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Digital Gemology: gemstone and diamond cut library

Cut Performance Index scores

get_cut_scores
Read-onlyIdempotent

Scores from the Digital Gemology Cut Performance Index for every cut we sell: overall, brilliance, fire, scintillation, tilt, symmetry, spread, shape-norm and leakage, ray traced separately in diamond, moissanite, cubic zirconia, ruby, sapphire, emerald and amethyst, with each cut's place in its material. Filter by cut, category or material; with no filter, every row. Figures are unrounded. Never compare or rank scores across materials. Ruby and sapphire share one refractive index, so the same figures. Cuts not yet scored come with the reason.

Input Schema

NameRequiredDescriptionDefault
cutNoThe cut's slug or name, for example 'oval' or 'DG-M5'.
categoryNobrilliants, jewelry, historic, house or platonic.
materialNoOne stone (diamond, moissanite, cubic-zirconia, ruby, sapphire, emerald or amethyst); leave it out for all seven.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • changedInput schema / properties / material / description
      Previous value: -"diamond or moissanite; leave it out for both."New value: +"One stone (diamond, moissanite, cubic-zirconia, ruby, sapphire, emerald or amethyst); leave it out for all seven."
    • changedInput schema / properties / material / enum
      Previous value: -[
      -  "diamond",
      -  "moissanite"
      -]New value: +[
      +  "diamond",
      +  "moissanite",
      +  "cubic-zirconia",
      +  "ruby",
      +  "sapphire",
      +  "emerald",
      +  "amethyst"
      +]
  2. First observed

TDQS

A4.2/5.0
Behavior5/5

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

Annotations already establish read-only, idempotent, closed-world behavior, and the description adds substantive domain constraints beyond them: the cross-material comparison ban, the ruby/sapphire shared refractive index caveat, unrounded figures, and the fact that unscored cuts return a reason. This is exactly the extra context an agent needs to interpret results correctly.

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 metric list is front-loaded and every clause carries information, including the caveats. The second half runs long in a single breath, but no sentence is filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, so the description takes on the burden of describing the return payload, and it does so thoroughly (metric names, per-material ray tracing, ranking placement, unrounded values, missing-score reasons). Nothing essential for correct invocation or interpretation is missing.

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% and enums are fully documented for category and material, so the schema carries the load. The description adds only the global default ('with no filter, every row'), which the schema already states for material; baseline 3 is appropriate.

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?

Names a specific resource (Digital Gemology Cut Performance Index scores) and enumerates exactly what is returned: overall, brilliance, fire, scintillation, tilt, symmetry, spread, shape-norm, leakage, ray traced per material. An agent can distinguish this from get_cut or search_cuts without opening any schema.

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?

States filtering behavior ('Filter by cut, category or material; with no filter, every row') and a hard usage rule ('Never compare or rank scores across materials'), but gives no guidance on when to choose this over siblings such as best_cuts_for_gemstone, cut_in_gemstone or search_cuts. Tool selection is left to inference.

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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