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

Annotations already declare readOnlyHint=true, idempotentHint=true and destructiveHint=false, so safety is covered. The description adds value by disclosing the return shape (one row per platform plus an identifier count), which is not encoded in annotations or an output schema.

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, no filler: the first describes the output, the second states the purpose. The retrieval-relevant use case is front-loaded and nothing is repeated from the title or annotations.

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 vocabulary tool with no output schema, the description fully covers what an agent needs: what is listed, what accompanies each entry (counts), and why it matters for lookup_project.

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 zero parameters, so the baseline is 4. The description still adds downstream semantics by tying the result to the 'platform argument of lookup_project', which is the only parameter meaning an agent needs to infer.

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+resource ('List every platform PulseGate records identifiers on') and adds the returned dimension ('with how many identifiers it holds for each'). It also names its relationship to the sibling lookup_project, so an agent can distinguish it without opening either schema.

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 an explicit use case: 'Use it to learn the vocabulary the platform argument of lookup_project accepts.' That clearly routes the agent here before calling lookup_project, though it does not state any exclusions or cases where this tool should be skipped.

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