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

No annotations provided. Description mentions cost ($0.005–$0.05 USDC), which is useful, but lacks disclosure of other behavioral traits such as authentication requirements, rate limits, or whether it is read-only. The scraping nature implies read but not explicit.

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?

Description is short and front-loaded with purpose. Includes example call and cost info. No unnecessary words, but could be slightly more structured (e.g., separate sections).

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 simple one-parameter tool with no output schema, the description is moderately complete. It states what data is scraped and costs, but does not describe return format or any pagination behavior. Adequate but with clear 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 has one parameter 'company' with no description. Schema coverage is 0%. Description adds no semantic meaning beyond title; only provides an example value 'stripe'. Does not explain what format or conventions are expected for the company name.

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?

Clearly states it scrapes Glassdoor company pages and lists specific data types (rating, reviews, salary estimates). The tool name itself distinguishes it from other scraper siblings, but no explicit differentiation from similar employer scraper tools like scrape_indeed.

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?

Only says 'Use for employer-research agents,' which is vague. No guidance on when to use versus alternatives, no exclusions or prerequisites provided.

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