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metrxbots

Metrx MCP Server

by metrxbots

Get Cost Summary

metrx_get_cost_summary
Read-onlyIdempotent

Retrieve a comprehensive cost summary for your AI agent fleet, including total spend, call counts, error rates, agent breakdown, and optimization opportunities. Start here to understand agent economics.

Instructions

Get a comprehensive cost summary for your AI agent fleet. Returns total spend, call counts, error rates, agent breakdown, revenue attribution (if available), and optimization opportunities. Use this as the starting point for understanding your agent economics. Do NOT use for real-time per-request cost checking — use OpenTelemetry spans for that.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
period_daysNoNumber of days to include in the summary (default: 30)
Behavior4/5

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

Annotations already indicate readOnlyHint=true, destructiveHint=false, idempotentHint=true. Description adds value by listing returned fields (total spend, call counts, etc.), but doesn't mention response format or pagination. No contradiction with annotations.

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, no fluff. Purpose and usage guidance are front-loaded. Every sentence earns its place.

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?

Return fields are listed, usage context provided, and tool differentiated from sibling. However, no output schema exists, and the description doesn't specify whether data is cached or real-time, leaving minor gaps.

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 has 100% coverage for the single parameter 'period_days' with its description. The tool description does not add any additional meaning or nuance to the parameter, so baseline 3 is appropriate.

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 'Get a comprehensive cost summary for your AI agent fleet' – specific verb and resource. Distinguishes from sibling tools by referencing real-time per-request cost checking as a separate use case.

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

Usage Guidelines5/5

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

Explicitly tells when to use ('starting point for understanding agent economics') and when not to use ('Do NOT use for real-time per-request cost checking'), and provides alternative ('use OpenTelemetry spans').

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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