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Track usage

autumn_track_usage
Destructive

MUTATES Autumn billing data — records a usage event (deducts/credits a feature balance). Provide EITHER feature_id OR event_name. Autumn API: POST /v1/balances.track.

Input Schema

NameRequiredDescriptionDefault
valueNoAmount of usage to record. Defaults to 1. Negative values credit the balance.
entity_idNoEntity id for entity-scoped balances.
timestampNoUnix timestamp (ms) for the event. Defaults to now.
event_nameNoEvent name to track usage for. Provide this OR feature_id.
feature_idNoThe feature to track usage for. Provide this OR event_name.
propertiesNoAdditional properties to attach to the usage event.
customer_idYesThe ID of the customer.
idempotencyKeyNoOptional key to dedupe retried events.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4/5.0
Behavior4/5

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

Annotations only give destructiveHint=true; the description adds real value on top by declaring this MUTATES billing data, that it can deduct or credit a balance, and the exact API route being hit. It doesn't cover error behavior or what happens if the customer has no balance, which keeps it from a 5.

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?

Three short sentences, front-loaded with the mutation warning, then the call constraint, then the endpoint. Nothing is wasted and the highest-risk information appears first.

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

Completeness4/5

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

For a destructive billing mutation with eight params and no output schema, the description covers the critical facts: that it mutates, that it adjusts balances, and the feature_id/event_name branch. It could say more about what the response returns (resulting balance, dedupe behavior) since no output schema exists, but the essentials are present.

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 coverage is 100%, so all eight parameters are already documented, including the feature_id/event_name exclusivity. The description restates that alternation but adds no new syntax, defaults, or interaction detail beyond the schema — baseline 3.

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

Purpose5/5

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

States a specific verb and resource (records a usage event), the business effect (deducts/credits a feature balance), and the underlying endpoint (POST /v1/balances.track). No sibling does this, so the agent can distinguish it immediately.

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

Usage Guidelines3/5

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

The only routing guidance is the parameter constraint 'Provide EITHER feature_id OR event_name', which is a call-shape rule rather than when-to-use guidance. Nothing says when to pick this over autumn_check or when not to call it (e.g., test vs production customers), so usage is only implied by the name and effect.

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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