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Viral Agent

Search AI agents

search_agents
Read-only

Find AI agents and agent tools by name or by the problem they solve, for example "answer customer emails" or "turn videos into clips".

Input Schema

NameRequiredDescriptionDefault
limitNo
queryYesName or plain-language description of the job

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 and openWorldHint=false, so the safety profile is covered. The description usefully clarifies that matching is semantic as well as lexical ("by the problem they solve"), but says nothing about result ordering, whether results are capped, or what a result contains.

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?

A single front-loaded sentence with the capability stated first and concrete examples appended. No filler, and the examples earn their place by demonstrating the query style.

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 read-only search tool with no output schema, the description is adequate on intent but thin on return behavior: it never says what comes back (agent names, IDs, descriptions) or that an ID from here feeds into get_agent. The unmentioned limit parameter also leaves the result-set size unexplained.

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 coverage is only 50%: query is documented, limit is not described at all beyond min/max bounds. The description partly compensates by giving example queries ("answer customer emails", "turn videos into clips"), which teaches the expected phrasing, but it never mentions the limit parameter or a sensible default value for it.

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?

States a clear verb ("Find") plus the resource ("AI agents and agent tools") and the two matching modes (name or problem solved). The contrast with get_agent/get_rising/get_trending is implicitly clear from "search," but the description never names those siblings or says how results differ from a direct get.

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?

Usage is implied by the examples: use this when you know the job to be done but not the agent. There is no explicit "when not to use" or routing guidance such as "use get_agent when you already have an ID," which is the natural alternative among the siblings.

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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