proven_fits

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

There are no annotations, so the description carries the transparency burden. It discloses the data source (recent killmails) and the output nature (module frequencies per slot), implying a read-only operation. However, it does not mention edge cases like insufficient killmail data, ship name validation, or whether authentication is needed. The description adds context beyond the basic function but lacks depth on failure modes.

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: the first states the core functionality and output, the second provides usage guidance. It is front-loaded, information-dense, and free of fluff. Every sentence earns its place.

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 relatively simple lookup tool with 2 parameters and no output schema, the description explains what it returns (common modules per slot with frequencies) and how to use it. It lacks details on error behavior or data freshness, but it is sufficient for an agent to select and invoke the tool correctly in most scenarios.

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?

Input schema covers both parameters with descriptions (100% coverage), so the baseline is 3. The tool description does not add significant new meaning to the parameters; it merely reinforces that data comes from recent killmails, which is already implied by the sample parameter. No additional semantic value beyond the schema.

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's purpose: it shows the most common modules pilots use per slot on a given ship, learned from recent killmails. This specific output distinguishes it from siblings like analyze_fit (which checks a specific fit) and can_i_fly (which checks requirements). The verb 'learned' and the resource 'killmails' make the function 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?

The description explicitly says to use it for proposing a realistic starter fit, and then sanity-check with analyze_fit and can_i_fly. This provides clear workflow guidance and names alternatives for subsequent steps. It effectively tells the agent when to invoke this tool versus others.

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