human_input

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Ask the user to select several options

ask_multi_select

Read-only

Ask the user to choose one or more options from a list and wait for the answer. Returns the selected labels for use in your workflow.

Instructions

Ask the user to select one or more options from a list and wait for the answer. Use this when the user should pick a subset — which platforms to target, which checks to enable, which modules to include. Set min/max when the count genuinely matters; leave them out otherwise. Returns the selected labels in selected and comma-joined in answer.

Input Schema

TableJSON Schema

Name	Required	Description
`max`	No	Maximum number of selections allowed. Defaults to the number of options.
`min`	No	Minimum number of selections required. Defaults to 1.
`options`	Yes	The candidate items. The user may select more than one.
`question`	Yes	The question whose answer is a subset of the listed options. Say explicitly whether the choices are independent.
`timeout_ms`	No	Optional override, in milliseconds, for how long to wait for the user. Defaults to the server setting (HIM_TIMEOUT_MS, 300000).

Output Schema

TableJSON Schema

Name	Required	Description
`via`	Yes	Channel that produced the outcome.
`tool`	Yes	Name of the tool that produced this result.
`answer`	Yes	The answer as a string: chosen label, "yes"/"no", or the typed text.
`status`	Yes	Outcome. Only `answered` carries a usable answer. `needs_user_input` means you must ask the user yourself, in chat, using the question and options in `message`.
`message`	Yes	Human-readable summary, including options when the question is still unanswered.
`fallback`	Yes	Configured fallback mode (HIM_FALLBACK).
`form_url`	Yes	Loopback form URL, when the http fallback served this question.
`question`	Yes	The question as it was asked.
`selected`	Yes	Selected labels; exactly one for ask_choice, N for ask_multi_select.
`confirmed`	Yes	ask_confirm only: true for yes, false for no.
`free_text`	Yes	Optional free-text note supplied alongside a choice.
`next_step`	Yes	What you should do next. Follow it.
`elapsed_ms`	Yes	Wall-clock time spent waiting for the user, in milliseconds.
`client_elicitation`	Yes	Whether the connected client declared MCP form-elicitation support during initialize.
`auto_reject_suspected`	Yes	True when a decline came back so fast that the client probably auto-rejected rather than asking the user.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.2.0Sep 14, 2026

TDQS

A4.5/5.0

Behavior4/5

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

Annotations already declare readOnly and non-destructive, and the description adds the wait-for-answer blocking behavior plus the return format. It does not address timeout or cancellation behavior, but the schema's timeout_ms parameter and its description cover the timeout default.

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?

Four short sentences front-load the core behavior, then usage context, parameter advice, and return shape. Every sentence carries information, and there is no filler or repetition of schema details.

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?

With 100% schema coverage, rich annotations, an output schema, and this description, the agent has everything needed to choose and call the tool: purpose, when to use it, min/max semantics, and return values. There are no obvious gaps.

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?

The schema already documents all five parameters (100% coverage), so the baseline is 3. The description adds value with operational advice to set min/max only when the count genuinely matters and to omit them otherwise, helping an agent decide how to invoke the tool.

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 'Ask the user to select one or more options from a list and wait for the answer,' naming a specific verb, object, and behavior. The subset examples ('which platforms to target, which checks to enable') clearly set it apart from single-choice, confirm, and free-text sibling tools.

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 explicitly tells the agent when to use the tool ('Use this when the user should pick a subset') with concrete examples, plus guidance on min/max. It stops short of naming sibling tools as alternatives for non-subset cases, so the exclusion is implicit rather than stated.

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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