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search_listings

Search for agentic AI tools by keyword query with optional filters. Use this for keyword-based search. For natural language queries like 'something that automates email', use semantic_search instead. For browsing all tools in a category, use get_category instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax results to return
queryYesSearch query (e.g. 'code review', 'open source coding agent')
cohortNoFilter by cohort: PEOPLE (individual tools) or TEAMS (team/enterprise tools)
categoryNoFilter by category slug (e.g. 'coding-agents', 'general-purpose-agents')
minScoreNoMinimum agenticness score (default 1 to exclude unscored/junk entries, set to 0 to include all)
mcpSupportNoFilter to tools with MCP (Model Context Protocol) support
openSourceNoFilter to open-source tools only
autonomyLevelNoFilter by autonomy level
deploymentModelNoFilter by deployment model

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / query / maxLength
      Added value: +500
  2. First observed

TDQS

A4.2/5.0
Behavior3/5

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

No annotations are provided, so the description carries the behavioral burden. It implies a safe read operation but does not disclose return format, pagination behavior, result ordering, or whether there are rate limits. Useful routing context, but little operational transparency.

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 short sentences, front-loaded with the core action, and each sentence earns its place by either stating scope or routing to an alternative. 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?

For a read-only search tool with nine fully documented parameters and a required query, the description covers selection and routing adequately. The only gap is return shape and pagination, which matter less here since there is no output schema and limit/default are already in the schema.

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%, with defaults, min/max, and enums all documented in the schema. The description mentions keyword query and optional filters but adds no format, syntax, or interaction detail beyond that, so the baseline of 3 applies.

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+resource ('Search for agentic AI tools') plus the query mode and the presence of optional filters. It explicitly differentiates itself from siblings semantic_search and get_category, so an agent can pick the right tool without opening schemas.

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?

Gives explicit when-to-use guidance ('keyword-based search') and names two alternatives with the conditions that select each ('natural language queries ... use semantic_search', 'browsing all tools in a category ... use get_category'). This is textbook routing guidance.

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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