incident-timeline-creation

Reconstructs incident timelines from server logs, metrics, and chat history.

Updated Dec 29, 2025
One-click install
npx skills add https://github.com/snoodleboot-io/discrecontinual_equations --skill incident-timeline-creation-snoodleboot-io
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: incident-timeline-creation
Source: https://github.com/snoodleboot-io/discrecontinual_equations/tree/main/.claude/skills/incident-timeline-creation
Command: npx skills add https://github.com/snoodleboot-io/discrecontinual_equations --skill incident-timeline-creation-snoodleboot-io

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Post-incident reviews often rely on faulty human memory, producing inaccurate timelines that obscure root causes and delay learning. This Skill reconstructs precise, second-level incident timelines by correlating server logs, metrics dashboards, and chat history into a single authoritative record. ## Core Features & Use Cases - Multi-Source Correlation: Merges server logs, metrics (CPU, latency, error rates), and chat messages into one chronological timeline with source attribution. - Critical Metrics Calculation: Computes detection lag, response lag, remediation time, customer impact duration, and total incident duration. - Contributing Factor Analysis: Identifies systemic weaknesses such as missing query timeouts, absent connection pool monitoring, or lack of circuit breakers. - Use Case: After a database outage, feed the on-call engineer's logs, monitoring alerts, and Slack history into this Skill to produce a markdown timeline table with root cause, detection, mitigation, and recovery events for the postmortem document. ## Quick Start Create an incident timeline from these server logs, metrics snapshots, and chat history, including detection lag and remediation time calculations.

Frequently Asked Questions about incident-timeline-creation

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I create an incident timeline for a postmortem?▼

Gather server logs, metrics dashboards, and chat history, then order events chronologically using logs as the source of truth. Tag each event with its type (root cause, detection, mitigation, recovery) and source, then calculate detection lag, response lag, and remediation time.

What data sources should I use for incident timeline reconstruction?▼

Use server logs as the primary source of truth since they are accurate to the second. Supplement with metrics dashboards for alert and error-rate timing, and chat history for human actions like acknowledgments and mitigation steps.

How do I calculate detection lag and response lag?▼

Detection lag is the time between the root cause event and the first alert firing. Response lag is the time between the alert and the first human acknowledgment. Both are derived by subtracting timestamps from logs, monitoring, and chat records.

Why are incident timelines based on memory inaccurate?▼

Participant memory is typically off by plus or minus ten minutes and misses system-level events. Server logs and metrics provide second-level accuracy, so timelines should always be sourced from machine records rather than recollection.

What are common mistakes when building incident timelines?▼

Common mistakes include mixing time zones, starting from the alert instead of the actual root cause, and recording only human actions while ignoring metric changes and system errors. Convert all timestamps to UTC and include both system and human events.