Skip to main content
Glama
kowshik3383

Production Monitoring MCP

by kowshik3383

explain_incident

Triage production incidents by generating an executive briefing with root cause, evidence chain, confidence, and recommended action.

Instructions

Generates a human-readable executive briefing of an incident with root cause, evidence chain, confidence, and recommended action.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
repoNoGitHub repo name
ownerNoGitHub owner or organization
timeframeNoTimeframe to evaluate e.g. '24h', '2d'
deployment_idNoSpecific deployment ID to triage
service_or_projectYesProject name / Sentry project / Vercel project

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.4/5.0
Behavior3/5

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. It usefully discloses the shape of the result (root cause, evidence chain, confidence, recommended action), implying a read-only synthesis, but it never states whether anything is mutated, what permissions/scope the repo/owner/timeframe inputs require, or that this is likely a slower, more expensive generation call.

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?

A single front-loaded sentence that names the action, the deliverable, and its four components with zero filler. Nothing could be trimmed without losing content.

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?

With no output schema, the description adequately compensates by enumerating what the briefing contains, and the input schema fully documents all five parameters. The remaining gaps are usage routing and behavioral cost/latency details, which keep it short of a 5.

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 all five parameters (repo, owner, timeframe, deployment_id, service_or_project) are already documented in the schema. The description adds nothing about how these inputs are combined or which combinations scope the analysis, 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?

States a specific verb (generates) and resource (human-readable executive briefing of an incident), and enumerates the briefing's contents: root cause, evidence chain, confidence, recommended action. An agent can tell it is a synthesis/explanation tool rather than a raw data fetcher, but it never names or contrasts the closest sibling, correlate_incident.

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?

There is no explicit when-to-use, when-not-to-use, or alternative routing. An agent must infer from the sibling list that this is the right choice over get_error_details or correlate_incident when a narrative briefing is wanted, which is left entirely unstated.

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