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Cultivar detail (with live availability if sold)

get_strain
Read-onlyIdempotent

Full encyclopedia record for one cultivar: lineage and parents, breeder(s), terpenes, aroma/flavor/effects, growing notes, history, awards, crosses bred from it, sources. Accepts an encyclopedia slug ('wedding-cake') or a menu slug ('wedding-cake-cannabis-clones'). If Prime Cuts sells it, 'menu.availability' is live (InStock / PreOrder / OutOfStock, units ready now, next batch date).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesEncyclopedia slug, menu slug, or the cultivar's name/alias (e.g. 'wedding-cake', 'wedding-cake-cannabis-clones', 'Wedding Cake', 'GMO')

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and idempotentHint, and the description adds that live availability is fetched if sold, which is a useful behavioral detail. No contradictions with annotations.

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 relatively compact but packs in many details. It is structured with a clear list of returned fields and separate sentences for slug types and availability, making it easy to scan without being bloated.

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?

Without an output schema, the description enumerates the expected fields (lineage, terpenes, awards, etc.) and explains the availability sub-object. This gives an agent enough context to anticipate the response, though the exact structure is not specified.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The parameter slug is fully explained with two accepted formats and concrete examples ('wedding-cake' and 'wedding-cake-cannabis-clones'), going beyond the schema description to clarify usage.

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 clearly states the tool's purpose: returning a full encyclopedia record for a cultivar, including detailed fields like lineage, breeder, terpenes, and effects. It also specifies that live availability is included if the item is sold, leaving no ambiguity.

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 description provides concrete input guidance (slug types with examples) and explains when live availability appears, but it does not explicitly compare to sibling tools like search or list_strains. Still, the use case is clear from context.

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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