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sparkfun_category

Browse a SparkFun category to get paginated public products and dynamic facet filters; apply attribute:value filters using values from the response filters array.

Instructions

Browse a SparkFun category. Returns paginated public products and dynamic facet filters for a SparkFun category URL key. Each filter must be attribute:value; use values from the response's filters array.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoOne-based result page (1-100)
filterNoRepeatable dynamic facet in attribute:value form
url_keyYesSparkFun category URL key
per_pageNoProducts per page (1-24)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.17.5
    • addedInput schema / properties / filter / items
      Added value: +{
+  "type": "string"
+}
  2. Addedv1.16.2

TDQS

A3.9/5.0
Behavior4/5

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

With no annotations provided, the description carries the burden of behavioral disclosure. It usefully states that products are 'public,' that results are paginated, and that filters must come from the response's filters array. It does not cover response shape or rate limits, but for a read-only browse tool this is reasonably transparent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences with no filler. It front-loads the core purpose, then immediately gives the critical filter constraint. Every sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the absence of annotations and an output schema, the description covers the essential invocation details: what the tool returns, how pagination works via the schema, and how to construct valid filters. It could mention how to discover a valid url_key, but that is likely covered by the sibling sparkfun_categories tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3. The description adds meaningful parameter guidance beyond the schema: filters must use `attribute:value` and values should be taken from the response's filters array. This prevents an agent from inventing filter values.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool browses a SparkFun category and returns paginated public products plus dynamic facet filters. This distinguishes it from sibling tools like sparkfun_product and sparkfun_search in general terms, though it does not explicitly name an alternative.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage: use this when browsing a category by its URL key. However, it gives no explicit guidance on when to prefer this over sparkfun_search or sparkfun_categories, and no exclusions or alternatives are mentioned.

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

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