Find Alternative Parts

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

The description adds valuable behavioral context beyond what annotations provide. While annotations already indicate this is a read-only, non-destructive, idempotent operation, the description adds practical details about performance implications ('filtering by footprint is slower'), sorting behavior ('sorted by stock'), and response structure. It doesn't contradict annotations, which already cover the safety profile adequately.

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 well-structured and efficiently organized. It starts with a clear purpose statement, provides usage context, then documents parameters in a structured format with bullet points for enum values, and concludes with return value information. Every sentence adds value without redundancy.

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's complexity (6 parameters, 0% schema coverage) and the presence of an output schema, the description provides excellent contextual completeness. It fully documents all parameters, explains behavioral aspects, provides usage guidance, and describes the return structure. The output schema handles the formal return specification, allowing the description to focus on semantic understanding.

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?

With 0% schema description coverage, the description fully compensates by providing comprehensive parameter documentation. It explains each parameter's purpose, provides examples (e.g., 'C2557'), documents defaults, enumerates valid values for library_type and has_easyeda_footprint with clear explanations, and offers practical guidance on parameter usage. This goes well beyond what the bare schema provides.

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 with specific verbs ('find alternative parts similar to a given component') and resources ('searches the same subcategory for parts with better availability'). It distinguishes itself from siblings like 'jlc_get_part' or 'jlc_search' by focusing specifically on finding alternatives rather than retrieving or searching for parts generally.

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 explicit guidance on when to use this tool ('useful when a part has low stock or you want to compare options'). It also offers specific usage advice within parameter descriptions, such as recommending 'no_fee' library type 'to find cheaper alternatives for an extended part' and noting that 'filtering by footprint is slower as it checks each alternative.'

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