Skill Detail

Investigate production issues from Slack with runbooks and monitoring MCPs using DIY AI Debugging Agent Toolkit

Handle alerts and debugging questions from Slack, query connected monitoring MCP servers, and follow runbook-guided investigation steps for live incidents.

Runbooks & DiagnosticsMCP
Runbooks & Diagnostics MCP Security Reviewed
โญ 6 GitHub stars
INSTALL WITH ANY AGENT
npx skills add agentskillexchange/skills --skill investigate-production-issues-from-slack-with-runbooks-and-monitoring-mcps-using-diy-ai-debugging-agent-toolkit Copy
Works best when you want a reusable capability, not another fragile one-off prompt.
At a glance
Tools required
Slack app, MCP server connections for monitoring tools, Python runtime, OpenAI key, optional runbooks or prompts for incident workflows
Install & setup
pip install uv && uv sync && uv run python app.py
Author
DrDroidLab
Publisher
Open Source Project
Last updated
Apr 23, 2026
Quick brief

Use DIY AI Debugging Agent Toolkit when an agent needs to respond in Slack, inspect monitoring systems through MCP servers, and follow runbook-guided steps during production debugging. The upstream repository is concrete about the workflow: receive alerts or questions in Slack, consult configured monitoring MCP servers, apply prompts or runbooks, and respond with investigative findings.

How it works

What this skill actually does

Invoke this instead of using Slack, dashboards, or a raw MCP connection normally when the immediate job is incident debugging with chat-driven triage. The scope boundary is specific enough to be skill-shaped: this is a Slack-anchored production-debugging workflow that consults monitoring MCP tools and runbooks, not a generic observability platform or broad agent framework listing.