linkedin_system_status

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

Annotations already mark this as read-only, idempotent, and non-destructive. The description adds useful behavioral context by detailing what data is reported (cache, rate-limit quota, local storage) and how DRY_RUN status is surfaced, which goes beyond the structured annotations.

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 concise sentences: the first states the tool's purpose with specific output categories, the second provides concrete usage guidance. Every word adds value, with no redundancy or 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?

For a zero-parameter, read-only diagnostic tool, the description is fully sufficient. It covers what the tool does, what metrics are included, and when to use it, without needing to explain return values (since there is no output schema) or input complexity.

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 input schema has zero parameters, so there is no parameter-specific information needed. The baseline for 0-parameter tools is 4, and the description appropriately focuses on the tool's output and purpose rather than inputs.

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 uses a specific verb 'Report' and explicitly enumerates the categories of server health information (configuration, browser state, cache stats, rate-limit quota, local storage counts). This clearly distinguishes it from related tools like auth_status or get_settings by focusing on diagnostic server health metrics.

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?

The description gives clear usage context: diagnose slowness, unexpected refusals, or confirm DRY_RUN before writes. It does not explicitly name alternatives or provide exclusions, but the intended use cases are well-defined and actionable.

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