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Start Stream

start_stream

Connect an EEG device and begin a live streaming session; requires confirmation and a device test first, with an idle watchdog to stop abandoned streams.

Instructions

Connect an EEG device and START a live streaming session on the user's head. Requires confirm=True; call test_device first. Track with stream_status(). Idle watchdog: if no stream_status()/get_live_session() poll happens for idle_timeout_sec (default 900), the session is stopped and the device disconnected automatically — an abandoned stream never keeps running on the user's head. Any poll resets the timer; idle_timeout_sec=0 disables the watchdog.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
portNo
confirmNo
ip_portNo
source_idNo
chunk_sizeNo
ip_addressNo
n_channelsNo
session_idNo
device_typeYes
mac_addressNo
stream_nameNo
serial_numberNo
connection_typeNo
idle_timeout_secNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.5.1

TDQS

A4.3/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and does so well: it discloses the confirm gate, the prerequisite test_device call, and the idle watchdog (auto-stop + device disconnect after idle_timeout_sec, empty stream never left running, any poll resets, idle_timeout_sec=0 disables). This is substantial behavioral context about an operation on the user's body.

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?

Front-loaded with the purpose, then the confirm/prerequisite requirement, then the watchdog caveat. Dense but each sentence earns its place; the watchdog explanation is slightly long but warns of a real safety-relevant behavior.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return values need not be explained, and the safety/lifecycle behavior is covered. However, for a complex 14-parameter device-connection tool with 0% schema coverage, the omission of any device configuration semantics leaves a meaningful gap.

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

Parameters2/5

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

Schema coverage is 0% for 14 parameters, so the description must compensate, yet it only explains confirm and idle_timeout_sec. Crucially, the required device_type parameter and all connection fields (port, ip_port, ip_address, mac_address, serial_number, connection_type, n_channels, chunk_size, source_id, session_id, stream_name) are left completely undefined.

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 and resource — connect an EEG device and start a live streaming session — and names related siblings (test_device, stream_status, stop_stream implicitly), so the agent can distinguish it from other device tools 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?

Explicitly states prerequisites and ordering: 'Requires confirm=True; call test_device first' and 'Track with stream_status()'. It routes the agent to the right siblings and conditions rather than leaving sequencing to inference.

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