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turnnoblindeye

Wellness Project MCP

delete_meal

DestructiveIdempotent

Permanently remove a logged meal by ID or date and food name. Linked hydration entries are deleted automatically, and ambiguous matches delete nothing to avoid mistakes.

Instructions

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.

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. Dates show when Glama detected each change.

  1. First observedv1.2.1

TDQS

A5/5.0
Behavior5/5

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

Despite strong annotations (destructiveHint=true, readOnlyHint=false), the description adds important behavioral detail: irreversibility, cascade deletion of linked hydration events, and the exact error behavior when a match is not exactly one meal. It also clarifies that nothing is deleted on ambiguity, which is critical safety 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.

Conciseness5/5

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

The description is longer than average, but every sentence earns its place. It is front-loaded with purpose, then organized into clearly capped sections (FIND THE MEAL, HYDRATION) with no filler or repetition.

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, irreversible operation, the description covers all critical aspects: how to identify the exact meal, what happens on ambiguity, retry guidance, and cascade effects. An output schema exists, so return-value documentation is not the description's responsibility. 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?

Schema coverage is 100%, but the description adds substantial selection logic: id is an alternative to date+name, name is a case-insensitive substring used only for disambiguation, and date defaults to today. This gives the agent the decision rules needed to choose the right parameter combination, going well beyond the schema descriptions.

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 a specific verb and resource: 'Permanently delete a meal entry.' It also states the exact triggering condition ('when the user explicitly asks to remove or delete a logged meal'), which clearly distinguishes it from related meal tools like update_meal and log_meal.

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 explicit when-to-use guidance, including the user-intent trigger. It also provides a detailed decision procedure for locating the meal (id vs. date+name, name only when multiple meals exist) and an explicit exclusion: do not issue a separate hydration delete. This fully routes the agent away from incorrect usage.

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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