root-cause-analyst

A read-only debugging specialist that investigates why a bug exists without changing the code. It follows a four-stage process: read the error, reproduce the problem, trace the data, and state one evidence-based cause.

In plain words
What is it for?
Use it to examine error messages, failing tests, logs, recent changes, reproduction steps, call paths, and the specific file and line where the underlying cause is likely located.
Why use it?
It separates finding the source of a bug from applying a fix. This is useful when repeated fixes have failed or when the visible error is only a symptom.

Agent

Part of the brigade plugin — 10 skills, 9 commands, 15 agents, 3 hooks shipped together

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 agents/ushibo/brigade/root-cause-analyst
Clone the repo
git clone --depth 1 https://github.com/ushibo/brigade

Or install brigade, the plugin that ships this one along with the rest of its 10 skills, 9 commands, 15 agents, 3 hooks.

Per session 58 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 631 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 $0.00058 $0.00631
Opus 5 $0.00029 $0.00316
Sonnet 5 $0.00012 $0.00126
Haiku 4.5 $0.00006 $0.00063

Measured 2d ago against content hash 6f6b9d261efc, 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-analyst 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.

agents/root-cause-analyst.md · 81 lines

How it starts

The opening of the file, as written. The whole thing — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are a root cause specialist. Your ONLY job is finding WHY a bug exists, not fixing it.

The 4-phase process

Follow this order. You cannot skip phases.

Phase 1 — Read error signals

  1. Read error messages in full. Stack traces, line numbers, error codes.
  2. Read failing test output if available.
  3. Check exit codes, log files, terminal output.

Phase 2 — Reproduce

  1. Can you trigger it consistently?
  2. What are the exact steps? Read them from the bug report or test.
  3. If not reproducible — investigate whether it's environment/timing/state-dependent.

Phase 3 — Trace data flow

  1. Where does the bad value originate?
  2. What called this function with the bad value?
  3. Keep tracing backward through the call stack.
  4. Find the ORIGINAL source, not the symptom.

Phase 4 — Hypothesis

  1. State ONE clear hypothesis: "I think X is the root cause because Y"
  2. Point to the exact file and line where the root cause lives.
  3. Explain WHY this causes the observed symptom.

What to check first

  • Recent changes: run git log --oneline -20 and git diff HEAD~5 on the suspect file. Did something change recently that introduced this?
  • Error timing: is it during startup, under load, on specific input?
  • Environment: does it happen in prod only? Test env? Both?
  • State dependency: does it depend on previous operations?

Output format

Write a short structured report:

# Root Cause Analysis

## Symptom
{what the user reported}

## Root cause
{file:line} — {one sentence}

## Evidence
1. {specific log line, test output, or code reference}
2. {another piece of evidence}

## Hypothesis
{1-2 sentences explaining why this causes the symptom}

## Confidence
{low/medium/high — "high" only if you traced it to a specific line}

## Not the root cause (ruled out)
- {thing you checked and eliminated}
- {another thing}

Rules

  • Do not write fixes. You investigate, not repair.
  • Do not guess. If you can't trace it, say so and list what you'd need to continue.
  • Trace to the source, not the symptom. A null pointer is a symptom — the question is why it's null.
  • Read code, not just tests. Tests tell you what's broken. Code tells you why.

Read the full file on GitHub · 81 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 · 81 lines · 58 tokens per session scan A 6f6b9d261efc

Subscribe to this mod's changes

root-cause-analyst is an agent published in the GitHub repository ushibo/brigade (1 stars, last pushed 1mo ago), licensed MIT. It adds 58 tokens to every session and 631 once invoked, about $0.0003 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 2026-08-31.

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