Muse login

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

With no annotations, the description carries the full behavioral burden and does disclose the key non-obvious trait: this launches a browser window and blocks waiting for an interactive human Meta sign-in, which is not derivable from the schema. It omits what happens on timeout or failure (e.g., error vs. status return), so it is not fully complete.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two short sentences, front-loaded with the action and followed by the usage condition; no filler or redundancy.

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

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

For a one-parameter, no-output-schema tool, the description covers what it does, its side effect, and when to call it. Only post-call expectations (success/failure signaling, whether it returns login state) are left unstated.

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

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

The single parameter timeout_sec is already fully documented in the schema (100% coverage), including default and bounds. The description's 'wait for sign-in' phrasing implies blocking behavior but adds no format or default detail beyond the schema, so the baseline of 3 applies.

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

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

States a specific action (open muse.ai in the dedicated Chrome window) and its outcome (wait for Meta sign-in), so the agent knows exactly what the tool performs. It is clearly distinguishable from siblings like muse_status, which it references by name rather than duplicating.

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

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

Gives an explicit trigger condition: 'Use when muse_status reports loggedIn=false,' which ties the tool to a specific sibling's output. It stops short of stating when not to use it (e.g., already logged in, or while another login is pending), so there is a small amount of inference left.

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