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nullpath-labs

nullpath MCP Client

discover_agents

Search for AI agents by capability, category, or query to find suitable options with pricing and reputation information.

Instructions

Search for agents by capability, category, or query. Returns a list of matching agents with their pricing and reputation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryNoSearch query (e.g., "summarize", "translate", "code review")
categoryNoFilter by category (e.g., "text", "code", "data")
limitNoMaximum results to return (default: 10)
Behavior2/5

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

With no annotations provided, the description carries full burden but only states it 'Returns a list of matching agents with their pricing and reputation'. It lacks details on behavioral traits such as pagination, rate limits, authentication requirements, error handling, or whether the search is case-sensitive. This is inadequate for a search tool with potential complexity.

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

Conciseness4/5

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

The description is appropriately sized with two concise sentences that front-load the core functionality ('Search for agents...') and follow with the return value. There's no wasted text, but it could be slightly more structured by explicitly separating search inputs from outputs.

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

Completeness2/5

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

Given the tool has no annotations, no output schema, and 3 parameters, the description is incomplete. It doesn't explain the return format (e.g., structure of the list, what fields are included beyond pricing and reputation), error conditions, or prerequisites. For a search tool with potential rich results, this leaves significant gaps for an AI agent.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already documents all parameters (query, category, limit) with descriptions. The description adds minimal value by listing the search criteria ('by capability, category, or query') but doesn't provide additional semantics beyond what's in the schema, such as how these parameters interact or examples of valid inputs.

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's purpose: 'Search for agents by capability, category, or query' with the specific verb 'search' and resource 'agents'. It distinguishes from siblings like 'lookup_agent' (likely single agent) and 'check_reputation' (specific attribute) by focusing on multi-criteria search. However, it doesn't explicitly contrast with 'get_capabilities' which might overlap.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives like 'lookup_agent' (for single agent lookup) or 'get_capabilities' (which might retrieve capabilities without searching). It mentions search criteria but offers no context about when this search is preferred over other sibling tools, leaving the agent to infer usage.

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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