Get CAI methodology and discovery

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

The annotations already declare readOnly, openWorld, idempotent, and non-destructive behavior, so the description does not need to repeat those. It does add useful context about the document's contents and its canonical nature, but it does not disclose additional behavioral details such as response format, pagination, or any operational side effects. This is acceptable given the rich annotation set.

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 a single sentence that front-loads the core action and resource ('Return CAI's canonical machine discovery document') and then efficiently lists the key contents. There is no fluff, repetition, or unnecessary detail.

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 parameterless, read-only retrieval tool with no output schema, the description adequately conveys what the agent will receive, including scope, methodology version, endpoint links, and Score/Confidence semantics. Combined with the annotations, it provides everything needed to select and invoke this tool correctly.

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 input schema has zero parameters and schema description coverage is 100%, so there is no parameter gap for the description to compensate for. The description correctly focuses on what the tool returns rather than nonexistent inputs, which is appropriate for a parameterless endpoint.

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 a specific verb ('Return'), a specific resource ('CAI's canonical machine discovery document'), and enumerates its contents (scope, methodology version, endpoint links, Score/Confidence semantics). This distinguishes it sharply from the sibling tools, which analyze assets, retrieve job status, or list assets.

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 makes the tool's use case obvious: use it whenever the CAI discovery/methodology document is needed. It does not explicitly name alternative tools or exclusion conditions, but none of the siblings are plausible substitutes for retrieving this canonical document, so the guidance is adequate.

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