ForkMate

delete_meal

DestructiveIdempotent

Delete a food from the user's diary — remove one food from an entry (by item_index), or the whole entry (omit item_index). Identify the entry by its id and local_date (both from get_day). This is a TRUE removal: the data is gone, with NO server-side tombstone and no undo. Deleting the last food in an entry removes the entry. Safe to retry — deleting something already gone is a no-op success. SAFETY: all calorie and macro values here — including carbohydrates — are ESTIMATES (from USDA / Open Food Facts or the user's own entry), approximate and not lab-measured or per-batch. They are for general nutrition tracking ONLY. Do NOT use them for insulin dosing, carb-counting for a bolus, blood-glucose prediction, or any other medical decision, and do NOT compute a dose or glucose estimate from them. For anything medical, direct the user to the product's own label and their care team.

Input Schema

TableJSON Schema

Name	Required	Description
`id`	Yes	The entry id to delete from (from get_day).
`item_index`	No	Which food to remove (0-based). Omit to delete the whole entry.
`local_date`	Yes	YYYY-MM-DD diary date of the entry (from get_day).

TDQS

A4.6/5.0

Behavior5/5

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

The description significantly exceeds annotations by disclosing permanent removal (no tombstone, no undo), the behavior when deleting the last food, and idempotency as a no-op on already-deleted entries. The medical safety warning adds important cautionary context beyond the structured 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?

The core operational description is concise and scannable, but the medical safety warning is quite lengthy. However, the warning is critical for a food-related tool and directly supports user safety, so it earns its place despite the length.

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?

The description covers edge cases (last food removal, retry as no-op), explains where to obtain the required identifiers (get_day), and includes the medical disclaimer. For a destructive tool with no output schema, it fully sets expectations for behavior and consequences.

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% with helpful parameter descriptions, but the description adds operational meaning: item_index omission deletes the whole entry, and both id and local_date come from get_day. This connects the parameters to their real-world usage beyond the schema.

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 clearly states the tool's function: 'Delete a food from the user's diary' with precise details about deleting a single food by item_index or the whole entry. This distinguishes it from siblings 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 Guidelines4/5

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

It explains how to identify the target entry using id and local_date from get_day, and when to omit item_index to delete the whole entry. It does not explicitly name alternative tools, but the diary vs. pantry context and sibling names provide implicit guidance.

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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TDQS

A4.5/5.0

Disambiguation5/5

Each tool targets a distinct resource and action: pantry vs diary vs food search vs preferences vs diagnostics. Even similar tools like get_day/get_range are clearly differentiated by scope, and search_foods/lookup_barcode are distinguished by input type (text vs barcode).

Naming Consistency5/5

All tools follow a consistent verb_noun pattern with lowercase snake_case (add_pantry_item, get_day, log_meal, search_foods). The only exception is whoami, which is a standard diagnostic convention and does not disrupt the overall consistency.

Tool Count5/5

With 12 tools, the server is well-scoped for its food-tracking domain. Each tool covers a necessary function (pantry CRUD, diary CRUD, food search, preferences, diagnostics) without redundancy or bloat.

Completeness5/5

The tool set provides full lifecycle coverage for the core domain: pantry items can be added, read, and removed (upsert covers update); diary entries can be created, read (single/day/range), updated, and deleted; food lookup includes text search and barcode; and preferences are accessible. No obvious gaps hinder agent workflows.

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