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

Annotations already cover the safety profile (readOnlyHint, idempotentHint, openWorldHint, destructiveHint=false), so the bar is lower, and the description still adds meaningful context: the data is a non-comprehensive sample, every response carries a data_caveat, and a paid plan is required. That is exactly the kind of data-quality and access disclosure an agent needs. It does not discuss pagination or rate limits, which keeps it below a 5.

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 the core action before the dataset caveats, plus a one-line plan requirement. Every sentence carries information, though the parenthetical Ahrefs comparison is slightly extraneous for an agent that only needs to know the data is sampled.

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 an output schema present, the description need not explain return values, and it correctly focuses on dataset limitations, plan gating, and the caveat field. Coverage is solid for a two-parameter read tool; only guidance on result ordering or how the sample is drawn is missing.

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 coverage is 100% and both parameters are fully documented in the schema, so the baseline applies. The description adds only that results are 'sample rows' governed by a growing coverage set, which slightly flavors the limit parameter but adds no new syntax or format information.

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 opening sentence gives a specific verb and resource ('Look up observed backlinks for a domain') and the following sentences define the dataset's provenance (audit-fed graph), which separates it from the audit-oriented siblings. It stops short of naming any sibling tool by name, so the differentiation is indirect rather than explicit.

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 definition gives a real prerequisite ('Requires Basic plan ($15/mo) or higher') and warns the dataset is a sample, which implies spot-checking rather than exhaustive research. It never states when to prefer this over another tool or what the intended use case is, so the guidance is context rather than routing.

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