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

With no annotations provided, the description must carry the behavioral burden, and it does disclose key operational facts: it targets public profiles only and states a concrete pricing model ($0.02 per profile scraped). It omits other important behavior like rate limits, failure/partial-result handling, or auth requirements.

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?

Three short sentences, front-loaded with what the tool does, then usage, then cost. Efficient and scannable with negligible waste, though the pricing sentence is appended rather than integrated.

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?

Covers purpose, usage, and the notable pricing behavior for a simple 3-param extraction tool with no output schema. It lacks return-shape detail and failure/limit behavior, but is sufficient for an agent to invoke it correctly.

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% and each parameter (profileUrls, includeSkills, includeExperience) is fully documented in the schema, so the baseline is 3. The description adds no syntax or format detail beyond what the schema already provides.

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 (Extract) plus resource (public LinkedIn profile data) and enumerates the fields returned (name, headline, experience, company). It is immediately distinguishable from its sibling scrapers (instagram_scraper, tiktok_scraper, youtube_scraper) by naming the target platform explicitly.

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?

Gives clear use contexts ('enriching B2B leads', 'recruiting research'), which tells the agent when the tool is relevant. It does not, however, name alternatives or state exclusions (e.g., non-public profiles, rate limits), so it stops short of full when/when-not guidance.

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