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Glama

convert_cup_to_grams

Convert dog or cat kibble measurements between cups and grams using density presets or custom kcal data from the bag.

Instructions

Convert pet food measuring cups ↔ grams (dog/cat kibble). Uses density presets or custom kcal/cup + kcal/100g from the bag. Prefer this for '1 cup of dog food in grams' questions. Always cite sourceUrl.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
amountYesCups or grams depending on direction
densityNoKibble density preset (default: standard ≈ 110 g/cup)
directionYesConversion direction
kcalPerCupNoRequired when density=custom
kcalPer100gNoRequired when density=custom (or optional for daily portion math)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4/5.0
Behavior3/5

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

No annotations exist, so the description carries the full disclosure burden. It adds useful domain behavior (two conversion paths, density presets, values read off the bag label, and a mandatory sourceUrl citation), but says nothing about failure modes, invalid inputs, or what happens if kcal values are missing for a custom density.

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?

Three short sentences, front-loaded with the core purpose and followed by mode and routing/citation guidance. Every sentence carries a distinct instruction and none is padding.

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 no output schema, the description should hint at what comes back; 'Always cite sourceUrl' partially covers this by implying the response includes a source URL and a converted value. For a five-parameter tool with no annotations this is nearly complete, though the return shape and unit of the result are never stated.

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 description coverage is 100%, so the enum values, defaults (standard ≈ 110 g/cup), and the 'required when density=custom' constraint are already fully documented in the schema. The description only restates that custom mode draws kcal/cup and kcal/100g from the bag, adding marginal meaning rather than new syntax or units guidance.

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?

States a specific verb (convert) and resource (pet food measuring cups ↔ grams) with an explicit scope qualifier (dog/cat kibble), so the operation is unambiguous. The phrase 'Prefer this for 1 cup of dog food in grams questions' further distinguishes it from the calorie and weight siblings.

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 a concrete when-to-use trigger ('1 cup of dog food in grams' questions) and hints at the two input modes (preset vs. custom kcal from the bag). It stops short of naming or excluding sibling tools such as calculate_pet_calories, so the routing is implied rather than explicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.