Check connection

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

The readOnlyHint annotation already signals safety, and the description adds relevant behavioral context: token identity is attributed to every recorded change, and caller identity may be forwarded by a gateway. This goes beyond the annotation without contradicting it.

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 two sentences with the core action first, followed only by consequential detail about attribution and caller identity. There is no fluff or repetition of the title.

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 tool, the description conveys the main outputs: deployment capabilities, token owner, and caller identity. It does not specify exact response formatting or failure behavior, but the tool's simplicity and readOnly annotation make this a minor gap.

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 has zero parameters and the empty schema fully describes the input surface, so there is nothing for the description to add about parameter semantics. The baseline of 4 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?

The description opens with a specific verb and resource: 'Verify the token and organization' and states what the tool reports (deployment capabilities, token owner, caller identity). This makes its role distinct from sibling data-operation tools like productive_get or productive_create.

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 clearly establishes the context — validating the Productive token and organization and surfacing what the deployment can do — so an agent knows to call it for connection/auth checks. It does not explicitly name alternatives or when-not conditions, but the absence of parameters and the verification purpose make the intended use obvious.

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