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parse_ingredients

Parse raw ingredient text into structured Mealie ingredients and create records through the API using nlp, brute, or openai parsers.

Instructions

Parse Ingredients — Recipe: Ingredient Parser. Create ingredient. [POST /api/parser/ingredients] Keywords: parse_ingredients, parse ingredients, create ingredient, add ingredient, new ingredient, make ingredient, write ingredient, ingredient, ingredients, recipe ingredient parser, parser, create, add, new, make, write, post, mealie.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.11

TDQS

C2.1/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. It states the HTTP endpoint but does not explain authentication needs, whether it persists data, what the parser modes do, or what is returned.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The core phrase is front-loaded, but the definition is heavily diluted by a long keyword list of near-synonyms. This keyword stuffing adds no actionable meaning and makes the description unnecessarily noisy.

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

Completeness2/5

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

With no output schema, no annotations, and 0% schema description coverage, the description should explain more about inputs, parser behavior, and return values. It gives only the endpoint and a muddled 'Create ingredient' label, leaving a caller under-informed for a parser tool with three modes.

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

Parameters1/5

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

Schema description coverage is 0%, and the description adds no parameter meaning. It does not mention the required ingredients array, the parser field, or the nlp/brute/openai enum values, leaving all parameter semantics to an undocumented schema.

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

Purpose3/5

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

The description states a specific verb and resource: 'Parse Ingredients' and '[POST /api/parser/ingredients]'. However, it also says 'Create ingredient,' which muddles whether this parses existing ingredient text or creates a stored ingredient. It does not explicitly distinguish itself from the sibling parse_ingredient.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance on when to use this tool versus parse_ingredient or other recipe/ingredient tools. The keyword list implies broad synonym coverage but provides no conditions, prerequisites, or exclusions.

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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