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

Annotations declare readOnlyHint=false, idempotentHint=true, destructiveHint=false; the description explains why the read-looking tool is not read-only (it consumes an LLM run and is credit-gated) and adds the return cardinality (up to 6 entries) plus the full fail-open contract with a 'note' field. That is substantive context beyond the annotations rather than repetition.

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?

Four tight sentences, front-loaded with what it does, followed by return shape, the sibling contrast, the cost gate, and the failure semantics. No filler and no repetition of the schema.

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?

With no output schema, the description carries the return contract (up to 6 'missing' entries with name and hint) and the failure behavior, which is exactly what an agent needs. Nothing material for correct invocation is missing.

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?

Single parameter with 100% schema description coverage ('Project id (from lab_list_projects) — positive integer as string'), so the schema already does the work. The description adds no syntax or format detail beyond it; 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 precise verb+resource and scope: finds people present in a project's material but lacking a character sheet. It explicitly distinguishes itself from lab_cast_autopopulate ('It creates nothing — lab_cast_autopopulate does that'), so an agent can route 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?

Names the alternative sibling and the division of labor (this finds gaps, the other creates), and flags the cost gate ('costs an LLM run, so it is credit-gated'), which tells the agent to call it deliberately rather than speculatively. The fail-open note also tells the agent not to treat an empty list as a failure.

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