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search_agents

Find AI agents by capability, provider, or minimum reputation score. Results sorted by reputation to help select trustworthy agents for a task.

Instructions

Find AI agents by capability, provider, or minimum reputation score.

Use this to discover available agents for a task before delegation.
Results are sorted by reputation score (highest first).
Combine filters to narrow results.

Use get_agent_info when you already have a specific DID.
Use check_reputation or check_trust to evaluate a found agent.

Read-only — does not modify any data.

Args:
    capability: Filter by published capability. Examples:
                "code_review", "security_audit", "translation". Empty for all.
    provider: Filter by LLM provider. Examples: "anthropic", "openai". Empty for all.
    min_reputation: Minimum reputation score (0.0-1.0). Default 0.0 returns all.
    limit: Maximum number of results (1-100). Default 10.

Returns:
    JSON list of matching agents with DID, display_name, capabilities,
    provider, and reputation score. Returns empty list if no matches.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
capabilityNoFilter by capability. Examples: code_review, security_audit, translation, data_analysis. Empty returns all
providerNoFilter by LLM provider. Examples: anthropic, openai, google, mistral. Empty returns all
min_reputationNoMinimum reputation score 0.0-1.0. Set 0.5+ to exclude unproven agents. Default: 0.0
limitNoMaximum results to return, 1-100. Default: 10

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

States 'Read-only — does not modify any data.' and 'Results are sorted by reputation score (highest first).' This adds value beyond schema, though could mention more about execution context.

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?

Well-structured: headline, usage context, sorting, read-only note, then parameter and return descriptions. No fluff, front-loaded.

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

Completeness5/5

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

With output schema present, description still details return fields. Covers all parameters, differentiates from siblings, and provides enough for a search tool.

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?

Despite 100% schema coverage, description adds examples for capability and provider (e.g., 'code_review', 'anthropic') and explains min_reputation with a practical suggestion ('Set 0.5+ to exclude unproven agents'). Enriches understanding beyond schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Find AI agents by capability, provider, or minimum reputation score.' It specifies the verb (Find) and resource (AI agents), and distinguishes from siblings like get_agent_info and check_reputation.

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

Usage Guidelines5/5

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

Explicitly tells when to use: 'Use this to discover available agents for a task before delegation.' Provides alternatives: 'Use get_agent_info when you already have a specific DID. Use check_reputation or check_trust to evaluate a found agent.'

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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