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prenzio

Rudow MCP Server

by prenzio

route_drilldown

Inspect a specific route’s request count, error rate, average and p95 latency, and errors by status code to diagnose issues found in route metrics.

Instructions

Deep dive into a specific route: request count, error rate, average and p95 latency, errors by status code. Call this after seeing a problematic route in metrics_routes to get details.

Input Schema

NameRequiredDescriptionDefault
routeYesThe route path to drill down into, e.g. '/api/v1/chat'.
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

A4.4/5.0
Behavior4/5

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

No annotations exist, so the description carries the disclosure burden; it does so by listing exactly what the call returns (counts, error rate, latency percentiles, status-code breakdown) in lieu of an output schema. It stops short of stating behavior for unknown routes, empty windows, or whether the aggregate is read-only/cached, but the return-content disclosure is solid for a query tool.

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, front-loaded with the return payload then the routing instruction; every clause earns its place with no filler.

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?

Covers purpose, workflow, and output contents despite having no output schema or annotations. The only gap is unspecified edge-case behavior (missing route, zero-traffic window), which is minor for a read-only metrics query.

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%, so route, minutes, and project_id are already documented, including the default window and the hint to call list_projects. The description adds no parameter detail beyond what the schema provides, so the baseline 3 applies.

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?

States a specific verb ("Deep dive") and resource (a specific route) and enumerates the exact metrics returned: request count, error rate, average/p95 latency, errors by status code. It explicitly contrasts with the sibling metrics_routes, so an agent can distinguish the two without opening either schema.

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 says "Call this after seeing a problematic route in metrics_routes to get details," naming the alternative tool and the condition that selects it. The workflow relationship (overview first, drilldown second) is unambiguous.

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