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

Adds substantial context beyond the annotations: it charges exactly one AI-gateway operation against the org's shared monthly ceiling (not a plan quota), the page crawl and SERP fetch are free, and a URL is graded fresh regardless of domain or audit history. It also warns that `grade` is a qualitative AI read rather than a calibrated score, and documents key output `state` values.

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?

Dense but front-loaded: purpose, then billing, then input scope, then output-reading caveats. Nearly every sentence earns its place, though the parenthetical '(built together ... recommendations)' has a stray unbalanced paren and some cost/state detail could be tightened.

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?

With no output schema, the description compensates by explaining the return shape: `state` values, `analysed` carrying the full report, and the `coverage.serpUnavailable` / `competitorsCrawled` fields to check. Combined with billing and input-scope detail, an agent has everything needed to call and interpret this tool 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%, so the baseline is 3; the schema already documents projectId, url, keyword, languageCode and locationCode including their defaults. The description only adds a nuance on `url` (out-of-domain URLs are acceptable and graded fresh), which slightly extends but does not meaningfully exceed the schema.

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+resource: on-page recommendations plus an AI content grade for one page, benchmarked against pages ranking for its target keyword. It is clearly distinguishable from siblings like get_content_page_metrics or the get_audit_* family, and it explicitly declares what it is not (no AI-written-content detection).

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 concrete operational guidance: 'ALWAYS narrow on state first', how to read `target_unreachable` (ordinary, not a zero score), and to check `coverage.serpUnavailable` / `competitorsCrawled` before trusting the comparison. It also clarifies the url scope (any http(s) URL, not only crawled project pages). It stops short of naming a specific alternative sibling tool to use instead in any condition.

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