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Agent Tested

Search Agent Tested tools

search_tools
Read-onlyIdempotent

Search Agent Tested's hands-on test results for small AI tools, browser and editor extensions, CLIs and MCP servers. Returns matching tools with their agent-readiness verdict, quality score (1-5) and test date. Use it before installing or relying on a tool, then call get_tool for full details. Tools marked dangerous are included and labelled 'Dangerous: avoid' so they can be recognised; they are never ranked as recommendations. Untested tools have no score.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryNoWords to match against tool name, slug, summary and category. Empty or omitted lists all tools.
filtersNo
categoryNoTool kind (normalised from the dataset's free-text category).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive, so the bar is lower, yet the description adds real behavioral context: dangerous tools are included and relabelled 'Dangerous: avoid' rather than ranked, and untested tools carry no score. It stops short of describing pagination or result-ordering behavior, which would matter given the limit parameter.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Four sentences, front-loaded with the scope and return payload, with the usage/workflow guidance and edge-case notes following. Slightly dense but every sentence adds information; no filler.

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

Completeness4/5

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

With no output schema, the description usefully enumerates the return fields (agent-readiness verdict, quality score, test date) and the dangerous/untested edge cases. The main gap is pagination/limit behavior for a search tool that defaults to 10 and caps at 25.

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 50%, below the high-coverage baseline, so the description is expected to compensate. It hints at filterable dimensions by mentioning the 'agent-readiness verdict' and 'quality score (1-5)', which map to the agent_ready and min_quality filters, but says nothing about limit, the filters object structure, or category values. Partial compensation only.

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 and resource ('Search Agent Tested's hands-on test results for small AI tools, browser and editor extensions, CLIs and MCP servers') and immediately names the sibling boundary ('then call get_tool for full details'). An agent can distinguish this from get_tool and the other siblings without opening any schema.

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 says when to use it ('before installing or relying on a tool') and names the follow-up alternative ('then call get_tool for full details'), giving a clear two-step workflow. It also clarifies that dangerous tools are returned but flagged, so the agent knows not to treat them as recommendations.

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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