Build a PFMEA worksheet, process risk analysis, or AP table using the AIAG-VDA FMEA Handbook 2019 7-step approach.

MITAuto-check passedEducation

Install Pfmea Process

skills CLI
$ npx skills add hashgraph-online/awesome-codex-plugins --skill pfmea-process -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install hashgraph-online/awesome-codex-plugins pfmea-process --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/RBraga01/Quality-Engineering-Skills/skills/risk-analysis/pfmea-process .claude/skills/pfmea-process && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
pfmea-process
GitHub stars
1.2k
Token cost
~2.9k tokens
SKILL.md length
1,409 words
Files
3 (incl. references, assets)
Skills in repo
736
Repo updated
First seen
Licence
MIT

At a glance

Build a PFMEA worksheet, process risk analysis, or AP table using the AIAG-VDA FMEA Handbook 2019 7-step approach.

  • Works in 7 steps: Planning and Preparation → Structure Analysis → Function Analysis → …
  • Tasks that involve Root cause analysis
  • SKILL.md covers Goal, Required Execution Checklist, When to use and Prerequisites, plus 5 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Pfmea Process is an agent skill from hashgraph-online/awesome-codex-plugins. Build a PFMEA worksheet, process risk analysis, or AP table using the AIAG-VDA FMEA Handbook 2019 7-step approach. Covers Structure Analysis, Function Analysis, Failure Analysis, Risk Analysis (Action Priority H/M/L), Optimization, and Documentation. Required by IATF 16949 and OEM customer-specific requirements for new processes, process changes, and post-escape PFMEA updates.

Its SKILL.md is about 2.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including reference files and assets (for example `assets/ap-table.md` and `references/aiag-vda-2019.md`).

It sits in Education, covering Root cause analysis and Educational content. The repository describes itself as: A curated list of awesome OpenAI Codex / ChatGPT plugins, skills, and resources. The 1 Codex Marketplace. See live plugins at: https://hol.org/plugins/best-codex-plugins. The licence is MIT.

When your agent uses it

  • Tasks that involve Root cause analysis
  • Tasks that involve Educational content

Example prompts

  • “/pfmea-process”

Workflow steps

7 steps, taken from the step headings in SKILL.md.

  1. Planning and Preparation
  2. Structure Analysis
  3. Function Analysis
  4. Failure Analysis
  5. Risk Analysis (Action Priority)
  6. Optimization
  7. Results Documentation

What it can do on your machine

Read from SKILL.md and the folder at commit 16b4156. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Pfmea Process loads about 2.9k tokens when it runs, and up to ~6.8k if it reads all its reference files. Until then it costs about 98 tokens; SKILL.md has 1,409 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~98
When it runs · the whole SKILL.md, loaded when a task matches
~2.9k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~6.8k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from hashgraph-online/awesome-codex-plugins at commit 16b4156, republished under its MIT licence (© hashgraph-online). 1,409 words, ~2,873 tokens.

Download SKILL.mdSave it as .claude/skills/pfmea-process/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
pfmea-process
description
Build a PFMEA worksheet, process risk analysis, or AP table using the AIAG-VDA FMEA Handbook 2019 7-step approach. Covers Structure Analysis, Function Analysis, Failure Analysis, Risk Analysis (Action Priority H/M/L), Optimization, and Documentation. Required by IATF 16949 and OEM customer-specific requirements for new processes, process changes, and post-escape PFMEA updates.
license
MIT
metadata.author
RBraga01
metadata.version
1.1
metadata.iso-9001
8.1
metadata.iatf-16949
8.3.3.3
metadata.aiag-reference
AIAG-VDA FMEA Handbook 2019, Steps 1–7
metadata.domain
quality-engineering
metadata.subdomain
risk-analysis
metadata.industries
automotive,electronics,aerospace,medical,general
metadata.status
approved

Process FMEA (PFMEA) — AIAG-VDA 2019

Goal

Identify and prioritise process risk before production — using the AIAG-VDA 2019 7-step approach — so that high-priority failure modes are eliminated or controlled before they reach the customer, and the result feeds directly into the Control Plan and Work Instructions.

