request_indexingSubmit up to 50 URLs for search-engine indexing (Google/Bing) via SEOPro AI auto-indexing. Requires the auto-indexing feature on the account. Show the exact URL list and obtain explicit user approval first; every call requires confirm_indexing=true.
| Name | Required | Description | Default |
|---|---|---|---|
| urls | Yes | ||
| website_id | Yes | ||
| confirm_indexing | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses externally visible side effects (submitting URLs to Google/Bing indexing), the dependency on the account feature, and the critical user-approval requirement. This meaningfully exceeds what the annotations alone communicate, especially given destructiveHint=true.
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 concise sentences deliver the action, scope, prerequisites, and mandatory approval workflow with no filler. The most important behavioral rules are front-loaded.
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?
The description covers the main operational constraints: URL cap, required account feature, approval workflow, and confirmation flag. It is complete enough for calling the tool, though it could be slightly stronger by referencing get_indexing_status for follow-up and resolving the confirm_indexing schema ambiguity.
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 0% schema description coverage, the description must compensate, and it does explain the 50-URL cap and the confirm_indexing=true requirement. However, it does not clarify the role of website_id beyond the schema's title, and it introduces a mild ambiguity by saying confirm_indexing is required while the schema marks it optional with default false.
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 ('Submit') with a clear resource ('up to 50 URLs for search-engine indexing') and names the search engines (Google/Bing). It is immediately distinguishable from sibling status-checking tools like get_indexing_status.
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 prerequisites (auto-indexing feature must be enabled), a required user-approval workflow, and the confirmation flag requirement. It does not explicitly name alternatives or say when not to use it, but the action is straightforward enough that the usage context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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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.