health_schema

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

With no annotations, the description carries the full burden. It discloses the tool's informational nature and enumerates what it returns (tables, semantic layer, metrics, aggregations, traps). It could be more transparent about potential access limitations or output size, but the core behavior is clearly conveyed.

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?

Two sentences, with the main action front-loaded in the first sentence and a clear directive in the second. No redundant words or filler; every clause earns its place.

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?

For a zero-parameter metadata listing tool, the description fully covers what it does, what it returns, and when to use it. The lack of output schema is not an issue because the description itself enumerates the semantic content, and the sibling tools are clearly distinct.

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?

There are zero parameters, and the schema description coverage is 100% (trivially). The description adds contextual meaning about the tool's purpose and return value, satisfying the baseline for parameter-less tools.

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 identifies the tool as listing every health table and returning a curated semantic layer, including metric definitions, valid aggregate functions, and known data traps. This specific verb-resource pairing distinguishes it from the sibling tools health_report and health_query.

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 explicit instruction 'Call this before writing any query' provides clear when-to-use guidance, implying it is a prerequisite for data querying and reporting. This effectively differentiates it from health_query and health_report, which are for actual data retrieval.

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