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List / filter cultivars

list_strains
Read-onlyIdempotent

Meaning-aware search over the 331-cultivar encyclopedia, ranked by relevance. Free-text 'q' understands phrases like "short flowering", "high yield", "purple strains", "gas", "OG lineage", "Zkittlez terp profile", "Prime Cuts exclusives", or a breeder name; the same meanings are available as explicit filters. Every result carries 'matched_on' (the factual fields it matched) and the response carries 'interpreted' (how q was read). Nothing is inferred beyond the documented record. Each result includes a 'menu' block with a live-availability URL when Prime Cuts sells the cultivar.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoFree text: strain/alias/lineage/breeder names or descriptive phrases (aroma, colour, flowering speed, yield, exclusives)
typeNo
colorNoReported flower colour, e.g. 'purple'
limitNo
yieldNoMinimum documented yield rating
flavorNoAroma/flavour/terpene keyword with synonyms, e.g. 'gas' (fuel, diesel), 'candy', 'citrus'
offsetNo
breederNoBreeder slug from list_breeders, e.g. 'seed-junky-genetics'
lineageNoName that must appear in the lineage or ancestry, e.g. 'OG', 'Zkittlez', 'Gelato'
on_menuNotrue = only cultivars Prime Cuts sells as clones
terpeneNoDominant terpene, e.g. 'limonene'
exclusiveNotrue = only cultivars bred or pheno-hunted in-house by Prime Cuts Nursery
terp_profile_ofNoStrain name/slug: return cultivars that share its dominant terpene or descend from it
flowering_max_weeksNoDocumented flowering time at most this many weeks (e.g. 8 for fast finishers)
flowering_min_weeksNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already mark read-only/idempotent/non-destructive; description adds relevant behavior: relevance ranking, no inference beyond documented record, and inclusion of a live-availability menu block when applicable. No contradiction.

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?

The description is dense but purposeful: purpose first, then query semantics, then result behavior, with no filler or redundant restatement of the schema.

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?

Complex 15-parameter tool is handled well; description covers query semantics, output highlights (matched_on, menu, live availability), and business context (Prime Cuts). It omits a full result-field list, but that is not needed for selecting and invoking.

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?

Despite 73% schema coverage, description enriches key parameters: q accepts descriptive phrases, flavor treats synonyms (gas/fuel/diesel), yield is a minimum rating, terp_profile_of switches meaning, flowering_max is a cap, and on_menu/exclusive are defined.

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?

Description opens with 'Meaning-aware search over the 331-cultivar encyclopedia, ranked by relevance' – a specific verb and resource plus filtering/ranking distinction from siblings like get_strain/search.

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?

Gives concrete query examples and states that free-text q maps to the same meanings as explicit filters; however, it doesn't explicitly contrast when to prefer this over sibling search/get_strain, though the encyclopedia/filter framing makes it inferable.

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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