health_check

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

With no annotations, the description carries the burden. It discloses that probing uses a trivial query and reports status/latency/flags, plus timeout defaults, but omits whether the operation is read-only/non-destructive, any auth or cost implications, and how many adapters are hit by default.

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, front-loaded with what it does followed by when to use it. No wasted words.

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-annotation, no-output-schema diagnostic tool, the description compensates by describing the return payload (status, latency, capability flags) and the triggering scenarios. Minor gap is the lack of explicit safety/non-destructive confirmation.

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 coverage is 100%, so both parameters (chains, timeoutMs) are already well documented with defaults and bounds. The description adds no meaning beyond the schema, so baseline 3 applies.

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?

States a specific verb (probe) and resource (registered chain adapters) and enumerates the reported outputs (status, latency, capability flags). This clearly separates it from data-fetching siblings like find_stores and search_products, though it doesn't name them explicitly.

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?

Gives concrete triggering conditions: 'when a chain seems missing from results' or 'when debugging adapter problems.' Clear context, but doesn't explicitly name the alternative data tools or state when NOT to use it.

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