Agent skill · AI & Agents

rca-systems-theoretic

Systems-theoretic approaches to root cause analysis for complex socio-technical systems where linear causal chains fail. Covers Nancy Leveson's STAMP (Systems-Theoretic Accident Model and Process), STPA (System-Theoretic Process Analysis) for hazard analysis, CAST (Causal Analysis based on STAMP) for post-incident investigation, Rasmussen's risk-management framework and dynamic safety model, Hollnagel's FRAM (Functional Resonance Analysis Method), and AcciMap. Use when investigating incidents in healthcare, aviation, nuclear, autonomous systems, distributed microservices, or any system where m

majiayu000github.com/majiayu000GitHub ↗
claude-codeMIT
Install
npx skills add majiayu000/claude-skill-registry --skill rca-systems-theoretic --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 16 KB
Bundled scripts: none
Path: skills/analysis/rca-systems-theoretic/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Systems-Theoretic RCA Classical RCA asks "what component failed?" Systems-theoretic RCA asks "what *control* failed?" The difference is not cosmetic. An incident where no component is individually broken — every actor behaved plausibly, every tool worked as specified — is incomprehensible to classical techniques but natural to systems-theoretic ones. This skill teaches you to treat incidents as control-structure failures rather than component failures, and to use STAMP-family techniques to find the actual design flaws. ## The paradigm shift | Classical RCA | Systems-theoretic RCA | |---|---| | Incidents are caused by component failures | Incidents are caused by inadequate constraints on system behavior | | Find the broken part | Find the broken *control loop* | | Human error is a root cause | Human error is a *symptom* of a control failure upstream | | Linear causal chains | Feedback loops and emergent behavior | | "Blame the operator" outcome | "Redesign the feedback mechanism" outcome | The shift originates in Nancy Leveson's *Engineering a Safer World* (MIT Press, 2011) and her decades of work investigating Challenger, Columbia, Therac-25, and other complex-system accidents. #

What's inside
Steps it walks through
  1. The paradigm shift
  2. Framework 1 — STAMP: Systems-Theoretic Accident Model and Process
  3. The core claim
  4. The STAMP model components
  5. The four types of unsafe control action
  6. Leveson's ten STAMP principles (from Engineering a Safer World)
  7. Framework 2 — STPA: System-Theoretic Process Analysis
  8. Step 1 — Define the purpose of the analysis
  9. Step 2 — Model the control structure
  10. Step 3 — Identify unsafe control actions (UCAs)
  11. Step 4 — Identify loss scenarios
  12. Empirical evidence for STPA
  13. Framework 3 — CAST: Causal Analysis based on STAMP
  14. CAST process
Ships with 1 file
  • metadata.json
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About this skill
What does the rca-systems-theoretic skill do?

Systems-theoretic approaches to root cause analysis for complex socio-technical systems where linear causal chains fail. Covers Nancy Leveson's STAMP (Systems-Theoretic Accident Model and Process), STPA (System-Theoretic Process Analysis) for hazard analysis, CAST (Causal Analysis based on STAMP) for post-incident investigation, Rasmussen's risk-management framework and dynamic safety model, Hollnagel's FRAM (Functional Resonance Analysis Method), and AcciMap. Use when investigating incidents in healthcare, aviation, nuclear, autonomous systems, distributed microservices, or any system where m

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill rca-systems-theoretic --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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