Skip to main content
Glama

AnswerPool

by io.github.blakeyounger

Get any AnswerPool product

answerpool_get
Read-only

RUN ANY of the 133 AnswerPool products by id — this plus answerpool_search_catalog is the main path, and every product is reachable this way. Find an id with answerpool_search_catalog, then pass its inputs as a JSON object, e.g. {"product_id": "weather_alerts", "params": {"area": "CA"}}. Covers SEC filings, fundamentals and insider activity, Federal Register rulemaking, federal procurement and grants, NIH, clinical trials, FDA recalls and adverse events, US macro indicators, weather and severe-weather alerts, known-exploited vulnerabilities, research-topic momentum and entity resolution. Each product's input and output schema is in the catalog entry. Free products need no key; paid ones debit a prepaid credit key and are never charged on failure.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsNo
product_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added

TDQS

A4.7/5.0
Behavior4/5

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

The annotations already declare readOnlyHint and destructiveHint, and the description adds useful behavior: paid products 'debit a prepaid credit key and are never charged on failure'. It also points to catalog entries for schemas, but says nothing about error responses or rate limits.

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 the core action and workflow. The category list and pricing sentence are useful but make it slightly longer than strictly necessary.

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

Completeness5/5

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

For a generic dispatcher of 133 products, it covers the full call path: obtaining the id, passing params, locating schemas, and handling keys. The existence of an output schema is referenced via catalog entries, so return values need not be spelled out here.

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

Parameters5/5

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

With 0% schema description coverage, the description compensates by giving a concrete example of the JSON object and explaining that each product's input/output schema lives in its catalog entry. This gives the agent enough to construct both parameters correctly.

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 opens with a specific verb and resource: 'RUN ANY of the 133 AnswerPool products by id'. It clearly positions this tool as the main execution path and distinguishes it from answerpool_search_catalog, which finds ids.

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?

It explicitly defines the workflow: 'Find an id with answerpool_search_catalog, then pass its inputs as a JSON object'. It also differentiates paid vs free products, telling the agent when a key is required.

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

All AnswerPool toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.7/5.0
Disambiguation3/5

Search, list, and get are clearly distinct, and credit_balance is unambiguous. However, answerpool_sec_company overlaps with answerpool_get since SEC company data is described as one of the many products reachable through get, which could confuse an agent about whether to use the generic get or the specialized tool.

Naming Consistency3/5

All tools share the answerpool_ prefix, but the suffix pattern is inconsistent: list_products and search_catalog follow verb_noun, get is a bare verb without an object, and credit_balance and sec_company are noun phrases. The naming is readable but not uniformly patterned.

Tool Count4/5

Five tools is a reasonable size for a data-product gateway: two discovery tools, one execution tool, an account tool, and a convenience shortcut. The count is appropriate, though sec_company is arguably redundant given answerpool_get.

Completeness4/5

The tool set covers the full user workflow: find products, list all products, execute a product, and check billing balance. Minor gaps exist, such as no way to inspect a single product's schema without listing everything and no general mechanism for product-specific convenience tools beyond sec_company, but no critical workflow is blocked.

Resources