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Search the AnswerPool catalog

answerpool_search_catalog
Read-only

FIND THE RIGHT DATA PRODUCT. Search 130+ computed products across SEC filings and fundamentals, federal regulation, procurement and grants, NIH, clinical trials, FDA recalls and adverse events, US macro indicators, weather and severe-weather alerts, known-exploited software vulnerabilities, research topics, and cross-domain entity resolution. Returns matching product ids with price, inputs and a free sample_url showing a real answer from that product; pass a product id to answerpool_get. Free.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryNo
free_onlyNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and destructiveHint, so safety is covered. The description adds that it returns product ids with price, inputs, and a sample_url, and explicitly notes it is 'Free'. This gives the agent useful behavioral context beyond the annotations.

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?

The description is front-loaded with an imperative 'FIND THE RIGHT DATA PRODUCT' and lists domains compactly. It is somewhat dense but each sentence serves a purpose—scope, output, and routing. No redundant filler.

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?

With an output schema present, return values are covered elsewhere. However, the description does not explain the input parameters (query, limit, free_only) which are undocumented in the schema. For a search tool, an agent needs to know how to construct a query. The description gives domain hints but no parameter semantics, leaving an incomplete picture.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must explain parameters. It only vaguely touches on 'free' in the last sentence, which loosely relates to free_only, but does not explain limit, query, or free_only explicitly. The agent is left to infer what query should contain or what limit controls.

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 verb 'Search' and the resource 'catalog', enumerates the domains covered, and explicitly differentiates from the sibling tool answerpool_get by instructing to pass a product id there. This leaves no ambiguity about what the tool does.

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

Usage Guidelines4/5

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

It provides a clear workflow: search for products, then pass the product id to answerpool_get. This implies when to use this tool (discovery) versus get (retrieval), though it does not explicitly mention when to prefer list_products over search. The guidance is sufficient for most use cases.

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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