Find similar components

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

Annotations already mark the tool as read-only, so the description doesn't need to restate that. It adds useful behavioral context: results are computed from the fetched registry index, and the score is a structural heuristic comparable only within one result set. These details prevent misuse and set expectations beyond what the schema or annotations provide.

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 tightly written sentences, front-loaded with the core purpose and followed by use cases and a caveat. Every sentence adds value, with no redundancy or fluff.

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 simple parameters, existing annotations, and an output schema, the description provides enough context: it explains the basis of relatedness, the nature of the score, and when to use the tool. The only minor gap is that it doesn't mention whether the registry index needs to be pre-fetched, but this is a small omission for a tool of this complexity.

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?

Both parameters (name and k) have clear descriptions in the schema, so the baseline is 3. The description doesn't add per-parameter semantics, but given the 100% schema coverage, it is not necessary for parameter understanding.

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 function: it finds components related to a given one via same group, shared categories, and composition edges. It also frames specific use cases ('what else is like this', finding variants), which distinguishes it from siblings like search_components or get_component.

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 gives clear context for when to use the tool (finding related components and variants) and adds a caveat that scores are structural heuristics, not embedding similarities. However, it does not explicitly name alternatives or state when not to use this tool, so it lacks explicit exclusions but provides sufficient situational guidance.

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