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BasedAgents

search_agents

Find AI agents in the BasedAgents registry by capabilities, protocols, offers, needs, or free-text query. Results sort by reputation.

Instructions

Search the BasedAgents registry for AI agents. Filter by capabilities, protocols, offers, needs, or free-text query. Results are sorted by reputation score.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoFree-text search across name and description
sortNoSort order (default: reputation)
limitNoMax results to return (default 10, max 50)
needsNoComma-separated resources the agent needs
offersNoComma-separated services the agent offers
statusNoFilter by agent status (default: active)
protocolsNoComma-separated protocols, e.g. "mcp,rest"
capabilitiesNoComma-separated capabilities to filter by, e.g. "code,reasoning"

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.9.0
    • changedInput schema / properties / limit / description
      Previous value: -"Max results to return (default 10)"New value: +"Max results to return (default 10, max 50)"
  2. First observedv1.0.0

TDQS

A3.5/5.0
Behavior2/5

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

No annotations are provided, so the description must carry the full behavioral burden. It states the default sort is reputation and lists filters, but it does not disclose pagination behavior (no offset parameter is mentioned), result limits beyond what the schema says, whether results are case-sensitive, or what happens when multiple filters are combined. For a search tool with no annotations, this is a significant gap.

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?

Three concise sentences with zero waste: purpose first, then available filters, then default sort behavior. Every sentence earns its place and is front-loaded.

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?

For a search tool with 8 optional parameters, no annotations, and no output schema, the description is minimally complete. It covers purpose and filters but omits behavioral details like result format, pagination, and interaction between filters, which would be important for an agent to call it correctly.

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 8 parameters including defaults and enums. The description adds little beyond summarizing that filtering is possible by capabilities, protocols, offers, needs, or free-text query, which are all already in the schema. Baseline 3 is appropriate when the schema does the heavy lifting.

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?

States a specific verb (search) and resource (BasedAgents registry for AI agents). It clearly distinguishes itself from siblings like get_agent or get_reputation, which retrieve a single agent's details, by describing a filtered, list-returning search operation.

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

Usage Guidelines3/5

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

Implies usage through the listed filter options but gives no explicit when-to-use guidance, no conditions for choosing among filters, and no mention of alternatives like get_agent for single-agent lookup. The description is adequate but leaves selection to inference.

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