root-cause-analyzer

A guided method for finding the underlying cause of a recurring or complex problem by asking “why” several times.

In plain words
What is it for?
Use it to investigate errors and recurring issues, check for similar cases in the knowledge base, document findings, and update internal solution records.
Why use it?
It helps distinguish the real source of a failure from its visible symptoms and records the resulting lessons for future use.

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/davidmatousek/agentic-oriented-development-kit/root-cause-analyzer
Any agent
npx skills add davidmatousek/agentic-oriented-development-kit --skill root-cause-analyzer
Clone the repo
git clone --depth 1 https://github.com/davidmatousek/agentic-oriented-development-kit

Made for: Claude Code, Codex.

Per session 68 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,776 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 100% copy Near-identical to another mod 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 $0.00068 $0.02776
Opus 5 $0.00034 $0.01388
Sonnet 5 $0.00014 $0.00555
Haiku 4.5 $0.00007 $0.00278

Measured 2d ago against content hash b8614825c578, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

root-cause-analyzer scanned grade A with 0 findings 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 2d ago.

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.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

100% identical to root-cause-analyzer — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.claude/skills/root-cause-analyzer/SKILL.md · 409 lines

How it starts

The opening of the file, as written. The whole thing — 409 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Root Cause Analyzer Skill

Purpose

Systematically identifies root causes of complex problems using the 5 Whys methodology from docs/5-WHYS-METHODOLOGY.md. Documents findings in docs/development-learnings/ and updates Knowledge Base (docs/kb/) using make kb-pattern. Implements FR-009 from the feature specification.

Knowledge Base Integration

IMPORTANT: Before starting root cause analysis, check the Knowledge Base for existing patterns.

Pre-Analysis KB Check

from scripts.kb.search import kb_search, kb_get_pattern

# Search for similar issues
results = kb_search(
    query="[error message or symptom]",
    category="[ARCH/DB/API/TEST/etc]",
    min_quality_score=60,
    limit=5
)

if results:
    print(f"Found {len(results)} existing patterns!")
    # Review top pattern
    pattern = kb_get_pattern(results[0].id)
    if pattern:
        # Apply existing solution instead of re-analyzing
        print("Applying existing root cause analysis from KB")
else:
    print("No existing patterns found. Proceeding with new 5 Whys analysis")

When to Check KB

  1. Before starting 5 Whys: Search for error messages, symptoms, or similar problems
  2. During analysis: Browse relevant categories (ARCH, DB, API, TEST, ERROR) for design patterns
  3. After finding root cause: Search again to see if this is a known systemic issue
  4. Before documenting: Check if similar pattern exists to avoid duplication

What to Search For

  • Exact error messages: Copy error text into search query
  • Symptom keywords: "timeout", "connection pool", "race condition", etc.
  • Technology + problem: "postgresql connection pool exhausted"
  • Pattern category: Use category filter to narrow results

If Pattern Found

  1. Review the existing pattern's 5 Whys analysis
  2. Check if root cause matches current issue
  3. Apply existing solution if applicable
  4. Update pattern usage count if applied
  5. Add cross-reference in your documentation

If No Pattern Found

Read the full file on GitHub · 409 lines

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. 2d ago First seen · 409 lines · 68 tokens per session scan A b8614825c578

Subscribe to this mod's changes

root-cause-analyzer is a skill published in the GitHub repository davidmatousek/agentic-oriented-development-kit (22 stars, last pushed 2mo ago), licensed MIT. It adds 68 tokens to every session and 2,776 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to root-cause-analyzer, differing in 0 lines, and is treated as a copy.

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