Search the AICatalog directory of 20,000+ AI tools by keyword. Returns matching tools with name, tagline, catalog URL and pricing.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max results (1-25). | |
| query | Yes | Search keywords, e.g. 'video editing'. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It describes the return fields (name, tagline, catalog URL, pricing) but does not disclose ordering, pagination, or potential limitations like partial matches or rate limits.
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 with no wasted words. The purpose and return values are front-loaded.
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 simple search tool with two parameters and no output schema, the description adequately covers what the tool does and what it returns. Missing details like pagination are not critical for basic 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?
Schema description coverage is 100% with both parameters having descriptions. The tool description does not add semantics beyond the schema, so baseline of 3 applies.
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 searches an AICatalog of 20,000+ AI tools by keyword and returns specific fields. It effectively distinguishes from siblings (get_tool, list_categories) by focusing on keyword-based search.
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 for keyword searching and explicitly states what is returned. However, it does not explicitly contrast with alternatives like get_tool for specific tool details or list_categories for browsing by category.
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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Each tool has a clearly distinct purpose: search returns a list, get details a single item, and list categories provides taxonomy. No overlap.
All tools follow a consistent verb_noun pattern in snake_case: search_ai_tools, get_tool, list_categories.
Three tools are perfectly scoped for a read-only AI tool catalog: search, detail retrieval, and category listing. No excess or deficiency.
The surface covers the essential operations for browsing a catalog: searching, viewing details, and navigating categories. No missing CRUD that would hinder an agent.