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amberflo

by io.usefulapi

Explain usage

amberflo_explain_usage
Read-only

Explain/drill into the raw meter events behind a meter's usage over a time range — useful to debug why a number looks off. API: POST /usage/explain.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filterNoDimension filter: map of dimension name -> allowed values.
group_byNoDimension names to group by, e.g. ["customerId"].
take_limitNoReturn only the top N records.
aggregationNoAggregation function: SUM | COUNT | MIN | MAX.
meter_api_nameYesThe meterApiName to explain (from amberflo_list_meters).
end_time_in_secondsNoRange end, unix epoch seconds. Defaults to now if omitted.
start_time_in_secondsYesRange start, unix epoch seconds (inclusive).

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?

The description's 'explain/drill into' implies read-only access, consistent with the readOnlyHint annotation. It adds the API endpoint but no other behavioral details (e.g., pagination, rate limits). With annotations covering safety, this is adequate but not enriched.

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?

Two sentences: one for purpose, one for API endpoint. No redundancy, every word earns its place.

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 tool with 7 parameters and no output schema, the description is minimalist. It doesn't mention return format or how many events are returned. While adequate for a debug tool, it could be more complete.

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 the baseline is 3. The description adds no additional meaning beyond what the input schema already provides for parameters.

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?

The description clearly states the tool explains/drills into raw meter events behind a meter's usage, with a specific use case: debugging discrepancies. It uses strong verbs and distinguishes from sibling tools like get_usage.

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?

It provides guidance on when to use ('useful to debug why a number looks off') but does not explicitly state when not to use or mention alternatives among siblings. The context is clear enough for appropriate selection.

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