get_market_intel

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

The description adds value beyond the readOnlyHint annotation by listing the exact return fields (capacity, vacancy, pricing, etc.), providing clarity on what the tool retrieves. No contradictions with 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 front-loaded with purpose and includes an example and exclusions. It is reasonably concise, though the enumeration of return fields could be shortened without losing meaning.

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?

While the description covers the main parameter and lists return fields, three out of four parameters are undocumented. Given no output schema, the return listing helps, but the incomplete parameter documentation leaves significant gaps for a tool with 4 parameters.

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?

Of four parameters, only 'market' is explained via examples and slug explanation. The other three (metric, period, compare_to) are not described. With 0% schema coverage, the description fails to adequately compensate for the missing parameter details.

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 purpose: retrieving data-center market intelligence for a single market. It uses specific verbs (get, use when asking about), identifies the resource (market data), and distinguishes from siblings (rank_markets for multiple markets, get_facility for a facility).

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 states when to use (for one market) and when not to use (for ranking or facility), and provides alternative tool names. It also includes an example query with expected parameter format.

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