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lorkorblaq

io.github.lorkorblaq/labloop-mcp

by lorkorblaq

Get test prices by provider

labloop_get_test_providers
Read-onlyIdempotent

Retrieve test centers and prices for a given test ID, sorted cheapest first. Use an exact test ID from a prior search to compare provider costs.

Instructions

Get the test centers offering a test and their prices, cheapest first.

Returns {status, testId, testName, currency, providers: [{provider, price}]}, or {status: "invalid_test_id"} if the id is unknown.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
test_idYesThe exact 'id' value (e.g. 'tst-cbc-basic') copied from a prior labloop_find_test or labloop_list_tests result. Never a test name or abbreviation such as 'PSA'. If no id is visible in the conversation yet, call labloop_find_test first.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint, and openWorldHint. The description adds useful behavioral detail beyond those annotations: results are sorted cheapest first, and an invalid id returns '{status: "invalid_test_id"}' rather than throwing. This meaningfully informs an agent's expectations.

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?

The description is compact: one sentence states the core behavior and ordering, and a second sentence gives the exact return shape and error case. No filler or repetition exists.

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 simple read-only lookup with one parameter, an output schema, and rich annotations, the description covers everything needed: the resource, the sort order, the return structure, and the invalid-id behavior. The parameter schema also supplies the prerequisite call guidance.

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%, and the test_id parameter is already well documented with an example, a warning against using test names, and a fallback instruction to call labloop_find_test first. The main description adds no additional parameter semantics beyond what the schema provides, so the baseline of 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 uses a specific verb and resource: 'Get the test centers offering a test and their prices', and explicitly notes ordering ('cheapest first'). This clearly differentiates it from siblings like labloop_find_test and labloop_list_tests, which focus on finding/listing tests rather than providers and pricing.

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 parameter description gives clear usage context: the test_id must be the exact 'id' from a prior labloop_find_test or labloop_list_tests result, and if no id is visible, the agent should call labloop_find_test first. It does not explicitly state when to prefer this tool over quote_or_book_collection, so it stops short of a full when/when-not contrast.

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