Required Execution Checklist

  • Scope defined: process step boundaries, model year, team assembled with cross-functional representation
  • Process Flow Diagram (PFD) available and used as Step 2 input
  • All process steps in the PFD have a corresponding entry in Structure Analysis (Step 2)
  • Every process step has at least one Function defined in Step 3
  • Failure chain complete for each function: Effect → Mode → Cause (in this direction — not reversed)
  • All Failure Causes are evidence-based — no unverified assumptions used as final causes
  • S/O/D ratings agreed by the cross-functional team and documented
  • All Special Characteristics have S=9 or S=10
  • Every H-AP item has a named owner, target date, and is tracked to closure
  • PFMEA detection controls match the Control Plan; prevention controls match Work Instructions

When to use

  • New process development (pre-production)
  • Existing process change or transfer
  • After a quality escape (update to reflect failure mode)
  • Periodic review (IATF requires annual review or at change)
  • Customer-specific requirement (Ford, GM, Stellantis, BMW, VW all require PFMEA)

Prerequisites

  • Process flow diagram (PFD) — required for Step 2
  • Product drawings with special characteristics identified
  • DFMEA (if applicable) for effect severity reference
  • Team: process engineer, quality engineer, production supervisor, maintenance

The 7-Step AIAG-VDA 2019 Approach


Step 1 — Planning and Preparation

Define the scope:

  • FMEA header: part number, part name, model year, process step scope, revision, date, team
  • Analysis boundary: which process steps are in scope (start point and end point)
  • Timeline: new PFMEA or revision of existing?

Prepare:

  • Process Flow Diagram (PFD) — this drives Steps 2 and 3
  • List of Special Characteristics (SC) from the drawing (symbols: ◆ ★ ⬟ vary by customer)

Step 2 — Structure Analysis

Map the process hierarchy:

Process Item (e.g., Steering Column Assembly Line)
└── Process Step (e.g., Station 3 — Torque tightening)
    └── Work Element (e.g., Pneumatic driver, torque wrench)

For each process step, identify the 4M inputs: Man, Machine, Method, Material.

This structure becomes the "what can go wrong" framework in Step 4.

Consistency check: Every Process Step defined here must have at least one Function defined in Step 3. A process step with no function is incomplete — it cannot be analysed for failure in Step 4.


Step 3 — Function Analysis

For each process step and work element, define:

  • Process function: what should happen? (verb + noun + measurable characteristic)
    • Example: "Tighten bolt M8 to 22 ± 2 Nm"
  • Product characteristic: what product feature results from this step?
    • Flag all Special Characteristics (SC) — these get highest attention in D/O/D ratings

Functional chain:

Work Element function → Process Step function → Product Characteristic
(tool applies torque) → (bolt is tightened to spec) → (joint meets strength requirement)

Step 4 — Failure Analysis

For each function, identify the failure chain: Failure Effect → Failure Mode → Failure Cause

Work in this direction (Effect first, then Mode, then Cause):

Failure Effect (FE): what is the impact on the customer (internal or end user)?

  • End-user effect (most severe): safety, regulatory non-compliance, loss of function
  • Manufacturing effect: rework, scrap, line stoppage, warranty

Failure Mode (FM): how does this process step fail to perform its function?

  • Example: "Bolt torqued too low", "Part installed backwards", "Incorrect material loaded"

Failure Cause (FC): what causes the failure mode?

  • Machine: "Torque wrench not calibrated", "Air pressure drop"
  • Man: "Work instruction not followed", "Untrained operator"
  • Method: "Incorrect torque value in WI", "No torque verification step"
  • Material: "Wrong bolt grade loaded", "Lubrication not applied"

Multiple causes per failure mode are normal — each FC gets its own row.

Failure Cause validation: Failure Causes must be supported by objective evidence or structured root cause analysis (e.g., 5-Why). Unverified assumptions — "probably," "may be," "could be" — must not be entered as final Failure Causes. For post-escape PFMEA updates, the FC must match the validated root cause from the 8D or CAPA, not a revised opinion.


