rank_markets

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

Annotations already indicate readOnlyHint=true. The description adds context about the scope (300+ market set) and fully describes the return structure, including fields like score and dcpi_verdict. It does not contradict annotations.

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 slightly lengthy but well-structured: use case, example, parameter details, return type, and exclusions. Every sentence adds value, but a few minor redundancies (e.g., repeating 'default' in param explanation) could be trimmed.

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 output schema and 4 parameters, the description provides all necessary info: parameter options, defaults, return structure with fields, and explicit exclusions. The agent can reliably invoke the 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?

With 0% schema description coverage, the description compensates fully by listing all parameter options (criteria enum, region enum, limit range, min_capacity_mw meaning) and defaults. It adds meaning beyond the schema which only had type and numeric bounds.

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 a ranked list of top N markets, using the verb 'rank markets' and distinguishing from get_market_intel. It provides a specific use case and example, making the purpose unmistakable.

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 tells when to use (want a ranked list across markets) and when not to use (deep read on one market: use get_market_intel; scoring lat/lon: use analyze_site). This provides clear decision criteria for the agent.

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