root-cause-analysis

A structured debugging method for finding the underlying cause of a bug instead of only treating its visible symptoms.

In plain words
What is it for?
Use it to reproduce bugs, collect logs and other evidence, ask repeated cause-and-effect questions, and investigate crashes or unexpected behavior.
Why use it?
It helps prevent temporary fixes that leave the real problem in place.

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/rohitg00/skillkit/root-cause-analysis
Any agent
npx skills add rohitg00/skillkit --skill root-cause-analysis
Clone the repo
git clone --depth 1 https://github.com/rohitg00/skillkit

Made for: Claude Code, Codex.

Per session 110 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,207 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. 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 $0.00110 $0.01207
Opus 5 $0.00055 $0.00603
Sonnet 5 $0.00022 $0.00241
Haiku 4.5 $0.00011 $0.00121

Measured 2d ago against content hash d7f5da21f957, 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-analysis 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.

packages/core/src/methodology/packs/debugging/root-cause-analysis/SKILL.md · 175 lines

How it starts

The opening of the file, as written. The whole thing — 175 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Root Cause Analysis

You are performing systematic root cause analysis to find the true source of a bug. Do not apply fixes until you understand WHY the bug exists.

Core Principle

Never fix a symptom. Always find and fix the root cause.

The Five Whys Method

Ask "Why?" repeatedly to drill down to the root cause:

  1. Why did the API return an error? → The database query failed
  2. Why did the database query fail? → The connection pool was exhausted
  3. Why was the pool exhausted? → ROOT CAUSE: Missing finally block to close connections

Investigation Phases

Phase 1: Reproduce the Bug

Before investigating:

  1. Reproduce consistently - If you can't reproduce it, you can't verify a fix
  2. Document reproduction steps - Exact sequence of actions
  3. Note environment details - OS, versions, configuration
  4. Identify minimal reproduction - Smallest case that shows the bug

Questions to answer:

  • Does it happen every time or intermittently?
  • Does it happen in all environments?
  • When did it start happening? (recent changes)

Phase 2: Gather Evidence

Collect information before forming theories:

  • Error messages and stack traces
  • Log files (application, system, database)
  • Recent code changes (git log, blame)
  • User reports and reproduction steps
  • Monitoring data (metrics, APM)
  • Related issues (search issue tracker)

Do NOT:

  • Make changes while gathering evidence
  • Assume you know the cause without evidence
  • Ignore related symptoms

Phase 3: Form Hypotheses

Based on evidence, create ranked hypotheses:

Priority Hypothesis Evidence Test Plan
1 Connection leak in UserService Stack trace shows connection pool Add logging, check usage
2 Query timeout too short Occurs under load Test with longer timeout
3 Database server overload Correlates with peak hours Check DB metrics

For each hypothesis:

  • What evidence supports it?
  • What evidence contradicts it?
  • How can we test it?

Read the full file on GitHub · 175 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 · 175 lines · 110 tokens per session scan A d7f5da21f957

Subscribe to this mod's changes

root-cause-analysis is a skill published in the GitHub repository rohitg00/skillkit (1,477 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 110 tokens to every session and 1,207 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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