Incident Retrospective

A postmortem (also called incident review or retrospective) is a structured process for analyzing incidents to understand what happened, why it happened, and how to prevent similar incidents in future

16 stars

Best use case

Incident Retrospective is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

A postmortem (also called incident review or retrospective) is a structured process for analyzing incidents to understand what happened, why it happened, and how to prevent similar incidents in future

Teams using Incident Retrospective should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/incident-retrospective/SKILL.md --create-dirs "https://raw.githubusercontent.com/diegosouzapw/awesome-omni-skill/main/skills/backend/incident-retrospective/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/incident-retrospective/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How Incident Retrospective Compares

Feature / AgentIncident RetrospectiveStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

A postmortem (also called incident review or retrospective) is a structured process for analyzing incidents to understand what happened, why it happened, and how to prevent similar incidents in future

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Incident Retrospective

## Skill Profile
*(Select at least one profile to enable specific modules)*
- [ ] **DevOps**
- [x] **Backend**
- [ ] **Frontend**
- [ ] **AI-RAG**
- [ ] **Security Critical**

## Overview
A postmortem (also called incident review or retrospective) is a structured process for analyzing incidents to understand what happened, why it happened, and how to prevent similar incidents in future. The goal is learning, not blaming.

**Core Principle**: "Blame system, not person. Every incident is an opportunity to learn and improve."

## Why This Matters
- **Psychological Safety**: Engineers feel safe reporting issues
- **Honest Analysis**: Root causes are identified without blame
- **Organizational Learning**: Knowledge is shared and documented
- **System Improvement**: Action items prevent recurrence
- **Cultural Shift**: Failures become learning opportunities
- **Reduced MTTR**: Better response procedures over time

---

## Core Concepts & Rules

### 1. Core Principles
- Follow established patterns and conventions
- Maintain consistency across codebase
- Document decisions and trade-offs

### 2. Implementation Guidelines
- Start with the simplest viable solution
- Iterate based on feedback and requirements
- Test thoroughly before deployment


## Inputs / Outputs / Contracts
* **Inputs**:
  - Incident timeline and logs
  - Monitoring data and metrics
  - System architecture and configuration
* **Entry Conditions**:
  - Incident is resolved and stable
  - Root cause investigation is complete
  - Team has time allocated for analysis
* **Outputs**:
  - Postmortem document with findings
  - Action items with owners and deadlines
  - Updated runbooks and documentation
* **Artifacts Required (Deliverables)**:
  - Postmortem template library
  - Incident analysis report
  - Action item tracking
* **Acceptance Evidence**:
  - Completed postmortem with all sections filled
  - Action items assigned to owners
  - Stakeholder review completed
  - Documentation updated
* **Success Criteria**:
  - Root cause identified (Five Whys completed)
  - Action items created with owners and due dates
  - Postmortem reviewed and approved
  - Learnings shared with team

## Skill Composition
* **Depends on**: Failure Modes Analysis, Incident Triage
* **Compatible with**: Communication Templates, Escalation and Ownership
* **Conflicts with**: Systems without time for learning
* **Related Skills**: 
  - [40-system-resilience/failure-modes](40-system-resilience/failure-modes/SKILL.md) - Understanding what to analyze
  - [41-incident-management/communication-templates](41-incident-management/communication-templates/SKILL.md) - Communication during incidents
  - [41-incident-management/escalation-and-ownership](41-incident-management/escalation-and-ownership/SKILL.md) - Ownership during incidents

---

## Quick Start / Implementation Example

1. Review requirements and constraints
2. Set up development environment
3. Implement core functionality following patterns
4. Write tests for critical paths
5. Run tests and fix issues
6. Document any deviations or decisions

```python
# Example implementation following best practices
def example_function():
    # Your implementation here
    pass
```


## Assumptions / Constraints / Non-goals

* **Assumptions**:
  - Development environment is properly configured
  - Required dependencies are available
  - Team has basic understanding of domain
* **Constraints**:
  - Must follow existing codebase conventions
  - Time and resource limitations
  - Compatibility requirements
* **Non-goals**:
  - This skill does not cover edge cases outside scope
  - Not a replacement for formal training


## Compatibility & Prerequisites

* **Supported Versions**:
  - Python 3.8+
  - Node.js 16+
  - Modern browsers (Chrome, Firefox, Safari, Edge)
* **Required AI Tools**:
  - Code editor (VS Code recommended)
  - Testing framework appropriate for language
  - Version control (Git)
* **Dependencies**:
  - Language-specific package manager
  - Build tools
  - Testing libraries
* **Environment Setup**:
  - `.env.example` keys: `API_KEY`, `DATABASE_URL` (no values)


## Test Scenario Matrix (QA Strategy)

| Type | Focus Area | Required Scenarios / Mocks |
| :--- | :--- | :--- |
| **Unit** | Core Logic | Must cover primary logic and at least 3 edge/error cases. Target minimum 80% coverage |
| **Integration** | DB / API | All external API calls or database connections must be mocked during unit tests |
| **E2E** | User Journey | Critical user flows to test |
| **Performance** | Latency / Load | Benchmark requirements |
| **Security** | Vuln / Auth | SAST/DAST or dependency audit |
| **Frontend** | UX / A11y | Accessibility checklist (WCAG), Performance Budget (Lighthouse score) |


