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delete_meal

DestructiveIdempotent

Permanently delete a meal entry. Use when the user explicitly asks to remove or delete a logged meal.

FIND THE MEAL: pass id if already known. Otherwise pass date (YYYY-MM-DD, defaults to today) and, only if more than one meal was logged that day, name (a substring of the food description, case-insensitive) to narrow it down. This action is irreversible — a match that isn't exactly one meal returns an error explaining why, with nothing deleted; retry with id or a narrower name, never guess.

HYDRATION: any assistant hydration events linked to this meal are deleted by the database in the same food-row delete. Do not issue a separate hydration delete.

CAFFEINE: caffeine sidecars linked to this meal are deleted by the database in the same food-row delete. Do not call a separate caffeine delete tool.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNoMeal ID, if already known. Alternative to date + name — see FIND THE MEAL above.
dateNoDate the meal was logged. Format: YYYY-MM-DD. Used with name to find the meal when id is omitted; defaults to today if id and date are both omitted.
nameNoSubstring of the food description (case-insensitive) to disambiguate multiple meals on the same date. Only used when id is omitted.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYesHuman-readable result text returned by the tool.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changed
    • addedInput schema / properties / date
      Added value: +{
      +  "description": "Date the meal was logged. Format: YYYY-MM-DD. Used with name to find the meal when id is omitted; defaults to today if id and date are both omitted.",
      +  "type": "string"
      +}
    • changedInput schema / properties / id / description
      Previous value: -"Meal ID from list_meals. Required — do not proceed without it."New value: +"Meal ID, if already known. Alternative to date + name — see FIND THE MEAL above."
    • addedInput schema / properties / name
      Added value: +{
      +  "description": "Substring of the food description (case-insensitive) to disambiguate multiple meals on the same date. Only used when id is omitted.",
      +  "type": "string"
      +}
    • removedInput schema / required
      Removed value: -[
      -  "id"
      -]
  2. First observed

TDQS

A5/5.0
Behavior5/5

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

The annotations already flag the operation as destructive, but the description adds meaningful behavioral detail: the action is irreversible, ambiguous matches return an error with nothing deleted, retries should use id or a narrower name, and linked hydration/caffeine events are removed automatically. This goes well beyond the annotation metadata and directly shapes safe invocation.

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 longer than average, but every section earns its place. The intent is front-loaded in the first sentence, and the FIND THE MEAL / HYDRATION / CAFFEINE sections are clearly labeled and logically separated, making the content easy for an agent to parse and apply.

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?

For a destructive, ambiguity-prone delete operation, this description covers the entire invocation context: how to identify the target, what happens on failure, retry guidance, and automatic cascade behavior for linked records. An output schema exists to cover return values, so nothing essential is missing.

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?

Although the schema already has a strong 100% coverage with per-parameter descriptions, the tool description enriches those semantics with the decision tree: id takes priority, date defaults to today, and name is only a disambiguator used when multiple meals were logged that day. It even warns that an ambiguous match will error and the agent should never guess, which is genuinely useful parameter-level guidance.

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 opens with 'Permanently delete a meal entry,' naming the exact verb and resource. It also states the precise user-intent trigger ('when the user explicitly asks to remove or delete a logged meal'), which clearly differentiates it from update_meal and the other meal-related tools.

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

Usage Guidelines5/5

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

The description gives an explicit when-to-use condition and then expands into a structured disambiguation protocol: use id if known, otherwise date, and add name only when multiple meals exist on that date. It also provides strong exclusions, telling the agent not to issue separate hydration or caffeine delete calls because the database handles those cascades.

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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