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Intrect-io

lyra-browser

Official
by Intrect-io

ask_user_to_do

Asks the user to handle sensitive steps like credentials, CAPTCHAs, 2FA, or payment confirmation, highlights the target element, and returns awaiting_user.

Instructions

Ask the user to perform a step you must not do yourself.

Use for credentials, CAPTCHAs, 2FA, or payment confirmation. Highlights the relevant element when selector is given, then returns an awaiting_user envelope. Relay the instruction, then poll the page (read_page / get_url) to detect completion.

Requires an attended (headful) session — in headless mode there is no user to ask, so this returns unattended rather than making you wait.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
selectorNo
instructionYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.7/5.0
Behavior5/5

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

No annotations are provided, so the description carries the full burden and discharges it: it discloses the side effect (highlighting the element when selector is given), the return contract ('awaiting_user' envelope), the environmental prerequisite (attended/headful session), and the degradation behavior ('unattended' rather than waiting). This is exactly the behavior an agent needs before committing to a blocking human interaction.

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 with purpose, then use cases, then mechanics, then the environment caveat. Every sentence adds a distinct fact and none is redundant.

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?

An output schema exists, yet the description still names the two possible envelopes, which is the key decision-relevant outcome. Combined with the headful prerequisite and the polling instruction, nothing needed to invoke or react to this tool 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 0%, so the description must compensate. It meaningfully explains 'selector' (highlights the relevant element when given, optional/default null), but 'instruction' is only implied via 'Relay the instruction' without stating that it is the required text shown to the user. Partial compensation for a low-coverage 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?

States a specific verb+resource ('Ask the user to perform a step') and immediately scopes the domain with 'you must not do yourself', which distinguishes it from all the automated siblings like click/type_text. An agent can tell this is the human-in-the-loop escape hatch without opening the schema.

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?

Gives explicit use cases (credentials, CAPTCHAs, 2FA, payment confirmation) and an explicit when-not: headless mode returns 'unattended' rather than blocking. It also prescribes the follow-up workflow (relay, then poll read_page/get_url), which is actionable operational guidance.

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