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create_meter

Define usage dimensions for billing products by specifying unit pricing and measurement details to track consumption.

Instructions

Create a meter (usage dimension) for a product

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
productIdYesThe product ID
nameYesMeter identifier (e.g. 'api_calls', 'tokens')
displayNameYesHuman-readable meter name
unitYesUnit of measurement (e.g. 'request', 'token')
unitPriceYesPrice per unit (e.g. '0.001')
Behavior2/5

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

No annotations are provided, so the description carries full burden. It states 'create' which implies a write/mutation operation, but doesn't disclose behavioral traits like required permissions, whether this is idempotent, what happens on duplicate names, error conditions, or rate limits. For a creation tool with zero annotation coverage, this is insufficient.

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, efficient sentence that front-loads the core purpose. There's zero waste or redundancy. It's appropriately sized for a tool with good schema documentation.

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?

Given this is a creation/mutation tool with no annotations and no output schema, the description is incomplete. It doesn't explain what a successful creation returns, error handling, or important behavioral context. The 100% schema coverage helps with inputs, but overall context for safe/effective use is lacking.

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 documents all 5 parameters thoroughly. The description adds no additional parameter semantics beyond implying the meter is for a 'usage dimension', which is already suggested by parameter examples like 'api_calls' and 'tokens'. Baseline 3 is appropriate when schema does the heavy lifting.

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 action ('create') and resource ('meter for a product'), specifying it's for a 'usage dimension'. It distinguishes from siblings like create_product or create_customer by focusing on meters specifically. However, it doesn't explicitly contrast with other meter-related tools (none exist in siblings), so it's not a perfect 5.

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?

No guidance on when to use this tool versus alternatives is provided. The description doesn't mention prerequisites, dependencies, or scenarios where this is appropriate versus other creation tools like create_product. It's a basic statement of function without contextual usage advice.

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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