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Search products

search_products
Read-onlyIdempotent

Search the directory with a natural-language query and optional structured filters (category, free tier, API, MCP, open source). The query is matched by full-text and semantic similarity, so phrasing it like a need ("send transactional email with a free tier") works well. Returns up to limit products (default 10, max 50) plus a separate sponsored list.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryNoNatural-language query in any language. Omit to browse by filters only.
has_apiNoOnly products with an API.
has_mcpNoOnly products that offer an MCP server.
categoryNoRestrict to one category id (see the toolgrep://categories resource).
open_sourceNoOnly open-source products.
has_free_tierNoOnly products with a free plan or free usage allowance.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemsYes
sponsoredYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, closed-world). The description goes beyond them by disclosing the result shape: up to `limit` products plus a separate `sponsored` list, and that results combine full-text with semantic similarity. It does not mention ranking, pagination, or empty-result behavior.

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?

Three tight sentences: what it searches, how to phrase the query, and what comes back. The most decision-relevant information (query mode and filters) is front-loaded, and the result-shape caveat is last.

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?

With an output schema present, the description needn't explain return values, yet it still flags the `sponsored` list — a meaningful behavioral detail. What's missing is guidance on the sibling tools and on whether results are ranked or paginated, which matters for a search entry point.

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 86%, so the baseline is 3, but the description adds real value: the default (10) and cap (50) for `limit` are not in the schema, and it enumerates the filter dimensions (category, free tier, API, MCP, open source) in one place. It adds nothing further on the query semantics beyond match mode.

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?

States a specific verb+resource ('search the directory') plus the two search modes (natural-language query and structured filters), which is more precise than the title. It does not name or differentiate itself from siblings such as find_alternatives or compare_products, so an agent must infer the boundary.

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?

It gives useful usage context — phrase the query like a need, and omit the query to browse by filters only — which implies when this tool is appropriate. However, it never states when NOT to use it or which sibling to pick instead (e.g. find_alternatives for substitutes, get_product for a known item).

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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