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alexa_add_list_item

Add an item to an Alexa shopping or to-do list. Requires user confirmation before proceeding, returning a preview token when needed.

Instructions

Add an item to an Alexa shopping or to-do list. Asks the user to confirm first: a confirmation prompt where the client supports one; otherwise the first call returns a preview and a confirmToken, and only a repeat call with that token proceeds (see MCP_CONFIRM_MODE).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemYesThe item text, e.g. "oat milk".
listYesWhich list: "shopping", "todo", a list name, or a list id from alexa_list_lists.
confirmTokenNoONLY for the two-step confirmation fallback (a client without MCP elicitation). The confirmToken from this same tool's phase-1 "confirmation-required" response, passed back ONLY after the user has seen that preview and explicitly approved it in chat — never on the first call, never invented, never reused. Call again with the same arguments. Ignored when the client supports elicitation.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.3

TDQS

A4.1/5.0
Behavior4/5

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

Goes well beyond the annotations by disclosing the confirmation protocol, the phase-1 "confirmation-required" preview, the confirmToken contract, and the two-mode fallback behavior. It leans on an unexpanded external reference ("see MCP_CONFIRM_MODE") and says nothing about failure/error behavior, which keeps it below a 5.

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?

Two efficiently written sentences, front-loaded with the primary action before the confirmation detail. The dangling reference "(see MCP_CONFIRM_MODE)" adds a minor bit of unsupported pointer text.

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 mutation tool with no output schema, the description covers the critical conditional behavior (elicitation vs. two-step token flow) an agent needs to call it correctly. Return/preview contents and error handling are not described, leaving a small gap.

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 description coverage is 100%, so all three parameters (item, list, confirmToken) are fully documented in the schema itself. The description adds no syntax, format, or meaning beyond what the schema already provides, so the baseline 3 is appropriate.

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 ("Add") plus resource ("an item to an Alexa shopping or to-do list"). Easily distinguished from siblings like alexa_get_list_items, alexa_update_list_item, and alexa_remove_list_item, and the list scope is explicit.

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?

Explains the invocation context clearly: a confirmation prompt is attempted where supported, otherwise a two-step preview/confirmToken flow is required. It does not explicitly name alternatives or state when-not to use it, but the workflow guidance for this mutation tool is clear and actionable.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.