Vitalli

joiva_add_pantry_item

Add something the user put away at home. Nutrient values are not accepted here: Joiva resolves them from its own reference sources and refines them in the background. The record is as precise as its identity: name, brand, barcode. Nutrients written into note are not evaluated. A printed nutrition table counts as evidence only when photographed in the Joiva app (Vorrat → Einkauf fotografieren), not as typed numbers. Quantity may be grams, millilitres or pieces; unitWeightG is the known weight per piece, not an estimate.

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": {
      "label": "<label>",
      "quantity": "<quantity>",
      "unit": "<unit>"
    },
    "name": "joiva_add_pantry_item"
  }
}

Input Schema

Name	Required	Description
`note`	No
`unit`	Yes
`brand`	No	Manufacturer/brand, if known
`label`	Yes	Product name, e.g. 'Hackfleisch gemischt'
`staple`	No	Staple (Grundvorrat: salt, oil, spices): always considered available, carries no meaningful quantity, is never deducted and never goes on the shopping list.
`barcode`	No	EAN/UPC. Links to the product catalogue
`location`	No
`quantity`	Yes
`bestBefore`	No	YYYY-MM-DD
`unitWeightG`	No	Grams per piece/ml, when actually known

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 27, 2026

TDQS

A3.7/5.0

Behavior4/5

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

Annotations only declare the basic safety profile (non-readonly, non-destructive, non-idempotent). The description adds substantial behavioral context: Joiva resolves nutrients from its own sources and refines them in the background, note-stored nutrients are ignored, and nutrition tables only count when photographed in-app. This is useful context beyond the annotations.

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?

Front-loaded with the core action, then supporting rules. Mostly every sentence earns its place, though the photo-evidence sentence is somewhat verbose and could be tightened.

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

Completeness3/5

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

A 10-parameter mutation tool with no output schema deserves more: the description doesn't address duplicate/idempotency behavior (idempotentHint=false), what happens to location, staple, or bestBefore beyond what's in schema, or the return shape. Coverage is decent but leaves notable gaps.

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 60% schema coverage, the description meaningfully reinforces several parameters: quantity may be g/ml/piece, unitWeightG is a known per-piece weight (not an estimate), brand/barcode define record precision, and note is not evaluated. This adds real meaning over the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: 'Add something the user put away at home,' i.e. a pantry item. It is distinguishable from siblings like joiva_update_pantry_item or joiva_add_shopping_item, though it never names those alternatives explicitly.

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?

Constraints on what NOT to pass (nutrients, note nutrient text, typed nutrition tables) imply the tool's proper use, but there is no explicit routing to alternatives such as joiva_add_shopping_item or guidance on when to add vs. update an existing item.

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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