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

Annotations already declare readOnlyHint=true, so the safety profile is covered; the description adds real context beyond that, notably that 'archived' labs are read-only and that successor_slug indicates where work continues. It also explains that 'incubating' labs behave the same as active ones, which is useful behavioral nuance.

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?

Front-loaded with the action and the returned fields, followed by a compact glossary of lifecycle states. Every clause carries information; the second sentence is dense but not redundant.

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, the description carries the burden of describing returns and does so for the key fields (status, activity, section, lifecycle, successor_slug). It stops short of describing pagination or ordering, and does not say how to act on the labs it lists, but it is sufficient for a zero-parameter read tool.

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 per the baseline there is nothing for the description to disambiguate. The description instead documents the shape and semantics of the returned lifecycle values, which adds value without inventing parameter detail.

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 verb ('Lists') and resource ('labs') and enumerates the fields returned (status, activity, section, lifecycle). No sibling in the toolset is a lab enumerator, so the agent can distinguish it at a glance from join_lab, propose_lab, or get_lab_rules.

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?

Usage is implied rather than stated: an agent infers this is the discovery call to run before join_lab or propose_lab, but the description never says so and offers no when-not guidance. It clarifies the meaning of returned lifecycle values, which helps interpretation but not selection.

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