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elthio-mcp

by io.github.Iomed-commits
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verify_supplement_recommendation

Verify whether a supplement is safe to recommend to a user given their medications and current supplements. Runs the same interaction check as /med-check plus pathway analysis on the full stack including the new supplement. Returns safe_to_recommend, agent_summary, confidence, severity, timing_recommendation, citation, full_interactions, and pathway_analysis. Use whenever an AI agent is about to suggest a supplement and needs a go/no-go safety verdict.

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": {
      "supplement": "<supplement>"
    },
    "name": "verify_supplement_recommendation"
  }
}

Input Schema

NameRequiredDescriptionDefault
contextNoOptional — why the user wants this supplement (stored for audit only).
supplementYesSupplement the agent wants to recommend. e.g. 'Omega-3 Fish Oil 1000mg'
medicationsNoUser's prescription medications.
supplements_already_takingNoSupplements the user already takes (excluding the one being recommended).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations, the description must carry behavioral disclosure. It clearly indicates a safety verification and lists return fields such as safe_to_recommend, confidence, severity, and citation, which helps. But it does not disclose permissions, whether the operation is read-only, rate limits, or limitations of the pathway analysis.

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 purpose and is reasonably concise across three sentences. The return-field list is useful, though slightly dense, but overall it is well structured.

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?

For a tool with no output schema, the description helpfully names key return fields and the go/no-go verdict use case. Combined with complete parameter schema documentation, it is largely sufficient, though it could say more about limitations or alternatives among the safety-check siblings.

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%, so the API schema already documents all four parameters, including the audit-only context field. The description reinforces the key inputs by saying the check is based on medications and current supplements, but it adds little parameter meaning beyond the schema.

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?

The description states a specific verb and resource: verify whether a supplement is safe to recommend given medications and current supplements. It is clear about what the tool does, but it does not explicitly distinguish itself from sibling tools like check_supplement_safety or check_full_stack, so an agent may need to infer which safety-check tool is appropriate.

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?

It gives a clear usage condition: use whenever an AI agent is about to suggest a supplement and needs a go/no-go safety verdict. However, it does not name when to use alternatives such as check_supplement_safety, check_full_stack, or get_supplement_timing, so selection guidance is incomplete.

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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