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

The readOnlyHint annotation already covers safety, yet the description adds genuinely useful traits: it works without an account (auth-free), it is free, and it enumerates the sign-in method variants (oauth, oauth_geraet, bridge_key, legacy service user, anonym) plus device limits for device sessions. That is substantive behavioral context beyond the annotation.

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?

Three sentences, all front-loaded on what is returned before the usage trigger. The middle sentence, listing sign-in variants and device limits, is somewhat dense, but no sentence is filler.

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?

With no output schema and no parameters, the description carries the entire burden of explaining return contents, and it does so thoroughly — account fields, sign-in method, and device limits. An agent knows exactly what it will get back and under what conditions.

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 tool takes zero parameters, so the baseline is 4 and there is nothing for the description to clarify. It correctly omits any parameter discussion rather than inventing options.

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?

The description names the exact resource (the FilmLab account: email, user id, name, tier, credits) and the exact secondary payload (how the connection signed in, including the sign-in-method enum). It is unmistakably distinct from diagnostic siblings like lab_diagnose or identity checks like lab_identitaet_pruefen.

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?

It gives a concrete trigger: 'Call it when results look like someone else's — two clients signed in with two accounts see different projects.' That is an explicit when-to-use condition. It does not, however, name an alternative tool or state when not to use it, so it stops short of a 5.

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