cronometer-mcp

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add_repeat_item

Set up recurring food entries that automatically log on selected days. Choose a food, quantity, and days of week to keep your nutrition diary consistent without manual re-entry.

Instructions

Add a recurring food entry that auto-logs on selected days.

Quantity is in default servings for the food (e.g., for coffee where the default serving is 1 cup, quantity=12 means 12 cups).

Use search_foods to find food_id and food_source_id.

Args: food_id: Numeric food ID from search_foods results. food_source_id: Food source ID from search_foods results. quantity: Number of default servings. food_name: Display name for the food. diary_group: Diary group name (case-insensitive) or 0-based index. Names are user-configured — call list_diary_groups to see this account's groups. Defaults to a time-of-day choice among enabled groups if omitted. days_of_week: Comma-separated day numbers (0=Sun, 1=Mon, ..., 6=Sat), or "all" for every day (default), or "weekdays", or "weekends".

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "food_id": "<food_id>",
      "food_source_id": "<food_source_id>",
      "quantity": "<quantity>",
      "food_name": "<food_name>"
    },
    "name": "add_repeat_item"
  }
}

Input Schema

Name	Required	Default
`food_id`	Yes
`quantity`	Yes
`food_name`	Yes
`diary_group`	No
`days_of_week`	No	all
`food_source_id`	Yes

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed3 schema fields changedv2.2.0Aug 24, 2026
- addedInput schema / properties / diary_group / anyOf
```
Added value: +[
+  {
+    "type": "string"
+  },
+  {
+    "type": "integer"
+  },
+  {
+    "type": "null"
+  }
+]
```
- changedInput schema / properties / diary_group / default
```
Previous value: -"Breakfast"New value: +null
```
- removedInput schema / properties / diary_group / type
```
Removed value: -"string"
```
First observedv2.0.3Mar 21, 2026

TDQS

A4.6/5.0

Behavior4/5

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

With no annotations, the description carries the transparency burden and does it well: it explains auto-logging on selected days, quantity units via the coffee example, diary_group case-insensitivity/indexing/default behavior, and days_of_week formats/defaults. It does not discuss what happens on repeated calls or the success/response shape, but the presence of an output schema mitigates the return-value gap.

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-organized: a one-sentence purpose, a crucial unit-of-measure note with a concrete example, then a clean parameter block. Every sentence adds either behavioral context or parameter guidance, with no filler or redundancy beyond the repetitive but still useful quantity note.

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?

Given six parameters, zero schema descriptions, and no annotations, this description is remarkably complete. It covers the full parameter set, expected lookup workflow, defaults, and edge-case values. The presence of an output schema means return values do not need to be described.

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?

Schema description coverage is 0%, and the description fully compensates by explaining all six parameters: food_id and food_source_id provenance, quantity meaning, food_name purpose, diary_group semantics including default, and days_of_week allowed formats including 'all', 'weekdays', and 'weekends'.

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 states a specific action and resource: 'Add a recurring food entry that auto-logs on selected days.' This differentiates it from sibling add_food_entry (one-off) and delete_repeat_item, even without naming them.

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?

It gives clear preparation guidance: 'Use search_foods to find food_id and food_source_id' and points to list_diary_groups for diary_group names. It does not explicitly say when-not-to-use this tool versus add_food_entry or delete_repeat_item, but the recurring-entry context makes the intended use reasonably clear.

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