usage_summary
Totals for a meter: event count, total quantity, accrued minor units.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| meter_id | Yes |
Output Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
agent-metering
Schema Changelog
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
- First observed
TDQS
A3.5/5.0
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses the outputs (event count, total quantity, minor units) but omits read-only nature, auth requirements, error handling (e.g., invalid meter_id), and response format beyond the listed fields. Basic transparency is provided but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence of 12 words, extremely concise and front-loaded with the core purpose. While brief, it covers the essential outputs without fluff, earning a high score for efficiency.
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 simple tool with one parameter and an existing output schema, the description lists the three key outputs, providing enough context for an agent to understand what is returned. It lacks edge-case info but is largely complete given the tool's low complexity.
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 0% with only one parameter (meter_id). The description does not explicitly mention the parameter, but the tool name and description imply the meter context. The parameter name is self-explanatory, so the description adds minimal value beyond the schema.
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 returns totals for a meter, specifying three fields: event count, total quantity, accrued minor units. It distinguishes from siblings like list_meters (which lists meters) and record_usage (which records usage), making the purpose specific and unambiguous.
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, nor any prerequisites or when-not-to-use conditions. The description is minimal and does not help an agent decide between this and related tools like usage_timeseries or sla_report.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Try in Browser
Glama MCP Gateway
Add one secure layer between your agents and this server.
TDQS
A3.5/5.0
Disambiguation5/5
Each tool targets a distinct aspect of usage metering: creating meters, recording events, generating reports, flagging synthetic data, closing periods, and verifying chain integrity. No two tools have overlapping purposes.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern in snake_case (e.g., close_period, create_meter, list_events). No deviations or mixed conventions.
Tool Count5/5
With 11 tools, the set is well-scoped for a metering server. It covers creation, recording, listing, reporting, admin flags, period closing, and chain verification without being unnecessarily large.
Completeness4/5
The core lifecycle is covered: create meter, record usage, list events, generate reports, close period. Missing are tools to update/delete meters or retrieve invoices, but these are minor gaps given the immutable design intent.