get_opportunities

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

With no annotations, the description carries full responsibility and succeeds. It discloses the paid nature ($0.02 via x402), the exact response behavior (up to 50 cards, each with teaser and summary), error behavior (no-charge 400 for invalid category), payment settlement details (USDC on Base, compute-first, settle-after), and the prerequisite EVM_PRIVATE_KEY. This is exemplary transparency.

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?

Every sentence adds essential information: pricing, return shape, required and optional parameters, error behavior, payment mechanics, and setup requirement. The description is front-loaded with the most critical fact (cost) and remains tightly structured with no filler, making it highly efficient for an AI agent to parse.

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?

There is no output schema, so the description compensates by explaining the return shape (up to 50 opportunity cards, each a teaser plus summary) and error responses. Combined with the parameter schema, payment details, and setup instructions, it gives a complete picture of expected behavior and prerequisites, leaving no major ambiguities.

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?

The input schema already documents both parameters with 100% coverage, so the baseline is 3. The description adds value by explaining the consequence of an unknown/missing category (no-charge 400 listing valid categories) and reiterating the minScore 0-100 range, which provides operational context beyond the schema's static property definitions.

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 returns up to 50 opportunity cards per category, each with a teaser and summary. The plural 'opportunities' and category scope distinguish it from the sibling get_opportunity, and the specific verb 'get' plus resource 'opportunity cards in a category' make the purpose unambiguous.

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 explicitly requires a category and mentions the optional minScore filter, giving clear context for when to use the tool. It does not explicitly name alternatives like get_categories or get_trending_opportunities, but the error handling hint ('unknown/missing category → 400 listing valid categories') implies how to recover from a missing category. This is clear context without explicit exclusions.

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