query_schema

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

With zero annotation coverage the description carries the full burden, and it discloses the non-obvious inference mechanism ('inferred from current value + database metadata') plus ambiguity-handling guidance ('ask the user for clarification'). It omits explicit read-only/safety framing and error behavior for unknown records, but the added behavioral context goes beyond what 'Get' alone conveys.

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?

Front-loaded with purpose and return shape, then use-case, then inference note, then a tip. Every sentence carries information, though the semantic-naming tip is marginally advisory rather than essential.

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 must characterize the return, which it does at a high level ('data structure, field types, and metadata'). Combined with a 100%-covered input schema and the inference note, an agent has enough to call it correctly, though return-format specifics are unstated.

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 already documents endpoint, record_name, and include_example, including the env-var fallback. The description adds no parameter-level detail, so the baseline 3 is appropriate.

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 states a specific verb and resource ('Get JSON schema and type information for a record') and clarifies the output ('data structure, field types, and metadata'), which is clearly distinct from the value-fetching sibling get_record. It stops short of naming a sibling explicitly, so the differentiation is implied rather than stated.

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?

'Use this before setting record values to understand expected format' gives a concrete when-to-use trigger tied to set_record. There is no when-not guidance or named alternative, but the context is clear enough for an agent to place it in a workflow.

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