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

Since there are no annotations, the description carries the full burden and does an excellent job of fulfilling it. It explains crucial behaviors such as the cost per call, the data persistence side-effect (upserting), and the caching behavior governed by the 'refresh' parameter.

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 definition is direct and efficient. It front-loads the core purpose and then adds technical behavioral details in a single, cohesive statement. It avoids unnecessary fluff while being comprehensive.

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?

Given the small input schema, the description is exceptionally complete. It covers the input requirements, the expected output content, the financial cost, and the data management side-effects. No key behavioral or functional gaps remain.

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?

With 100% schema coverage, the baseline is 3. The description adds value by providing a concrete URL format example and linking the 'refresh' parameter directly to the cost/caching mechanism, adding context beyond the schema's structure.

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 clearly identifies the action ('Fetch') and the resource ('LinkedIn person profile'), specifying the exact data points returned (headline, role, history, education). However, it does not explicitly differentiate its scope from highly similar siblings like get_profile_summary.

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?

It provides a strong usage guide by detailing the operational cost (5 credits) and the persistence/side-effect behavior (upserted into people and linkedin_profiles). This context helps the agent understand the practical implications of using this specific tool.

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