Step 5 — Risk Analysis (Action Priority)

For each FC row, assign three ratings:

Severity (S) — impact of the Failure Effect on the customer
SEffect
10Safety — affects operator safety without warning
9Regulatory non-compliance
8Loss of primary function (end user)
7Reduced primary function
6Loss of comfort / convenience function
5Reduced comfort / convenience function
4Appearance issue — noticed by most
3Appearance issue — noticed by some
2Appearance issue — noticed by discriminating
1No effect

Severity rates the EFFECT, not the mode or cause. S=10 or S=9 means you must act regardless of O and D.

Occurrence (O) — likelihood the Failure Cause leads to the Failure Mode
OFailure Rate
10≥ 1 in 2
91 in 8
81 in 20
71 in 80
61 in 400
51 in 2,000
41 in 15,000
31 in 150,000
21 in 1,500,000
1Failure eliminated by prevention control

O considers prevention controls already in place (poka-yoke, SPC, incoming inspection of material).

Detection (D) — effectiveness of detection controls before product reaches next customer
DDetection
10No detection control
9Control unlikely to detect
8Control may detect
7Control has low chance of detection
6Control may detect — moderate
5Control likely to detect
4Control has good chance of detection
3Control almost certain to detect
2Control certain to detect — automatic rejection
1Failure mode cannot occur (prevented)

D considers detection controls already in place (gauging, inspection, poka-yoke).

Show full SKILL.md (548 more words)Show less
Action Priority (AP) — replaces legacy RPN

Use the AP table (see action-priority-ap skill for full table):

APMeaningRequired action
H (High)Action requiredAssign responsible owner + target date. Escalate if no improvement possible.
M (Medium)Action recommendedTeam should evaluate — reduction may be beneficial
L (Low)No action requiredDocument rationale for no action

Critical rule: S = 9 or 10 → AP is always H regardless of O and D.

Ratings discipline: All S/O/D ratings must be agreed by the cross-functional team — not assigned unilaterally by one engineer. Where team members disagree, document the rationale for the rating chosen. Ratings without team consensus are not acceptable for PPAP submission or customer OEM review.


Step 6 — Optimization

For every H-AP item: define a corrective action.

For each action:

  • Description of the action
  • Responsible person (name, not function)
  • Target completion date
  • Re-assess S/O/D after action: new AP (revised)

Priority for action type:

  1. Prevent the cause (best): eliminate the cause by design or poka-yoke
  2. Reduce occurrence: add process control that makes the cause less likely
  3. Improve detection: add or improve detection control (least preferred — doesn't prevent defect, only catches it)

Avoid the common trap of only improving detection (lowering D) — this catches defects but doesn't prevent them.

Tracking discipline: All actions must be logged in the PFMEA and tracked to closure with objective evidence (completed action description + implementation date + revised S/O/D ratings). Open H-AP items past their target date must be escalated to management with a documented reason for delay and a revised target date. A PFMEA with overdue open H-AP items is not acceptable for PPAP submission or OEM audit.


Step 7 — Results Documentation

Final PFMEA deliverables:

  • Completed PFMEA form with all 7 steps documented
  • Summary of H-AP items and their actions (status: open/closed)
  • Link to updated Control Plan (detection controls in PFMEA → control methods in CP)
  • Link to updated Work Instructions (prevention controls → WI procedures)
  • PFMEA revision history

PFMEA → Control Plan linkage: Every detection control in the PFMEA must have a corresponding entry in the Control Plan. Every prevention control must be reflected in the Work Instruction.

