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mhyounis19

cronometer-api-mcp

by mhyounis19

add_custom_food

Create a custom food in Cronometer with specified nutrients, returning a food ID for logging.

Instructions

Create a custom food in Cronometer with specified nutrition.

Nutrient amounts should be for the full serving size specified. After creation, use the returned food_id with add_food_entry to log it.

Args: name: Food name. calories: Calories per serving (kcal). protein_g: Protein per serving (g). fat_g: Fat per serving (g). carbs_g: Carbs per serving (g). fiber_g: Fiber per serving (g, default 0). sugar_g: Sugar per serving (g, default 0). sodium_mg: Sodium per serving (mg, default 0). saturated_fat_g: Saturated fat per serving (g, default 0). serving_name: Name for the serving size (default "1 serving"). serving_grams: Weight of one serving in grams (default 100).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
caloriesYes
protein_gYes
fat_gYes
carbs_gYes
fiber_gNo
sugar_gNo
sodium_mgNo
saturated_fat_gNo
serving_nameNo1 serving
serving_gramsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

Annotations already provide readOnlyHint=false, destructiveHint=false, idempotentHint=false, openWorldHint=true. The description adds context about nutrient amounts per serving and the return value usage, but does not disclose potential side effects (e.g., duplicate name handling) or error conditions.

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 concise, front-loaded with the purpose, and organized into a brief paragraph followed by a clear 'Args:' list. Every sentence adds value with no unnecessary text.

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 complexity (11 parameters, output schema exists), the description covers the main workflow, parameter details, and return value usage. Omits error handling or validation details, but is adequate for the tool's straightforward purpose.

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

Parameters4/5

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

With 0% schema description coverage, the description fully compensates by listing each parameter with a clear explanation, including units (g, mg, kcal) and defaults for optional ones. Adds contextual hint that amounts are for the full serving size.

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 action ('Create a custom food') and the resource ('in Cronometer with specified nutrition'). It distinguishes from sibling tools like add_food_entry (logging) and search_foods (searching).

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?

Explicitly instructs to use the returned food_id with add_food_entry, providing a clear workflow. Implicitly differentiates from alternatives, but does not explicitly state when not to use this tool.

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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