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

With no annotations, the description carries full burden. It transparently discloses that data comes from hand-run tests (not scraped) and outlines the return fields. It does not mention failure modes, rate limits, or authentication, but the core behavior is well-communicated.

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 long, front-loaded with the primary purpose, and contains no redundant information. Every sentence earns its place: the first details outputs, the second explains data source and provides usage examples.

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?

Given the tool is a single-parameter lookup with no output schema, the description fully covers the returned data structure, data provenance, and example usage. It includes sibling tool names for context but does not need to reference them explicitly.

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 single parameter 'name' is well-described in the schema (fuzzy-matched, case-insensitive). The description adds value by providing an example call with a concrete mapping of input to output, helping the agent understand expected values and result format.

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 the tool retrieves a forensic audit verdict for a single crypto casino, listing specific outputs (trust score, audit status, live test, license, review link). It distinguishes itself from siblings by emphasizing data from hand-run real-money tests, not scraped reviews.

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 provides concrete usage examples and question contexts (e.g., 'Is Duelbits legit?'). It implies single-casino lookups without explicit when-not-to-use or sibling alternatives, but the context is clear enough for an agent to infer appropriate use.

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