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halo_help

Get targeted guidance for Brilliant Labs Halo and Frame glasses operations, including BLE pairing, Lua scripting, display, Noa, and hardware topics. Specify a topic for focused instructions, or omit for an overview.

Instructions

Halo help - operations, BLE pairing, Lua, Noa.

Return Format

{success, message, result: {topic, text}}.

Examples

await halo_help() await halo_help("lua")

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicNoFocus: pairing, lua, display, noa, ble, hardware. Omit for the capability-matrix overview.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

B3.2/5.0
Behavior3/5

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

Annotations are empty, so the description must carry the burden. It does disclose the return format ({success, message, result}) and provides example calls, which gives some behavioral context. However, it does not state that the operation is read-only, describe error handling, or mention any side effects. For a help tool this is minor, but the lack of explicit safety disclosure keeps it at a 3.

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?

The description is concise and well-organized with sections for Return Format and Examples. The opening line is a bit telegraphic but still informative. There is no redundancy, and the structure front-loads the purpose. It earns a 4 for efficiency, though the opening could be slightly more descriptive.

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 simple tool with one optional parameter, the description is fairly complete. It specifies the return format and provides examples. The schema covers the parameter details. It does not mention edge cases like invalid topics, but given the low complexity and presence of an output schema description, it is sufficiently complete.

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%, and the schema already explains the 'topic' parameter with a list of focus areas and the note about omitting it for the overview. The description adds examples (e.g., halo_help('lua')) but does not materially extend the parameter semantics beyond what the schema provides. Baseline of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states 'Halo help - operations, BLE pairing, Lua, Noa.' which clearly indicates the tool provides help on these topics. It is not a tautology, and the verb 'help' is implied by the tool name and the list. However, it could be more explicit about the action (e.g., 'Retrieves help documentation for...'), so it misses a fully specific verb+resource phrasing.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus sibling tools like halo_device, halo_shutdown, or halo_dashboard. There is no mention of alternatives or exclusions. The examples show calls but do not explain when to invoke them, leaving the agent to infer usage from the topic list in the schema.

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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