List applications inside a specific category, paginated. Use this when the user wants to explore an area rather than search for a specific tool.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Page size. | |
| offset | No | Number of results to skip for pagination. | |
| linkName | Yes | The category linkName (e.g. 'image-generation'). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of disclosing behavior. It mentions pagination and scoping to a category, which are useful. However, it does not explicitly state that it is a read-only operation, nor does it describe error behavior or return format. For a simple read tool, this is adequate but not rich.
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 two sentences, front-loaded with the primary function and immediately followed by usage guidance. No wasted words.
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?
Given the simplicity of the tool (list with pagination) and the comprehensive parameter schema, the description covers the essential context. Since there is no output schema, a brief note on return structure would enhance completeness, but the current information suffices for a tool of this complexity.
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 coverage is 100%, with each parameter having a description. The description itself adds no additional parameter semantics beyond what the schema already provides, so the 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's function: listing applications within a specific category, with pagination. It explicitly distinguishes itself from searching or getting a specific tool, making it distinct from siblings like search_tools and get_tool.
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 provides explicit guidance on when to use this tool: when exploring an area rather than searching for a specific tool. This directly contrasts with search_tools and clarifies the intended use case.
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 clearly distinct purpose: browsing a category, comparing two tools, finding alternatives, fetching tool details, getting top picks, listing categories, and searching. There is no ambiguity or overlap.
All tool names follow a consistent verb_noun pattern in snake_case (e.g., browse_category, compare_tools, get_tool). The naming is predictable and uniform across the set.
With 7 tools, the set is well-scoped for an AI tool directory. Each tool serves a specific and necessary function, and there is no unnecessary bloat or deficiency.
The tool surface covers all core use cases for a directory: browsing by category, searching, getting details, comparing, and finding alternatives. Minor gaps like missing 'top trending' or user-specific features are acceptable and do not hinder typical workflows.
