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amberflo

by io.usefulapi

Query usage for a meter

amberflo_get_usage
Read-only

Query aggregated usage for a single meter over a time range, optionally grouped/filtered. API: POST /usage/.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filterNoDimension filter: map of dimension name -> allowed values.
group_byNoDimension names to group results by, e.g. ["customerId"].
take_limitNoReturn only the top N groups.
aggregationYesAggregation function: SUM | COUNT | MIN | MAX.
meter_api_nameYesThe meterApiName to query (from amberflo_list_meters).
take_is_ascendingNoSort order for `take` (default false = descending).
end_time_in_secondsNoRange end, unix epoch seconds. Defaults to now if omitted.
start_time_in_secondsYesRange start, unix epoch seconds (inclusive).
time_grouping_intervalYesBucket size: HOUR | DAY | WEEK | MONTH.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A3.9/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, so description does not need to restate safety. It adds the API endpoint but no further behavioral traits. No contradictions.

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?

Single sentence, clear and direct, no redundant information. Every word adds value.

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?

Given the complexity (9 params, no output schema), the description is minimal. It states the purpose but lacks details on return format or behavioral nuances. With high schema coverage and annotations, it is adequate but not rich.

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 descriptions in schema fully document parameters. The tool description adds no extra parameter meaning beyond schema, meeting the baseline.

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?

Description clearly states the verb 'Query', the resource 'usage for a single meter', and the scope 'aggregated usage over a time range'. It differentiates from sibling 'amberflo_get_all_usage' by specifying 'single meter'.

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

Usage Guidelines4/5

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

Description implies when to use: query a single meter; sibling 'amberflo_get_all_usage' is for all meters. It also notes optional grouping/filtering. However, it does not explicitly state when not to use or provide alternatives.

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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TDQS

A3.8/5.0
Disambiguation5/5

Each tool targets a distinct action and resource (e.g., create_customer vs list_customers, get_customer_plan vs list_customer_plan_history). No two tools overlap in purpose; descriptions clearly differentiate them.

Naming Consistency5/5

All tools follow the consistent pattern amberflo_verb_noun with snake_case. Verbs like create, get, list, assign, explain, ingest are used uniformly, and nouns consistently represent the resource (customer, usage, meters, etc.).

Tool Count5/5

14 tools is well-scoped for a billing/metering server, covering customer management, plan assignment, invoices, usage ingestion/querying, and meter discovery. Each tool serves a clear purpose without excess.

Completeness4/5

The tool set covers essential CRUD and lifecycle operations for customers, plans, invoices, and usage. Minor gaps exist (e.g., no update or delete customer, no unassign plan), but the core workflows are fully supported.

Resources