get_search_performanceGet the Google Search Console performance summary for a website: clicks, impressions, CTR, average position, top keywords, AI-assistant traffic sources and device/country breakdowns.
Dates are YYYY-MM-DD; defaults to the last 30 days.
| Name | Required | Description | Default |
|---|---|---|---|
| end_date | No | ||
| start_date | No | ||
| website_id | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds meaningful behavioral detail by specifying date format (YYYY-MM-DD) and the default time range of the last 30 days, which helps an agent understand how the tool will behave when optional dates are omitted.
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?
The description is compact and front-loaded: it states the tool's purpose in the first line, lists the key outputs in a scannable list, and adds only the essential date behavior in a second short sentence. No words are wasted.
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 three parameters and no output schema, the description covers the main purpose, expected output categories, and date semantics. It is complete enough for an agent to call the tool correctly for a typical use case. It could be more complete by noting how this tool relates to overlapping siblings, but that gap is already captured in usage_guidelines.
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 0%, so the description must carry parameter meaning. It directly clarifies that dates are YYYY-MM-DD and that they default to the last 30 days, and it identifies 'website' as the scope for website_id. It does not explain constraints like start_date <= end_date, but the provided semantics add meaningful value beyond bare parameter names.
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 uses a specific verb and resource: 'Get the Google Search Console performance summary for a website,' and lists concrete metrics such as clicks, impressions, CTR, average position, top keywords, AI-assistant traffic sources, and device/country breakdowns. However, it does not distinguish itself from overlapping siblings like get_top_search_keywords and get_ai_search_traffic, so it stops short of full differentiation.
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 implies the tool should be used when an overall Google Search Console performance summary is needed, and it notes the default 30-day behavior. However, it gives no explicit when-not-to-use guidance or alternatives, especially given siblings that cover top keywords and AI traffic specifically.
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.