linkedin_analyse_profile

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds valuable context beyond annotations by explaining that the score is computed by this server from section presence/substance and is not LinkedIn's own metric. This prevents misinterpretation and clarifies the tool's internal logic.

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 sentences, both purposeful: the first states the core action, the second clarifies the metric origin and provides a use-case example. No fluff, front-loaded with the main verb.

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 adequately covers a single-parameter tool with no output schema. It explains what it does, how the score is computed, and when to use it. It could mention the exact return format (e.g., score plus list of suggestions), but 'return specific, actionable improvement suggestions' already implies the output structure.

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 description coverage is 100%, with the single 'identifier' parameter fully documented (me, public identifier, URL, or URN). The description does not add extra parameter semantics, but the schema already carries the burden, so baseline 3 applies.

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 ('Score profile completeness') and resource ('profile') and clearly distinguishes itself from siblings like linkedin_get_profile or linkedin_get_profile_analytics by focusing on actionable improvement suggestions. The explicit use case 'how can I improve my profile?' reinforces its unique purpose.

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 provides a clear usage context: 'Use this to answer "how can I improve my profile?"' which implies the tool is for profile improvement advice. It does not explicitly mention alternatives or exclusions, but the context is strong enough to guide selection among siblings.

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