get_search_trendsGet monthly search-performance trends (clicks, impressions, CTR, average position) for the last N months. Use to spot growth or decay.
| Name | Required | Description | Default |
|---|---|---|---|
| months | No | ||
| website_id | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already carry the safety profile (readOnlyHint=true, idempotentHint=true, destructiveHint=false), so the bar is lower. The description adds the monthly aggregation and metric scope but discloses no further operational behavior such as return shape, pagination, or error handling. Moderate added value, consistent with annotations — no contradiction.
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 tight sentences with zero waste: the first packs verb, resource, metrics, and time window; the second adds the use case. Nothing repeats the title 'Get Search Trends' and the description is front-loaded with the core function. Every sentence earns its place.
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 read-only tool with one required parameter and no output schema, the description covers purpose, metrics, and granularity well. Since no output schema exists, an explicit statement of the return shape (one row per month) would strengthen it, but 'monthly trends for the last N months' makes that inferable. Only a minor gap.
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?
With schema description coverage at 0%, the description must compensate. 'For the last N months' usefully implies that `months` controls the lookback window, and `website_id` is reasonably self-evident. However, it never names the parameter explicitly, offers no valid range, and leaves the default behavior to the schema — only partial compensation for zero schema documentation.
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 ('Get') with a specific resource (monthly search-performance trends) and enumerates the exact metrics (clicks, impressions, CTR, average position) plus the time grain (monthly, N months). Clear and informative; however, given the near-identical sibling get_search_performance, the lack of explicit differentiation keeps it from a 5.
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?
'Use to spot growth or decay' gives an explicit use case, which is better than no guidance. But with 17 siblings including the ambiguous get_search_performance, there is no when-not-to-use statement and no routing to alternatives, leaving the selection decision largely to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools target a distinct resource and action, making selection straightforward. Minor overlap exists between get_ai_search_traffic and get_search_performance's AI-assistant traffic section, and among the three search-performance reporting tools, but descriptions are clear enough to avoid major confusion.
All tools follow a consistent lowercase snake_case verb_noun pattern: check_, generate_, get_, list_, publish_, request_, run_. The verbs are descriptive and every noun object clearly identifies the resource being acted on.
At 18 tools the set is slightly above the ideal 3-15 range, but the scope is broad enough to justify it: website management, article generation, publishing, search analytics, AI search, indexing, backlinks, and auditing. No tool feels redundant enough to remove.
The surface covers the main SEO lifecycle well: websites, keyword plans, articles, publishing, search performance, indexing, backlinks, and audits. Obvious gaps are article update/delete operations and website removal, but agents can work around these for most core workflows.