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Halal or Not: Is this medicine halal?

halalornot_check_medicine
Read-onlyIdempotent

Halal or Not. Is this medicine halal? Reads a medicine's active and inactive ingredients from its US label (openFDA) and flags gelatine, alcohol, pig-derived enzymes and heparin. The headline and say line lead with the ruling on necessity, so nobody stops a prescribed medicine; the ingredient reading follows (ingredient_headline, verdict)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesBrand or generic name.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, openWorld, idempotent, non-destructive), so the bar is lower. The description adds real context beyond annotations: it reads from the US openFDA label, flags specific substances (gelatine, alcohol, pig-derived enzymes, heparin), and explains the output ordering (headline ruling first, ingredient reading second). That behavioral intent is genuinely useful.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The opening 'Halal or Not. Is this medicine halal?' simply restates the title before reaching substance, and the closing clause packs field-name parentheticals (ingredient_headline, verdict) somewhat densely. Purpose is front-loaded but there is redundant framing.

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?

With a read-only annotation set, one fully documented parameter, and no output schema, the description compensates by describing the return structure (headline, say line, ingredient_headline, verdict) and the data source. An agent has most of what it needs to invoke and interpret this correctly.

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 coverage is 100% for the single 'name' parameter (brand or generic name), so the schema already does the documentation. The description adds no syntax or format detail beyond what the schema states, making the baseline 3 appropriate.

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: reads a medicine's active and inactive ingredients from its US label (openFDA) and flags named substances. The medicine/US-label scope distinguishes it from generic siblings like check_ingredients, though it does not explicitly name an alternative. Clear, but no explicit sibling differentiation.

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 phrase 'so nobody stops a prescribed medicine' hints that this is meant for prescribed medication contexts, but it never states when to prefer this over ask_is_it_halal or check_ingredients. No exclusions or alternatives are given.

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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