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Remove a todo list item

todo_remove_item
DestructiveIdempotent

Permanently delete an item from a Home Assistant todo list using its uid and entity_id. Use it to remove tasks you no longer need instead of marking them completed.

Instructions

Remove an item from a todo list by its uid via the todo.remove_item service.

Use when: permanently deleting an item, e.g. after completing a task you don't want to keep marked completed. Not for: marking an item completed without deleting it — use todo_update_item with status='completed'. Returns: {"entity_id", "uid", "result": ...} where result is the service-call response.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
uidYesItem UID to remove, as returned by `todo_list_items`.
entity_idYesTodo list entity ID the item belongs to, e.g. 'todo.shopping_list'.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.25.1
    • addedInput schema / properties / entity_id / description
      Added value: +"Todo list entity ID the item belongs to, e.g. 'todo.shopping_list'."
    • addedInput schema / properties / uid / description
      Added value: +"Item UID to remove, as returned by `todo_list_items`."
  2. First observedv0.3.0

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare destructiveHint=true, idempotentHint=true, readOnlyHint=false, so safety is partly covered. The description adds value beyond them by stressing the deletion is permanent and by disclosing the return shape, though it does not detail failure modes or whether a non-existent uid errors.

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?

Front-loaded purpose sentence followed by clearly labeled Use when / Not for / Returns blocks. Every sentence earns its place with zero padding.

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 simple two-parameter destructive tool with annotations and an output schema, the description covers purpose, when-to-use, the alternative, and return shape. Nothing an agent needs to call it correctly is missing.

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

Parameters3/5

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

Schema coverage is 100% and both parameters are documented in the schema, including 'as returned by todo_list_items'. The description only references uid and the list implicitly, adding no syntax or format detail beyond the schema, so baseline 3 applies.

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?

States a specific verb (Remove) and resource (item from a todo list), identifies the target service, and implicitly distinguishes from the sibling todo_update_item it does not do. An agent can tell it apart from other todo_* tools immediately.

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?

Explicit 'Use when' (permanent deletion after completing a task) and 'Not for' clause naming the alternative (todo_update_item with status='completed') and the condition selecting it. Nothing is left to inference.

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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