Validation checklist

Before releasing the PFMEA:

  • All process steps from the PFD are in the Structure Analysis
  • All Special Characteristics are identified and have S=9 or S=10
  • Every H-AP item has an owner and a target date
  • No H-AP items remain open without documented escalation reason
  • Detection controls in PFMEA match the Control Plan
  • Prevention controls in PFMEA match Work Instructions
  • All Failure Causes are evidence-based (no unverified assumptions used as final causes)
  • PFMEA review triggered by one of the mandatory events: process change, quality escape (post-8D update), or annual review (IATF 16949 §8.3.3.3)

Output Format

At the start of each use, ask the user:

"How would you like to receive the output? A — Structured Markdown (formatted tables and sections, ready to copy) B — Plain tables (simplified structure for Excel or Word) C — Narrative report (flowing text for a formal document or email)

Default: A."

Adapt all output sections to the chosen format. If the platform or session context already defines a format preference, skip this question.

Reference files

Changelog

VersionDateAuthorChange
1.02026-06-01@RBraga01Initial release
1.12026-06-03@RBraga01Expanded 7-step workflow with AP gate requirements and PPAP integration

© hashgraph-online, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files (references, assets) in plugins/RBraga01/Quality-Engineering-Skills/skills/risk-analysis/pfmea-process of hashgraph-online/awesome-codex-plugins.

  • SKILL.md
  • assets/ap-table.md
  • references/aiag-vda-2019.md

Open the folder on GitHubat commit 16b4156

Compare with similar skills

Pfmea Process next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Pfmea Process compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Pfmea Process this skillhashgraph-online/awesome-codex-plugins1.2k—~2.9kAutomated safety check: PassMIT
Codebase to Coursezarazhangrui/codebase-to-course5.7k—~4.4kAutomated safety check: PassNone
Mistake Analyzermingchen666/Reviva236—~2.7kAutomated safety check: PassNone
Error Pattern Analyzerrevfactory/harness-1001.3k—~1.1kAutomated safety check: PassApache-2.0
OpenMAIC Setup and ExtensionTHU-MAIC/OpenMAIC40k—~1.7kAutomated safety check: NotesMIT
AI Engineering Project Tutorrohitg00/ai-engineering-from-scratch65k—~1.6kAutomated safety check: PassMIT

Similar skills

  • Codebase to Course

    zarazhangrui/codebase-to-course

    Turns a codebase into an interactive single-page HTML course for non-technical learners, with scroll modules, animated diagrams, quizzes and plain-English code translations.

    5.7k GitHub stars~4.4k tokensUpdated 6 mo ago
    EducationAuto-check passed
  • Mistake Analyzer

    mingchen666/Reviva

    Analyze incorrect answers from text, documents, or images; identify root causes of mistakes; classify error types; explain correct reasoning; and generate targeted improvement suggestions…

    236 GitHub stars~2.7k tokensUpdated 16 days ago
    EducationAuto-check passed
  • Error Pattern Analyzer

    revfactory/harness-100

    A specialized skill for systematically classifying error patterns and constructing concept deficit maps.

    1.3k GitHub stars~1.1k tokensUpdated 6 mo ago
    EducationAuto-check passed
  • Guides setup, classroom generation and secondary development for OpenMAIC, the multi-agent interactive classroom, one confirmed phase at a time.

    40k GitHub stars~1.7k tokensUpdated today
    EducationAuto-check: notes
  • AI Engineering Project Tutor

    rohitg00/ai-engineering-from-scratch

    Tutors a learner through one stage of a hands-on AI engineering project per session: lesson, prediction, code, grader run and reflection, with hints but never full solutions.

    65k GitHub stars~1.6k tokensUpdated today
    EducationAuto-check passed
  • Hung-Yi Lee Teaching Style

    voidful/hung-yi-lee-skill

    Explains machine learning, LLMs, AI agents and speech modeling in a Hung-Yi Lee-inspired teaching style, drawing on a knowledge base built from his lectures and research references.

    1.3k GitHub stars~13k tokensUpdated 1 mo ago
    EducationAuto-check passed

More from hashgraph-online/awesome-codex-plugins

All 736 skills in this repo
  • Anime Reaction Gif

    hashgraph-online/awesome-codex-plugins

    Create original anime-style reaction stickers as looping GIFs and MP4 previews, using generated character pose sheets and timed key poses.

