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

Annotations only cover read-only/idempotent/open-world safety, and the description adds far more: the three-way outcome semantics, the explicit warning that 'no record' reflects coverage and not conduct, the prospective-census data origin with a start date, and the empirical hit rates with intervals. This is exactly the behavioral context an agent needs to avoid misreporting results.

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?

Front-loaded with the core definition, then cleanly sectioned into outcomes, evidentiary value, negative-screen disclaimer, and case rule. It is longer than most descriptions, but nearly every sentence carries substantive meaning; the phrasing 'and whether every one of them did' is slightly awkward filler.

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 full burden of explaining return semantics, and it does so completely — the three outcomes, what each means, and the trap of misreading 'no record'. An agent can report results correctly from this text alone.

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% and the description's case-sensitivity note largely restates the schema's own 'exact case' warning. It reinforces the consequence but does not add new parameter semantics beyond what the schema already documents, so baseline 3 is appropriate.

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 opening sentence names a specific subject (what the deployer wallet has done across past launches) and even explains why it can answer a deployer question rather than a token question, which separates it from the sibling solana_token. The three-outcome taxonomy makes the exact deliverable concrete.

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?

It gives explicit trigger conditions ('who made a Solana token', 'whether a deployer has a history', 'whether a launch's creator has ever had one survive') and explicit exclusions ('never restate it as a recommendation, a risk score, or a safety verdict'). Usage boundaries are unambiguous.

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