valid. However, it doesn't cover error cases, permissions, rate limits, or what happens if the proof is invalid.

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 highly concise and well-structured: two sentences that front-load the purpose and usage, with zero wasted words. Every sentence earns its place by providing essential information about what the tool does and how to use it.

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 complexity (on-chain verification with no annotations and no output schema), the description is moderately complete. It covers the basic operation and input handling but lacks details on error handling, return format beyond success case, and integration with sibling tools. For a tool with significant implications (on-chain operations), more context would be beneficial.

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 fully documents the single parameter 'result' and its nested properties. The description adds value by emphasizing to 'pass the full generate_proof result object directly' and that verification info is extracted automatically, but doesn't provide additional semantic context beyond what's in the schema.

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: 'Verify a ZK proof on-chain against the deployed verifier contract.' It specifies the action (verify), resource (ZK proof), and context (on-chain, against verifier contract). However, it doesn't explicitly differentiate from sibling tools like 'submit_proof' or explain how verification differs from submission.

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 clear context: 'Step 4 (optional)' and 'Pass the full generate_proof result object directly.' This indicates when to use it (after proof generation) and what input to provide. It mentions it's optional but doesn't specify when to skip it or alternatives to this tool.

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