RootCauseAnalysis

A structured way to investigate why an incident or failure happened, including contributing conditions and deeper system problems.

In plain words
What is it for?
Use it for root-cause analysis, Five Whys, fishbone diagrams, blameless postmortems, fault-tree analysis, and failure-risk reviews.
Why use it?
It helps teams look beyond the immediate mistake and learn from failures without blaming individuals.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/danielmiessler/lifeos/rootcauseanalysis
Any agent
npx skills add danielmiessler/LifeOS --skill rootcauseanalysis
Clone the repo
git clone --depth 1 https://github.com/danielmiessler/LifeOS

Made for: Claude Code, Codex.

Per session 93 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,621 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00093 $0.02621
Opus 5 $0.00046 $0.01311
Sonnet 5 $0.00019 $0.00524
Haiku 4.5 $0.00009 $0.00262

Measured yesterday against content hash 0c46f478db84, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

RootCauseAnalysis scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

curl -s -X POST http://localhost:31337/notify \
LifeOS/install/skills/RootCauseAnalysis/SKILL.md · 178 lines

How it starts

The opening of the file, as written. The whole thing — 178 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Customization

Before executing, check for user customizations at: ~/.claude/LIFEOS/USER/CUSTOMIZATIONS/SKILLS/RootCauseAnalysis/

If this directory exists, load and apply any PREFERENCES.md, configurations, or resources found there. These override default behavior. If the directory does not exist, proceed with skill defaults.

MANDATORY: Voice Notification (REQUIRED BEFORE ANY ACTION)

You MUST send this notification BEFORE doing anything else when this skill is invoked.

  1. Send voice notification:

    curl -s -X POST http://localhost:31337/notify \
      -H "Content-Type: application/json" \
      -d '{"message": "Running the WORKFLOWNAME workflow in the RootCauseAnalysis skill to ACTION"}' \
      > /dev/null 2>&1 &
    
  2. Output text notification:

    Running the **WorkflowName** workflow in the **RootCauseAnalysis** skill to ACTION...
    

This is not optional. Execute this curl command immediately upon skill invocation.


RootCauseAnalysis Skill

What It Does

Investigates why something failed — past the proximate cause, down to the contributing factors and latent conditions that actually made the failure possible. It offers five structured methods (5 Whys, Fishbone, Postmortem, Fault Tree, Kepner-Tregoe) and ends with actionable changes that prevent a whole class of failure, not just the one incident. Grounded in Toyota Production System, Ishikawa, Reason's Swiss Cheese model, Gano's Apollo method, and Google SRE / Etsy blameless culture.

How It Works

The goal is not "the" root cause — that framing is almost always wrong. A good RCA ends with 3+ actionable, systemic contributing factors, named blamelessly, that prevent a class of failure — not a single blame target. Everything below is structure that pushes the analysis past the first plausible answer, past blame, and stops only at causes you can actually change.

Core Concept

Five axioms this skill operates on:

  1. Proximate cause ≠ root cause. "The deploy failed because X crashed" is usually where real analysis starts, not where it ends.
  2. There is rarely one cause. Incidents typically have multiple contributing factors — active failures (what a human did) and latent conditions (what the system allowed). James Reason's Swiss Cheese model.
  3. Humans are not root causes. "Operator error" is a stop sign for analysis, not a conclusion. If a human could make the mistake, the system allowed it. Go deeper.
  4. Actionability is the stop condition. A cause is "root enough" when it points to a change you can actually make. Go too shallow and you miss the fix; go too deep ("physics") and you can't act on it.
  5. RCA is a bias-fight. Hindsight bias, confirmation bias, single-cause bias, and outcome bias all actively corrupt investigations. Structure exists to resist them.

Read the full file on GitHub · 178 lines

Files

What ships with it

7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 178 lines · 93 tokens per session scan A 0c46f478db84

Subscribe to this mod's changes

RootCauseAnalysis is a skill published in the GitHub repository danielmiessler/LifeOS (18,798 stars, last pushed 17d ago), licensed MIT. It adds 93 tokens to every session and 2,621 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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