get_api_status

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

With no annotations, the description carries the full burden; it does establish this is an aggregate read that returns counts and recency information. It does not state whether results are cached/live, how 'current' is measured, or any rate or auth constraints. Adequate for a zero-parameter read but not rich.

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: the first states the returned metrics, the second states the call condition. It is front-loaded with the payload and has no filler.

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 no-param, no-output-schema stats tool, the description effectively stands in for a return schema by enumerating the metrics. Only the response shape/format is left unspecified, which is a minor gap given how simple the output is.

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?

The tool takes no parameters, so there is nothing for the description to disambiguate and the baseline of 4 applies. The description correctly implies no scoping inputs are needed.

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 names a concrete resource and enumerates the returned metrics (total articles, total claims, verdict-carrying claims), so the agent knows exactly what it gets. It implicitly separates itself from the listing siblings (list_debates, list_recent_claims) by framing this as corpus-meta rather than content retrieval, though it never names them. It also usefully overrides the misleading tool name, which suggests API health rather than corpus statistics.

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?

'Call this for corpus-meta questions' plus three concrete question shapes (how much data, what it covers, how current) gives a clear use condition. No explicit exclusions or named alternatives are given, so the agent must infer that per-claim or per-debate lookups belong to the siblings.

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