Risk assessment

Skill vignesh2027/AI-AGENT-SKILLS/skills/risk-assessment

Turn your ai agent into senior engineer..The result is fast code that fails slowly. AI Agent Skills solves this by giving agents the same disciplined workflows senior engineers use

Install

npx -y skills add vignesh2027/AI-AGENT-SKILLS --skill risk-assessment

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Identify and mitigate technical and delivery risk before it becomes an incident

SKILL.md

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Overview

Risk not identified is risk not managed. This skill makes technical and delivery risk explicit so it can be mitigated, accepted, or escalated — before it surprises you.

When to Use

Before estimating a project
Before starting a large migration or refactor
Before a major deployment
When a project has been "almost done" for two weeks

Process

Step 1: List all risks

Brainstorm: what could go wrong? Include: technical unknowns, external dependencies, team knowledge gaps, deadline pressure, infrastructure, security, data integrity.

Step 2: Score each risk

For each risk: Likelihood (1–3) × Impact (1–3) = Risk Score (1–9). Prioritize scores ≥ 6.

Step 3: Classify risks

Known known: You know about it and understand it. Mitigate.
Known unknown: You know there's something you don't know. Research it.
Unknown unknown: You don't know what you don't know. Add buffer and run pre-mortems.

Step 4: Design mitigations

For each high-score risk: what is the mitigation? What is the fallback? Who owns it?

Step 5: Pre-mortem

Imagine it's 3 months from now and the project failed. What went wrong? Work backwards. This surfaces unknown unknowns.

Step 6: Define go/no-go criteria

For the deployment or launch: what conditions must be true to proceed? What conditions force a delay?

Verification Requirements

All risks identified and scored
High-score risks have documented mitigations
Pre-mortem conducted
Go/no-go criteria defined
Risk log tracked throughout the project