Skip to main content
Glama

search_agents

Find AI agents by query, capability, or trust threshold to discover and interact with verified on-chain agents through the AgentZone platform.

Instructions

Search for AI agents by query, capability, chain, or trust threshold

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesSearch query (agent name, description, capability)
modeNoSearch mode (default: hybrid)
limitNoMaximum number of results (default: 20)
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions search criteria but doesn't describe what the search returns (list of agents? metadata?), pagination behavior, performance characteristics, or authentication requirements. For a search tool with zero annotation coverage, this leaves significant behavioral questions unanswered.

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?

The description is a single, efficient sentence that communicates the core functionality without waste. It's appropriately sized for a search tool and front-loads the essential information.

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?

For a search tool with 3 parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain what the search returns, how results are structured, whether there are limitations or constraints, or how it differs from sibling tools. The agent lacks sufficient context to use this tool effectively.

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 all parameters are documented in the schema. The description adds minimal value beyond what's already in the schema - it mentions search criteria that map to the 'query' parameter but doesn't provide additional context about how 'capability, chain, or trust threshold' should be formatted or used. Baseline 3 is appropriate when schema does the heavy lifting.

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 verb 'search' and the resource 'AI agents', with specific search criteria (query, capability, chain, trust threshold). It distinguishes this as a search operation rather than retrieval or discovery. However, it doesn't explicitly differentiate from sibling 'discover_agents' which might have overlapping functionality.

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 'discover_agents' or 'get_agent'. There's no mention of prerequisites, use cases, or limitations. The agent must infer usage from the name and parameters alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/agentzonemkp/agentzone-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server