sparkfun_search

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

No annotations are provided, so the description carries the full behavioral burden. It does disclose that the data is 'public' and adds a meaningful behavioral constraint for filters ('use values from the response's filters array'). It does not address auth, rate limits, response shape, or side effects — though 'public search' implies a safe read operation.

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 short and front-loaded, with the core search action first and filter specifics last. There is minor redundancy between 'Search SparkFun products' and 'Searches public SparkFun product data', but the extra clauses (pagination, facet format, filter value source) each earn their 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?

All four parameters are fully documented in the schema, and the description covers the important operational details: public data, pagination, dynamic facets, and valid filter-value sourcing. There is no output schema, so the description could do a bit more about the expected return holds, but for a search tool with fully documented parameters it is largely complete.

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 100%, so the baseline is 3 even with no parameter info. The description adds real value beyond the schema by constraining filter values to come from the response's filters array, which is not captured in the schema's 'attribute:value' description. This helps an agent construct valid filter inputs.

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 states a specific verb and resource ('Search SparkFun products') and adds key context: it searches public product data with pagination and dynamic facets. It doesn't explicitly name and contrast sibling tools like sparkfun_category or sparkfun_product, but the search-vs-category/product distinction is reasonably inferable.

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 implies usage: use this when you need to search SparkFun products, and it mentions pagination/facets as part of that usage. However, it gives no explicit guidance on when to prefer this over alternatives such as sparkfun_category, sparkfun_product, or other e-commerce search tools, and no when-not-to-use guidance.

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