Catalog Search

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

Annotations already declare readOnlyHint and openWorldHint, but the description adds substantial behavioral context: 'Offline, deterministic, zero network'; availability is a 'curated snapshot of a MARKET, not physics'; and users must 'read not_covered before concluding from an empty result that a part does not exist.' This meaningfully clarifies the semantics of empty results and the trustworthiness of the data.

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 long but every section earns its place: purpose is front-loaded, then use-case differentiation, then a compact parameter reference, then return-shape and caveats. The list of parameters is scannable, and the behavioral warnings are placed where they matter most.

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 10-parameter search tool with no output schema and minimal annotations, the description is remarkably complete. It defines the return shape, the meaning of fields like `lengths`, `market`, and `captured`, and gives a concrete example ('ISO 4762 M4×12 is a stocked item and an M4×13 is not'). An agent has enough context to invoke the tool correctly and interpret results.

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 description coverage is 0%, so the description carries the full burden, and it delivers. It documents every argument: family with allowed values, standard with alias examples, kind with example tags, size with measurement types, length with exact or min/max window, grade with examples, drive with enum values, and limit with default. This far exceeds the bare type-only 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 opens with a specific verb and resource: 'Browse the off-the-shelf catalog' and immediately defines what the tool answers: which standard components exist, in which sizes, in which stocked lengths. It further distinguishes itself from dimensional corpora and states that 'nothing else in AnkusDrive knows' this information, clearly separating it from measurement or geometry tools.

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 when-to-use guidance: 'Call it while designing, before you commit geometry to a number.' It also contrasts with the dimensional corpora ('tell you what a part measures') and this tool ('whether it is a thing you can buy'), effectively explaining when not to use alternatives. No exclusions are left to inference.

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