Safety Engineering Foundations

SkillAI & models

Lets your agent analyze system hazards and unsafe interactions using STPA, deriving safety constraints and traceability worksheets.

Available today. Use it from your connected AI after setup.

Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

Then ask your AI: use the Safety Engineering Foundations skill

About this skill

Analyze system hazards and unsafe interactions. Use when assessing STPA, unsafe control actions, safety constraints, loss scenarios, or assurance traceability.

What this skill tells your AI

The instructions your AI receives, as published by vasilyu1983/ai-agents-public in frameworks/shared-skills/skills/foundations-safety-engineering/SKILL.md and read by ahel’s review.

Derive constraints that prevent unacceptable losses, including losses from interactions between functioning components. Scope the analysis to the requested system and decision; analysis does not authorize external actions.

When to use

Use when a task requests hazard analysis, STPA, unsafe control actions, system safety constraints, or an evidence argument connecting controls to prevention of specified losses.

For failure rates, repair/availability models, FMEA, and fault-tree probabilities, use reliability theory. For proving specified model properties, use formal methods. Operational incident response and security hardening remain with their existing owners.

Quick Reference

Hazard analysis → STPA reference; completion claims → assurance reference; deliverable → traceability worksheet.

Workflow

  1. Define system boundary, stakeholders, lifecycle phase, unacceptable losses, and environmental assumptions. Separate an accident/loss from a hazardous system state.
  2. Model controllers, controlled processes, control actions, feedback, and process-model assumptions. Include humans and interacting controllers when relevant.
  3. Read STPA analysis and examine each action in four categories: omission, unsafe provision, timing/order, and inappropriate duration where applicable.
  4. For each unsafe control action (UCA), identify context and hazard; derive a testable constraint and assign an owner. Explore stale/missing feedback, flawed process models, conflicting commands, and unsafe execution paths, including functioning components.
  5. Fill the traceability worksheet. Read assurance and boundaries before making completion or safety claims. Use the synthetic example as an illustration, not a risk estimate.

Completion criteria

Every analyzed UCA links to a hazard and loss, a constraint, and planned or observed verification. Record excluded scenarios, unknowns, residual hazards, owners, and review triggers. A scenario with no test evidence remains a proposed mitigation.

Do not equate uptime with safety, assign fabricated event probabilities, or describe an STPA diagram as proof. This skill provides analysis and assurance structure; it does not certify compliance, establish acceptable risk, or grant approval authority. Respect authorization already supplied and identify any specific additional action requiring authorization without creating universal approval loops.

Fact-Checking

Use the dated primary source for method claims and system-specific evidence for effectiveness claims. Keep synthetic scenarios separate from observed incidents. Verify later method or system changes before describing them as current.

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GitHub stars
88
Forks
19
Last commit
Sep 2026
Advanced
Catalog kind
skill
Key
foundations-safety-engineering
Source
github.com/vasilyu1983/ai-agents-public