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rwestergren

io.github.rwestergren/cronometer-api-mcp

by rwestergren

add_custom_food

Create a custom food item in Cronometer by specifying its nutritional values, including calories, protein, fat, and carbs. The food can then be logged in your diary.

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
fat_gYes
carbs_gYes
fiber_gNo
sugar_gNo
caloriesYes
protein_gYes
sodium_mgNo
serving_nameNo1 serving
serving_gramsNo
saturated_fat_gNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Annotations already indicate a write operation (readOnlyHint=false). The description adds that it creates a persistent custom food and returns a food_id, which is useful beyond annotations. It does not detail deletion or modification implications, but overall transparent.

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 description is front-loaded with the purpose and important usage note. The parameter list is structured but somewhat lengthy. Nonetheless, every sentence adds value, particularly given the need to compensate for schema deficiencies.

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?

The description covers all 11 parameters, mentions return value usage, and provides a critical serving size caveat. With an output schema present, missing details like error handling are minor. Mostly complete for a creation tool.

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?

With 0% schema coverage, the description fully compensates by detailing each parameter, including units (kcal, g, mg) and defaults (e.g., serving_name default '1 serving'). This adds essential meaning beyond the schema's bare property names.

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 explicitly states it creates a custom food with specified nutrition, distinguishing itself from sibling tools like search_foods and add_food_entry by noting the returned food_id is used with add_food_entry. The verb 'Create' and resource 'custom food' are clear.

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 provides clear context: use this to create a custom food, and then use add_food_entry to log it. It also notes that nutrient amounts are for the full serving size. However, it does not explicitly state when not to use or list alternative methods for similar tasks.

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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