linkedin_status

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

With no annotations, the description carries the full burden, and it does disclose one useful behavioral detail: "Does not return tokens." However, it omits other traits an agent would want, such as whether the check is a local lookup or a server-side session validation, and whether calling it has any side effects.

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 with no filler, and the core purpose is front-loaded ahead of the output constraint. Every word earns its place.

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?

The description implies a boolean session-stored answer and rules out token exposure, but never states what the response actually contains (e.g., a boolean, member identifier, or expiry info). With no output schema and no annotations, that gap is worth noting even for a zero-parameter 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 a 4 is appropriate. There is nothing for the description to disambiguate beyond confirming that no inputs are needed.

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 ("Show") and resource ("whether a member session is stored"), so the agent knows exactly what is being queried. It does not explicitly distinguish itself from siblings like linkedin_login or linkedin_logout, though the session-state framing makes the distinction inferable.

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?

There is no explicit when-to-use or when-not-to-use guidance, and no alternative tool is named. The agent must infer that this is a session pre-check before calling linkedin_profile or linkedin_create_post, which is reasonable but left unstated.

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