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Remove a like or dislike

delete_food_preference
DestructiveIdempotent

Remove a recorded like or dislike, by its subject as get_household_overview shows it.

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": {
      "subject": "<subject>"
    },
    "name": "delete_food_preference"
  }
}

Input Schema

NameRequiredDescriptionDefault
subjectYesThe recorded subject, e.g. 'broccoli' or 'spicy'.
memberNameNoMember it belongs to; omit for a household-level preference.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior3/5

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

Annotations already declare destructiveHint=true, idempotentHint=true and readOnlyHint=false, so the safety profile is carried structurally. The description adds only the provenance rule for the subject string; it does not say what happens if no matching preference exists, or whether removing a preference affects existing plans and shopping data.

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?

A single front-loaded sentence with zero filler; the verb and resource come first and the provenance constraint follows. Nothing extraneous is included for a two-parameter tool.

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?

For a simple destructive mutation, the annotations carry destructiveness and idempotency, the schema fully documents both parameters, and the description supplies the prerequisite read step. The only gap is what the tool does when the named subject is not recorded, which an agent would want before calling.

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?

Schema coverage is 100%, so the baseline would be 3, but the description goes beyond the schema by specifying where to obtain the exact subject string ('as get_household_overview shows it'), which is real matching guidance not present in the property docs. The memberName parameter is left entirely to the schema, which already covers it adequately.

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?

States a specific verb and resource ('Remove a recorded like or dislike') and identifies the deleting counterpart to the sibling add_food_preference. It does not explicitly name that sibling, but the resource is distinctive enough within the toolset to be unambiguous.

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?

Adds a useful workflow pointer: the subject must match what get_household_overview shows, which tells the agent to read state before deleting. It gives no when-not guidance (e.g. use update rather than delete, or what to do if the preference is absent) and never mentions add_food_preference as the inverse operation.

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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