Check your publisher analytics. Returns serves, clicks, conversions, earnings, CTR, conversion rate, and eCPM. Use this to see how your audience engages with recommendations.
| Name | Required | Description | Default |
|---|---|---|---|
| days | No | Lookback window in days (default 30) | |
| hub_id | No | Filter by hub | |
| agent_id | Yes | Your agent ID |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is known. The description adds valuable context by specifying the exact return fields (serves, clicks, conversions, etc.), which goes beyond what annotations provide. It does not discuss auth or data freshness, but given the simple read nature, this is sufficient.
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 two sentences with no redundancy. It front-loads the action and resource, then lists the return metrics, and ends with a practical usage scenario. Every word 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?
Given the tool's simplicity (3 params, all documented, no output schema, read-only annotations), the description adequately covers purpose, usage, and return values. It does not detail the return structure beyond the metric list, but for an analytics query tool, this is sufficient. The context from sibling tools further clarifies its unique role.
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 100%. The schema already documents all three parameters with descriptive text: days as lookback window, hub_id as filter, and agent_id as the required identifier. The description does not add information beyond the schema, so 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 states the tool checks publisher analytics and enumerates the specific metrics returned (serves, clicks, conversions, earnings, CTR, conversion rate, eCPM). The verb 'check' plus resource 'publisher analytics' is specific, and the list of metrics distinguishes it from sibling tools like registration or monetization.
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 explicitly provides a use case: 'Use this to see how your audience engages with recommendations.' This gives clear context for when to invoke the tool. It does not explicitly mention exclusions or alternatives, but the sibling tools serve clearly different purposes, so no additional disambiguation is necessary.
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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Each tool has a clear, distinct purpose: registration, earning, tracking, and feedback. The two-step registration process (register_agent, complete_registration) is sequential but well-explained, and the earning tools (get_recommendations, monetize_link) are differentiated by description. No major overlap that would cause misselection.
All six tools follow a consistent verb_noun snake_case pattern (e.g., check_publisher_stats, complete_registration, get_recommendations). There is no mixing of conventions or vague verbs.
Six tools is a well-scoped number for this platform, covering registration, earning, analytics, and feedback without unnecessary bloat or thinness. Each tool earns its place in the set.
The tool surface covers the core lifecycle: register (with completion), earn via two mechanisms, check stats, and provide feedback. Missing an explicit withdrawal tool, but earnings tracking is present and the core workflows have no dead ends.