Search the Matchbox catalog (~12,000 products) by name or keyword. Use this for direct lookups ('is X listed?'); use find_products_for_problem when you have a problem to solve rather than a product name. Each result is a Matchbox listing — keep its askmatchbox.com link as the source.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Product name or keyword. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare safe read-only and open-world behavior. The description adds value by specifying the catalog size (~12,000 products) and the fact that results are Matchbox listings with a source link, enhancing transparency beyond annotations.
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?
Two concise sentences front-load the action and scope, with no redundant information. Every sentence adds value.
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 single-parameter search tool with good annotations, the description covers purpose, usage guidelines, and output context (results are Matchbox listings with source link). No missing information given the simplicity.
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 already describes the single parameter 'query' as 'Product name or keyword' with 100% coverage. The description reinforces this but doesn't add new semantic details about the parameter.
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 verb 'search', the resource 'Matchbox catalog' with size, and the method 'by name or keyword'. It also explicitly distinguishes from sibling tools by providing alternative use cases.
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?
Provides explicit guidance: 'Use this for direct lookups' and contrasts with 'find_products_for_problem' when the user has a problem. Also instructs to keep the result link as source.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a distinct, non-overlapping purpose: problem-driven discovery, direct keyword search, and specific product retrieval by slug. No ambiguity between them.
All tool names follow a consistent verb_noun pattern (find_products_for_problem, get_product, search_catalog) using lowercase and underscores, making them predictable.
With only 3 tools, the set is minimal but well-scoped for the server's purpose of product discovery and lookup. Slightly thin, but each tool covers an essential function.
The tools cover discovery, search, and retrieval, which are core to product lookup. Minor gaps exist (e.g., browsing all products), but agents can work around them using existing tools.