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pharmacogenomics

Reports PharmCAT star-allele diplotypes and phenotypes per gene from raw DNA, noting coverage and provisional reference assumptions, to help answer medication and drug-metabolism questions.

Instructions

PharmCAT star-allele diplotypes and phenotypes per gene, with coverage. Provisional: untyped positions are assumed reference. Call when the user asks about medications or drug metabolism.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "pharmacogenomics"
  }
}

Input Schema

NameRequiredDescriptionDefault
report_dirNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.5.1

TDQS

A3.7/5.0
Behavior4/5

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

With no annotations present, the description carries the burden and does flag an important caveat: results are provisional because untyped positions are assumed reference. That is genuinely valuable context an agent would otherwise not have. It stops short of describing authentication, performance, or exact return structure, so it is not a full 5.

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?

Two compact sentences that front-load the resource description before the usage cue. Slightly awkward line wrapping and a bare 'Provisional:' fragment, but no wasted clauses.

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?

For an unannotated tool with no output schema, the description covers purpose, output content, and a key caveat reasonably well. It is incomplete on the one input parameter and on what 'coverage' means in practice, which leaves an agent to discover the calling convention by trial.

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?

The single parameter, report_dir, has 0% schema description coverage and is never mentioned in the description. An agent cannot tell from either source what the directory should contain or whether it is required. With only one optional parameter the damage is limited, but the gap is real.

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?

States a specific resource (PharmCAT star-allele diplotypes and phenotypes per gene, with coverage), which tells an agent exactly what data comes back. This is clearly distinct from siblings like lookup, analyze, clinvar_findings, and summary.

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?

Gives one concrete trigger condition ('when the user asks about medications or drug metabolism'), which is useful. However, it offers no exclusions or comparison to alternatives, so an agent must infer on its own whether this or a sibling such as lookup or analyze is the right call.

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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