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

With no annotations present, the description carries the full disclosure burden and meets it: it signals a read-only operation ('are read'), constrains the data scope to connections opened to agents, lists the three counting services with their distinct metric sets, and reveals the non-obvious aggregation behavior that breakdown rows do not sum to totals. It also discloses what the response contains ('the answer's period and notes say what was actually counted'), which is especially valuable given there is no output schema.

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 sentences with no filler; the service/metric enumeration is front-loaded, followed by the connection scope and the totals caveat. Every sentence earns its place, though the first sentence is a long multi-part list that must be parsed carefully because it interleaves metrics and dimensions per service.

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 7-parameter, multi-source aggregation tool with no annotations and no output schema, the description covers the data sources, per-source metrics and dimensions, the read scope, and the response's self-declared period and coverage. Anything an agent needs to call it correctly and interpret the results is either here or in the already-detailed parameter schema; no critical gap is evident.

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%, so the baseline is 3; the description still adds meaning beyond the schema by mapping which breakdown dimensions each service supports (tying to 'by') and warning that totals and breakdown rows behave differently. This helps an agent pick dimensions that a given open connection can actually produce. The per-parameter value beyond the schema is modest, but the aggregation semantics are genuinely additive.

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 identifies the resource precisely — website traffic metrics — and enumerates exactly which metrics and breakdown dimensions come from each of the three counting services (Google Search Console, Vercel Web Analytics, Google Analytics 4), so an agent can tell what data this tool returns. However, it is phrased as a topic clause ('How a project's website was visited...') rather than an explicit action verb, so the read/return operation is implied rather than stated. Among the sibling list it is the only analytics tool, so no sibling differentiation is required.

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 description gives clear context for when the data is valid: only connections opened to agents are read, the available services are the three named ones, and the caveat that the totals are the site's while breakdown rows do not add up to them. It does not name when-not-to-use conditions or alternatives, but no sibling tool offers comparable traffic data, so exclusion guidance would be redundant.

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