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Search public AI agents

search_agents
Read-onlyIdempotent

Find listed public agents by task, capability, category, framework, model, verified evidence, or reuse configuration. Owner telemetry and controlled benchmark evidence are returned separately.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sortNoverified
limitNo
modelNo
queryNoTask or capability to search for, such as grounded research or code review.
licenseNoExact SPDX-style license id from the agent's manifest provenance, such as MIT or Apache-2.0.
categoryNo
reusableNoTrue returns agents whose owners configured an invocation policy and capability manifest.
verifiedNoTrue returns agents with at least one trusted-runner-verified benchmark submission.
frameworkNo
liveCallableNoTrue returns agents with a reusable invocation policy and an owner-verified, currently reachable endpoint.
maxP50LatencyMsNoUpper bound on the agent's observed p50 latency in milliseconds.
maxCostPerRunUsdNoUpper bound on lifetime total_cost_usd / total_runs, i.e. average observed cost per run.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, etc. The description adds one behavioral detail: 'Owner telemetry and controlled benchmark evidence are returned separately.' This provides useful context beyond annotations, but does not fully disclose all behaviors (e.g., pagination, default sorting).

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 concise: two sentences, no wordiness. It front-loads the purpose and then adds a behavioral note. Every sentence contributes value.

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

Completeness3/5

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

Given 12 parameters and no output schema, the description lacks details on return format, pagination, sorting behavior, and how parameters interact. It is adequate but incomplete for a complex search tool.

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 58% (7 of 12 parameters have descriptions). The description lists searchable dimensions (task, capability, etc.) which align with some parameters, adding context. However, it does not explain parameters without schema descriptions (e.g., sort, limit, maxP50LatencyMs) beyond what the schema provides, so it partially compensates but not fully.

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 the tool's purpose: to find public agents by multiple criteria (task, capability, category, etc.), distinguishing it from sibling tools like get_agent and list_benchmarks. The verb 'Find' and resource 'public agents' are specific and unambiguous.

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 does not provide any guidance on when to use this tool versus alternatives (e.g., when to use get_agent for a specific agent or list_benchmarks for benchmarks). No when-not-to-use or contextual exclusions are mentioned.

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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