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

Annotations already establish the read-only, idempotent, closed-world safety profile, so the description's job is to add behavioral context — which it does by disclosing the payload contents (volume, competition, GSC metrics, cluster membership) and that results are paginated. It stops short of stating default ordering or what an empty result means, but it is well past what annotations cover.

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?

Two compact sentences that front-load the resource and then the payload, with no filler. The parenthetical source list is dense but each item carries information about where candidates originate.

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 reasonably compensates by naming the returned fields, and it covers pagination and filtering for a 5-parameter all-optional list tool. Gaps remain around default sort order and the fact that the default status filter is a union of approved and pending, but nothing essential to invoking it correctly is absent.

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 80% (limit defaults, status enum values, query substring, project_id id-or-slug are all documented in the schema), so the baseline is 3. The description's 'filter by status and substring' largely restates the schema rather than adding format or default nuance the schema lacks.

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 gives a concrete verb and resource ('Keywords Seonix researched for the project'), enumerates the data sources (seed AI, planner, Search Console, autocomplete, user-added) and the payload fields (volume, competition, GSC numbers, cluster membership). It implicitly separates this from gsc_top_queries and list_clusters by framing these as Seonix-researched candidates, but it never names a sibling 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?

'Paginated; filter by status and substring' points at how to narrow results, but it does not state when an agent should pick this over gsc_top_queries, list_clusters or get_cluster, nor any prerequisites like project selection. Usage is implied rather than prescribed.

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