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TestWell Lab Tests

by com.test-well

Compare all-in prices across providers for a test

compare_prices
Read-onlyIdempotent

For one blood test, the all-in single-test price (sticker + per-order fees) at TestWell and at every tracked direct-to-consumer provider with a verified equivalent — JustLabs, Quest, Labcorp OnDemand, Ulta Lab Tests, Walk-In Lab, HealthLabs and more — each with the date it was verified, plus typical hospital self-pay and Quest Direct reference prices. States the multi-test caveat (fees are paid once per order). Source: the TestWell Blood Test Price Index (CC BY 4.0).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
testYesTest slug or name, e.g. 'tsh', 'lipid panel', 'vitamin-d'

Schema Changelog

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

  1. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Annotations already mark it read-only and non-destructive, and the description adds valuable behavioral context: it returns verified dates, includes reference prices, states the multi-test fee caveat, and cites the data source. This goes well beyond the structured 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 dense but well-organized, leading with the core purpose and then adding caveats and source attribution. The provider list is somewhat long, but it is substantive for an agent deciding whether this tool covers a given provider.

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 single-parameter read-only tool, the description fully covers what data is returned, the scope of comparison, a relevant caveat, and the data source. Nothing essential for selecting or invoking the tool is missing.

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?

The input schema already documents the single 'test' parameter with examples and 100% coverage. The description adds minimal new parameter-level meaning beyond emphasizing 'one blood test,' so the baseline 3 is appropriate.

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 names a specific verb ('compare'), a clear resource (all-in single-test prices across providers for one blood test), and enumerates exactly which providers and reference prices are included. It also distinguishes this from siblings by narrowing scope to price comparison for a single test.

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?

The opening phrase 'For one blood test' clearly signals the intended use case, and the multi-test caveat explains a key limitation. It does not explicitly name alternative sibling tools or state when not to use it, but the usage context is clear enough for an agent to select it correctly.

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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TDQS

A4.2/5.0
Disambiguation4/5

Each tool has a distinct primary purpose, but compare_prices and compare_provider have overlapping comparison themes that could lead to misselection if an agent is not careful. The descriptions provide enough context to differentiate them, but the boundary between searching for a test and getting its full detail could also cause minor confusion.

Naming Consistency5/5

All tool names follow a clear verb_noun pattern with consistent snake_case formatting (e.g., calculate_free_testosterone, compare_prices, get_test, list_panels). The naming style is uniform and predictable across the entire set.

Tool Count5/5

13 tools is a well-scoped count for a lab test service covering search, details, pricing, reference ranges, interpretation, comparisons, and educational guides. Each tool earns its place without feeling redundant or bloated.

Completeness5/5

The tool set covers the full user journey: searching and viewing tests, panels, pricing and ordering quotes, reference ranges, interpretation, unit conversion, and finding draw sites. There are no obvious dead ends or significant missing operations for the stated purpose of a consumer-facing lab test information and ordering service.

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