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track_event

Record customer usage events for metered billing by specifying meter ID, customer ID, and usage value to track consumption data.

Instructions

Track a single usage event for a customer

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
meterIdYesThe meter ID to track against
customerIdYesThe customer's external ID
valueYesThe usage value (e.g. '1', '1500')
timestampNoISO 8601 timestamp (defaults to now)
metadataNoOptional metadata key-value pairs
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action ('track') but doesn't clarify if this is a write operation, what permissions are needed, how errors are handled, or if it's idempotent. This leaves significant gaps for a tool that likely mutates data.

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

Conciseness5/5

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

The description is a single, direct sentence that efficiently conveys the core action without any fluff or redundancy. It's appropriately sized and front-loaded with essential information.

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

Completeness2/5

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

For a tool with 5 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain the return value, error conditions, or behavioral nuances, leaving the agent with incomplete guidance for proper invocation.

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?

The description doesn't add any parameter-specific information beyond what's already in the schema, which has 100% coverage with clear descriptions for all parameters. This meets the baseline for adequate but unenriched parameter context.

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 ('track') and resource ('a single usage event for a customer'), making the purpose unambiguous. However, it doesn't explicitly differentiate from its sibling 'track_events_batch', which handles multiple events, leaving some room for confusion.

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 like 'track_events_batch' for multiple events or 'get_usage' for retrieval. It lacks context about prerequisites or typical scenarios, offering minimal usage direction.

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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