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get_customer_logs

Retrieve paginated activity logs for a specific customer to monitor subscription billing events and track customer interactions.

Instructions

List activity logs for a customer. GET /customers/{customerId}/logs. Returns paginated log entries.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
customerIdYesCustomer ID (required)
pageNoNoPage number (default: 1)
itemPerPageNoItems per page (default: 25)
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It discloses that the tool returns 'paginated log entries', which is useful behavioral context beyond the basic 'list' action. However, it doesn't mention authentication requirements, rate limits, error conditions, or what types of activities are logged, leaving gaps in transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately concise with two sentences that each serve a purpose: stating the action and disclosing pagination behavior. It's front-loaded with the core purpose. The HTTP method inclusion ('GET /customers/{customerId}/logs') is slightly redundant but not wasteful.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a read-only tool with 100% schema coverage but no annotations or output schema, the description provides adequate basic information about what it does and its pagination behavior. However, it lacks details about the structure of returned log entries, error handling, or authentication context that would make it more complete for an AI agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already fully documents all three parameters (customerId, pageNo, itemPerPage). The description adds no additional parameter semantics beyond what's in the schema, which meets the baseline expectation when schema coverage is high.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('List') and resource ('activity logs for a customer'), making the purpose unambiguous. However, it doesn't differentiate from sibling tools like 'get_subscription_logs' or 'list_customers', which would require explicit comparison to achieve a perfect score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. With many sibling tools available (e.g., 'get_customer', 'get_customer_invoices', 'get_subscription_logs'), there's no indication of when this specific log-fetching tool is appropriate versus other customer-related queries.

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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