    1.2k GitHub stars~922 tokensUpdated today
    Auto-check passed
  • Calibredb

    hashgraph-online/awesome-codex-plugins

    Manage and query Calibre libraries with the calibredb CLI (local paths or Calibre Content server URLs).

    1.2k GitHub stars~1k tokensUpdated today
    Auto-check passed
  • Rust API Test Harness

    hashgraph-online/awesome-codex-plugins

    A skill your agent uses when adding, changing, testing, or debugging Rust HTTP APIs and services, especially when Codex needs black-box integration tests, random-port app startup, real database test…

    1.2k GitHub stars~1.7k tokensUpdated today
    Auto-check passed
  • Art

    hashgraph-online/awesome-codex-plugins

    Make a studio's game look like something at build time — a cover from a real frame of the game (free), painted covers, backdrops, textures and character plates from image models through the…

    1.2k GitHub stars~2.4k tokensUpdated today
    Auto-check passed
  • Calle

    hashgraph-online/awesome-codex-plugins

    Use CALL-E from Codex through the calle CLI. An agent skill from hashgraph-online/awesome-codex-plugins.

    1.2k GitHub stars~2.9k tokensUpdated today
    Auto-check passed
  • Game Balance Economy

    hashgraph-online/awesome-codex-plugins

    Balance game difficulty, resources, rewards, probability, progression, economies, and dominant strategies.

    1.2k GitHub stars~618 tokensUpdated today
    Auto-check passed

Questions about Pfmea Process

What does Pfmea Process do?

Build a PFMEA worksheet, process risk analysis, or AP table using the AIAG-VDA FMEA Handbook 2019 7-step approach. Pfmea Process is an agent skill from hashgraph-online/awesome-codex-plugins. Build a PFMEA worksheet, process risk analysis, or AP table using the AIAG-VDA FMEA Handbook 2019 7-step approach.

When should I use Pfmea Process?

Pfmea Process fits situations like: tasks that involve Root cause analysis; tasks that involve Educational content.

How do I install Pfmea Process in Claude Code?

Run `npx skills add hashgraph-online/awesome-codex-plugins --skill pfmea-process -a claude-code`. Or copy the skill folder (plugins/RBraga01/Quality-Engineering-Skills/skills/risk-analysis/pfmea-process in hashgraph-online/awesome-codex-plugins) into .claude/skills/pfmea-process in your project. Claude Code loads it when a task matches its description.

How do I install Pfmea Process in Codex?

Run `npx skills add hashgraph-online/awesome-codex-plugins --skill pfmea-process -a codex`. Or copy the skill folder (plugins/RBraga01/Quality-Engineering-Skills/skills/risk-analysis/pfmea-process in hashgraph-online/awesome-codex-plugins) into .agents/skills/pfmea-process in your project. Codex loads it when a task matches its description.

Can I use Pfmea Process in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add hashgraph-online/awesome-codex-plugins --skill pfmea-process -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/pfmea-process, .gemini/skills/pfmea-process, .github/skills/pfmea-process and .opencode/skills/pfmea-process in your project.

What does Pfmea Process need to run?

SKILL.md names no scripts, command-line tools or credentials: Pfmea Process is instructions for the agent only.

Does Pfmea Process access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Pfmea Process safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Pfmea Process use?

Pfmea Process is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Pfmea Process use?

About 2.9k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 3.9k tokens, read only when the agent opens those files.

What are the alternatives to Pfmea Process?

Skills that share tags, products or a category with Pfmea Process: Codebase to Course (zarazhangrui/codebase-to-course, 5.7k stars), Mistake Analyzer (mingchen666/Reviva, 236 stars), Error Pattern Analyzer (revfactory/harness-100, 1.3k stars) and OpenMAIC Setup and Extension (THU-MAIC/OpenMAIC, 40k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Pfmea Process?

hashgraph-online (a GitHub organization) maintains it in hashgraph-online/awesome-codex-plugins, which has 1,232 GitHub stars. The repository holds 736 skills in this directory. The repository was last updated on October 6, 2026.

Source: hashgraph-online/awesome-codex-plugins on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.