fishbone-analysis

fishbone-analysis is a skill for Claude Code, Codex from RBraga01/Quality-Engineering-Skills. It costs 74 tokens per session (2,058 once invoked), scanned A, original, MIT.

A cause-and-effect diagram, also called an Ishikawa or fishbone diagram, for listing possible causes of a quality problem under six categories: people, machines, methods, materials, measurement, and environment.

In plain words
What is it for?
Use it to brainstorm causes during an 8D investigation, corrective-action review, or other root-cause analysis, then classify each cause using available evidence.
Why use it?
It helps an investigation consider the full process before selecting causes, reducing the risk of focusing too early on one explanation.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to brainstorm causes during an 8D investigation, corrective-action review, or other root-cause analysis, then classify each cause using available evidence.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/rbraga01/quality-engineering-skills/fishbone-analysis
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.

Any agent
npx skills add RBraga01/Quality-Engineering-Skills --skill fishbone-analysis
Clone the repo
git clone --depth 1 https://github.com/RBraga01/Quality-Engineering-Skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for fishbone-analysis

README.md
[![agentmods](https://agentmods.dev/badge/skills/rbraga01/quality-engineering-skills/fishbone-analysis/github.svg)](https://agentmods.dev/skills/rbraga01/quality-engineering-skills/fishbone-analysis)
Your own site
<a href="https://agentmods.dev/skills/rbraga01/quality-engineering-skills/fishbone-analysis"><img src="https://agentmods.dev/badge/skills/rbraga01/quality-engineering-skills/fishbone-analysis/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for fishbone-analysis

Your own site · 80×15
<a href="https://agentmods.dev/skills/rbraga01/quality-engineering-skills/fishbone-analysis"><img src="https://agentmods.dev/badge/skills/rbraga01/quality-engineering-skills/fishbone-analysis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 74 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,058 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • high Anti-Refusal · line 125
    Skill instructs the agent to omit warnings, disclaimers, or ethical commentary. Stripping safety caveats hides risk from the user and is a common jailbreak preamble.
    Fix: Remove instructions that suppress warnings, disclaimers, or ethical commentary. Let the agent surface safety-relevant caveats to the user.
How audits are shown
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 5.1 $0.00074 $0.02058
Opus 5 $0.00037 $0.01029
Sonnet 5 $0.00015 $0.00412
Haiku 4.5 $0.00007 $0.00206

Measured 9d ago against content hash d23711b27fbd, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

fishbone-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 9d 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.

skills/problem-solving/fishbone-analysis/SKILL.md · 202 lines

How it starts

The opening of the file, as written. The whole thing — 202 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Fishbone (Ishikawa) Analysis

When to use

Use fishbone analysis to brainstorm all possible causes of a quality problem before running 5-Why. It prevents tunnel vision and ensures no cause category is overlooked. Particularly valuable for complex defects with multiple potential contributing factors.

Typical use: 8D D4 brainstorming session, CAPA root cause investigation, initial problem analysis.

Prerequisites

  • Problem clearly defined with Is/Is-Not or 5W2H
  • Cross-functional team (quality, production, engineering at minimum)
  • Access to the process, machine, or product where defect occurred

Required Fishbone Checklist

☐ Problem statement defined and agreed before starting — no cause language in the problem statement ☐ All 6M categories addressed — at least one entry per M, or documented justification if a category is not applicable ☐ Brainstorming completed before any evaluation or elimination — do not evaluate while generating ☐ Every cause classified as Confirmed, Probable, or Unlikely using objective evidence — not opinion alone ☐ Confirmed = supported by data or physical evidence; Probable = logical, consistent with Is/Is-Not, not yet confirmed; Unlikely = contradicted by data ☐ Confirmed and Probable causes cross-checked against existing PFMEA failure cause entries before proceeding to 5-Why ☐ Each Confirmed or Probable cause carries forward to its own 5-Why chain ☐ After root cause confirmed: horizontal deployment check — could the same cause exist in similar parts, processes, or product families?


The 6M Framework

The six main "bones" of the fish. All six must be addressed. If a category genuinely does not apply, document: "No causes identified in this category after structured team review — not applicable because [reason]."

1. Man (Human Factors)

Questions to ask:

  • Was the task performed by a trained, qualified operator?
  • Is competence documented and current?
  • Was the operator following the correct work instruction?
  • Could fatigue, shift change, or distraction contribute?
  • Is the task ergonomically difficult or error-prone?
  • Is the same defect found on all shifts or only one? (single-shift → operator-specific)

Read the full file on GitHub · 202 lines

Files

What ships with it

1 file 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. 9d ago First seen · 202 lines · 74 tokens per session scan A d23711b27fbd

Subscribe to this mod's changes

fishbone-analysis is a skill published in the GitHub repository RBraga01/Quality-Engineering-Skills (28 stars, last pushed 4d ago), licensed MIT. It adds 74 tokens to every session and 2,058 once invoked, about $0.0004 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.