linkedin_detect_business_signals

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

With no annotations, the description carries the burden of behavioral disclosure. It clearly communicates a non-mutating 'scan' action and the type of output signals, but it does not disclose potential external data dependencies, auth requirements, rate limits, or any limitations around profile visibility. The core behavior is stated, but depth is missing.

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?

The description is a single, front-loaded sentence with no filler. It names the resource, the action, and the output categories immediately, making it easy to parse and retain.

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 tool has only two parameters and no nested objects, so the description is sufficient for basic invocation once profileId is known. However, there is no output schema and no annotation, and the description does not explain what the returned signals look like or when this tool should be preferred over the many activity-analysis siblings, leaving meaningful gaps.

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?

Schema coverage is 50%, with profileId only described as 'Profile ID' and category having no description. The description adds some semantic value by explaining the categories ('growth, marketing, operational, and technical tracking signals'), but it does not clarify the exact meaning of the enum values, and the mismatch between 'technical' in the description and 'tracking' in the enum could confuse the agent.

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 states a specific verb ('Scans'), a clear resource ('profile activity'), and a distinct outcome ('discover growth, marketing, operational, and technical tracking signals'). The mention of GA4, GTM, CAPI, and Attribution clearly distinguishes this from siblings like linkedin_analyze_recent_activity or linkedin_get_recent_activity.

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 implies the tool should be used when the agent needs to detect tracking or business signals from a LinkedIn profile's activity. However, it provides no explicit when-to-use guidance, no exclusions, and no reference to alternative sibling tools, leaving the selection logic to inference.

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