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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the description doesn't need to restate read-only behavior. It adds valuable context beyond annotations: the cost ($0.01 USDC), accepted payment methods, and that results are AI-classified and scored. These are useful behavioral traits not evident from annotations alone.

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 a moderately long paragraph but every sentence adds value: purpose, return type, usage examples, alternatives, cost, and payment methods. It is dense but not wasteful; a slightly more structured format (e.g., bullet points) could improve scannability, but it remains efficient for the amount of information.

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 moderate complexity (scanning multiple sources, AI classification, cost, payments) and no output schema, the description provides a complete enough picture: what it returns, when to use it, cost, and payment methods. It doesn't mention result limits or pagination, but for a scan tool with good annotations, this is adequate without being exhaustive.

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 coverage is 100% with clear descriptions for both parameters (days and min_score), so the schema already carries the load. The tool description itself does not add parameter-specific details beyond what's in the schema, though it mentions scoring out of 20 in the min_score schema. This meets the baseline for high schema coverage.

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 uses a specific verb ('Scan') and clearly identifies resources (GitHub, Hacker News, npm) and the target domain (agent payments ecosystem). It also distinguishes itself from siblings by stating it returns AI-classified and scored opportunities with recommended actions, and explicitly names alternatives for other use cases.

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 direct usage guidance: 'Use when the user asks about recent activity, new developments, or opportunities in agent payments' with example queries. It also explicitly says to use get_protocol_info for static protocol details and compare_protocols for side-by-side comparison, covering both when-to-use and alternatives.

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