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mame0001

sakenowa-mcp

by mame0001

find_similar_sake

Discover sake with matching or contrasting flavor profiles by selecting a reference sake and a mode such as similar, drier, or richer. Only sake with flavor charts are considered.

Instructions

★ Core feature ★ Given one sake, find others by flavor-vector proximity.

`mode` steers the direction in flavor space:
  - similar       : nearest overall (a true taste-alike)
  - drier         : like this, but drier
  - sweeter       : like this, but less dry / rounder
  - lighter       : like this, but lighter & crisper
  - richer        : like this, but fuller & heavier
  - more_aromatic : like this, but more floral/fragrant
  - calmer        : like this, but quieter on the nose
  - contrast      : the opposite palate (for deliberate exploration)

Only sake that have a flavor chart can be matched.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
brand_idYes
modeNosimilar
limitNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations provided, so description carries full burden. It explains the mode behavior and prerequisite, but lacks details on failure cases, auth requirements, or response structure. The output schema exists but is not referenced.

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 well-structured with a star emphasis, clear summary, and a bullet list for mode options. Every sentence serves a purpose without fluff.

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?

Given the output schema existence and 3 simple parameters, the description covers core behavior and mode variations well. It could improve by mentioning error conditions or how the limit parameter affects results, but overall it is adequate.

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 0%, but the description adds value for the 'mode' parameter with detailed options. The 'brand_id' and 'limit' parameters receive no added explanation beyond schema titles, so coverage is incomplete.

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 finds similar sakes by flavor-vector proximity, distinguishing it from siblings like compare_sake and search_sake.

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 explains when to use (given a sake, find similar), details the mode parameter for direction, and notes a prerequisite (only sakes with a flavor chart). However, it does not explicitly list when not to use or alternatives.

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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