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prenzio

Rudow MCP Server

by prenzio

metrics_routes

Retrieve top routes by request volume and error count for a project to identify high-traffic endpoints and failing hot spots.

Instructions

Top routes by request volume and error count. Shows which endpoints are getting the most traffic and which are failing most often. Use this to identify hot spots and problem areas.

Input Schema

NameRequiredDescriptionDefault
minutesNoWindow size in minutes (default 60).
project_idYesThe project to query. Call list_projects first to see which ids you can use.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden and does not meet it. It never states how many routes are returned, how the ranking is sorted or bounded, that the operation is read-only, or how errors are counted (rate vs absolute). The default 60-minute window is left entirely to the schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The ranking criterion is front-loaded, which is good, but the second sentence ("Shows which endpoints are getting the most traffic and which are failing most often") is a near-restatement of the first and does not earn its place. Three short sentences with one redundant.

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

Completeness2/5

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

With no annotations and no output schema, an agent learns nothing about return shape: top-N cardinality, ordering, whether counts are per-route only or broken down, or the time window semantics. For a metrics tool with zero structured behavioral coverage, the description is thinner than it needs to be.

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 description coverage is 100%, with both the window minutes and project_id already documented in the schema, including the pointer to list_projects. The description adds no parameter meaning beyond that, so baseline 3 applies.

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

Purpose4/5

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

The description names a specific resource and ranking criterion: top routes by request volume and error count. An agent knows exactly what data this returns. However, it never distinguishes itself from close siblings like route_drilldown, metrics_overview, or metrics_trends, so the agent must guess which route-related tool to pick.

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?

"Use this to identify hot spots and problem areas" gives implied usage but no explicit when-to-use versus alternatives. With route_drilldown, metrics_trends, and metrics_summary all available, the agent gets no routing logic — for instance, whether to come here first for an overview before drilling into one route.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.