## Technical Guardrails & Security Threat Model

### 1. Security & Privacy (Threat Model)
* **Top Threats**: Injection attacks, authentication bypass, data exposure
- [ ] **Data Handling**: Sanitize all user inputs to prevent Injection attacks. Never log raw PII
- [ ] **Secrets Management**: No hardcoded API keys. Use Env Vars/Secrets Manager
- [ ] **Authorization**: Validate user permissions before state changes

### 2. Performance & Resources
- [ ] **Execution Efficiency**: Consider time complexity for algorithms
- [ ] **Memory Management**: Use streams/pagination for large data
- [ ] **Resource Cleanup**: Close DB connections/file handlers in finally blocks

### 3. Architecture & Scalability
- [ ] **Design Pattern**: Follow SOLID principles, use Dependency Injection
- [ ] **Modularity**: Decouple logic from UI/Frameworks

### 4. Observability & Reliability
- [ ] **Logging Standards**: Structured JSON, include trace IDs `request_id`
- [ ] **Metrics**: Track `error_rate`, `latency`, `queue_depth`
- [ ] **Error Handling**: Standardized error codes, no bare except
- [ ] **Observability Artifacts**:
    - **Log Fields**: timestamp, level, message, request_id
    - **Metrics**: request_count, error_count, response_time
    - **Dashboards/Alerts**: High Error Rate > 5%


## Agent Directives & Error Recovery
*(ข้อกำหนดสำหรับ AI Agent ในการคิดและแก้ปัญหาเมื่อเกิดข้อผิดพลาด)*

- **Thinking Process**: Analyze root cause before fixing. Do not brute-force.
- **Fallback Strategy**: Stop after 3 failed test attempts. Output root cause and ask for human intervention/clarification.
- **Self-Review**: Check against Guardrails & Anti-patterns before finalizing.
- **Output Constraints**: Output ONLY the modified code block. Do not explain unless asked.


## Definition of Done (DoD) Checklist

- [ ] Tests passed + coverage met
- [ ] Lint/Typecheck passed
- [ ] Logging/Metrics/Trace implemented
- [ ] Security checks passed
- [ ] Documentation/Changelog updated
- [ ] Accessibility/Performance requirements met (if frontend)


## Anti-patterns / Pitfalls

* ⛔ **Don't**: Log PII, catch-all exception, N+1 queries
* ⚠️ **Watch out for**: Common symptoms and quick fixes
* 💡 **Instead**: Use proper error handling, pagination, and logging


## Reference Links & Examples

* Internal documentation and examples
* Official documentation and best practices
* Community resources and discussions


## Versioning & Changelog

* **Version**: 1.0.0
* **Changelog**:
  - 2026-02-22: Initial version with complete template structure

Related Skills

Incident Response

16
from diegosouzapw/awesome-omni-skill

Incident response is a systematic approach to handling security breaches and incidents to minimize damage, reduce recovery time, and prevent future occurrences. Effective incident response includes pr

agent-ops-retrospective

16
from diegosouzapw/awesome-omni-skill

Scan the current chat session for durable learnings (clarifications, corrections, decisions, pitfalls) and update .agent/memory.md. Use after critical review and before concluding work.

bgo

10
from diegosouzapw/awesome-omni-skill

Automates the complete Blender build-go workflow, from building and packaging your extension/add-on to removing old versions, installing, enabling, and launching Blender for quick testing and iteration.

Coding & Development

mcp-create-declarative-agent

16
from diegosouzapw/awesome-omni-skill

Skill converted from mcp-create-declarative-agent.prompt.md

MCP Architecture Expert

16
from diegosouzapw/awesome-omni-skill

Design and implement Model Context Protocol servers for standardized AI-to-data integration with resources, tools, prompts, and security best practices

mathem-shopping

16
from diegosouzapw/awesome-omni-skill

Automatiserar att logga in på Mathem.se, söka och lägga till varor från en lista eller recept, hantera ersättningar enligt policy och reservera leveranstid, men lämnar varukorgen redo för manuell checkout.

math-modeling

16
from diegosouzapw/awesome-omni-skill

本技能应在用户要求"数学建模"、"建模比赛"、"数模论文"、"数学建模竞赛"、"建模分析"、"建模求解"或提及数学建模相关任务时使用。适用于全国大学生数学建模竞赛(CUMCM)、美国大学生数学建模竞赛(MCM/ICM)等各类数学建模比赛。

matchms

16
from diegosouzapw/awesome-omni-skill

Mass spectrometry analysis. Process mzML/MGF/MSP, spectral similarity (cosine, modified cosine), metadata harmonization, compound ID, for metabolomics and MS data processing.

managing-traefik

16
from diegosouzapw/awesome-omni-skill

Manages Traefik reverse proxy for local development. Use when routing domains to local services, configuring CORS, checking service health, or debugging connectivity issues.

managing-skills

16
from diegosouzapw/awesome-omni-skill

Install, find, update, and manage agent skills. Use when the user wants to add a new skill, search for skills that do something, check if skills are up to date, or update existing skills. Triggers on: install skill, add skill, get skill, find skill, search skill, update skill, check skills, list skills.

manage-agents

16
from diegosouzapw/awesome-omni-skill

Create, modify, and manage Claude Code subagents with specialized expertise. Use when you need to "work with agents", "create an agent", "modify an agent", "set up a specialist", "I need an agent for [task]", or "agent to handle [domain]". Covers agent file format, YAML frontmatter, system prompts, tool restrictions, MCP integration, model selection, and testing.

maintainx-automation

16
from diegosouzapw/awesome-omni-skill

Automate Maintainx tasks via Rube MCP (Composio). Always search tools first for current schemas.