human_input

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Ask the user for free-form text

ask_text

Read-only

Ask users an open-ended question and collect typed responses for inputs that cannot be enumerated, such as URLs, identifiers, or naming preferences.

Instructions

Ask the user an open-ended question and wait for a typed answer. Use this only when the answer cannot be enumerated — a URL, a credential-free identifier, a naming preference, or extra context you cannot infer. If a handful of concrete answers would cover most cases, use ask_choice instead so the user can answer with one keystroke. Returns the typed string in answer.

Input Schema

TableJSON Schema

Name	Required	Description
`default`	No	Optional pre-filled answer the user can accept or edit.
`question`	Yes	The open-ended question to ask. Prefer ask_choice when the reasonable answers are enumerable.
`timeout_ms`	No	Optional override, in milliseconds, for how long to wait for the user. Defaults to the server setting (HIM_TIMEOUT_MS, 300000).
`placeholder`	No	Optional format hint shown inside the input, e.g. "owner/repo" or "an absolute Windows path".

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 provide readOnlyHint and openWorldHint, so the safety profile is covered. The description adds behavioral context beyond annotations: it states the tool 'waits for a typed answer' and 'Returns the typed string in `answer`,' clarifying the interaction model and return value. This is useful but not exhaustive; it doesn't mention cancellation or error handling, though that's minor given 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 two sentences with zero fluff. The core purpose is front-loaded, followed by targeted usage guidance and a clear return statement. Every sentence earns its place, making it highly efficient for an agent to parse.

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 tool with only one required parameter and three optional ones, the description covers all essential aspects: what it does, when to use it, and what it returns. The output schema exists, so return format is further documented. Annotations cover safety, and the alternative is explicitly named. No critical information is missing for correct invocation.

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 four parameters already have meaningful descriptions in the schema. The tool description does not add additional parameter-specific semantics beyond what the schema provides. Per the rubric, baseline 3 is appropriate when the schema carries the parameter documentation burden.

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 states a clear verb+resource: 'Ask the user an open-ended question and wait for a typed answer.' It also explicitly distinguishes from ask_choice by naming the sibling and the condition for its use, making the tool's purpose unambiguous.

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 and when-not-to-use guidance: 'Use this only when the answer cannot be enumerated' with concrete examples, and 'If a handful of concrete answers would cover most cases, use ask_choice instead.' This directly routes the agent to the correct sibling tool.

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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