Everything waiting on the merchant in their own store: recommendations that need a decision (escalated ones first, with what to check) and article drafts ready to publish. Returns the ids decide_recommendation and publish_draft take.
| Name | Required | Description | Default |
|---|---|---|---|
| api_key | No | Store-bound SeoAiX API key (inxy_sk_…). Optional if already sent as an Authorization: Bearer header. |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description shoulders the behavioral burden. It adds significant value by stating the ordering criteria ('escalated ones first, with what to check') and naming the specific IDs returned by the tool that map directly to subsequent API calls.
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 highly efficient, packing a broad scope and technical details into two sentences. While the first sentence is slightly dense, the information density justifies the score.
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?
Given there is no output schema, the description provides comprehensive guidance on what the user will receive—namely, IDs mapped to specific action tools. This makes the tool highly actionable for an agent.
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?
Since the input schema coverage is 100% and the tool only requires a single optional parameter, the description adds no semantic value or further detail beyond what the structured schema already provides. The baseline score of 3 is appropriate.
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 clearly defines its role as a tracking tool for pending tasks. It precisely names the resources (recommendations and drafts) and explicitly differentiates its function from the execution tools, specifically naming 'decide_recommendation' and 'publish_draft' as downstream actions.
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 provides clear context for when to use the tool (when the merchant needs to see their outstanding approvals or drafts). However, it does not provide prescriptive guidance on the workflow or when to choose this tool over other listing/audit tools.
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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