Picardo

Search lab tests

search_lab_tests

Read-onlyIdempotent

Search Picardo’s orderable Labcorp tests by test name, six-digit Labcorp code or topic word, for example "ferritin", "vitamin D" or "thyroid". Returns each test’s code for prepare_order_link, a short description, price, preparation and the panels that already order it for everyone.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "<query>"
    },
    "name": "search_lab_tests"
  }
}

Input Schema

Name	Required	Description	Default
`limit`	No
`query`	Yes

Output Schema

Name	Required	Description	Default
`tests`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 3, 2026

TDQS

A3.8/5.0

Behavior4/5

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

Annotations already cover read-only, idempotent, non-destructive and closed-world behavior, so the description only needs to add what they can't. It does add real context: which fields are matched, and that each result carries code, description, price, preparation and ordering panels. It omits result-count behaviour and the meaning of the limit ceiling.

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?

A single sentence that front-loads the verb and resource, then packs searchable fields, examples, and return shape with zero filler. Nothing is wasted and nothing is redundant with the annotations.

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?

An output schema exists, so the return-field recap is bonus rather than obligation, and the description is already sufficient to call the tool correctly. The remaining gaps (limit semantics, behaviour on zero results) are minor for a two-parameter search.

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 0%, so the description must carry parameter meaning. It adds genuine semantics for 'query' (name, six-digit code, topic word, with examples) but says nothing about 'limit', which has a default of 5 and a maximum of 10 that an agent cannot infer.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Search ... orderable Labcorp tests') and enumerates the searchable fields (test name, six-digit Labcorp code, topic word) with concrete example queries. The distinction from get_lab_panel and list_lab_panels is only implicit through the verb 'search', not stated explicitly.

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

Usage Guidelines3/5

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

Usage is only implied: the mention that results carry the code 'for prepare_order_link' sketches a search-then-order workflow, but there is no explicit when-to-use versus get_lab_panel or list_lab_panels, and no guidance on what to do when nothing matches.

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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