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.
npx skills add charlieviettq/awesome-agent-skill --skill algo-mfg-fmeagit clone --depth 1 https://github.com/charlieviettq/awesome-agent-skillWrote 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.
[](https://agentmods.dev/skills/charlieviettq/awesome-agent-skill/algo-mfg-fmea)<a href="https://agentmods.dev/skills/charlieviettq/awesome-agent-skill/algo-mfg-fmea"><img src="https://agentmods.dev/badge/skills/charlieviettq/awesome-agent-skill/algo-mfg-fmea/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.
<a href="https://agentmods.dev/skills/charlieviettq/awesome-agent-skill/algo-mfg-fmea"><img src="https://agentmods.dev/badge/skills/charlieviettq/awesome-agent-skill/algo-mfg-fmea.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00073 | $0.01192 |
| Opus 5 | $0.00036 | $0.00596 |
| Sonnet 5 | $0.00015 | $0.00238 |
| Haiku 4.5 | $0.00007 | $0.00119 |
Grade A, and why
"algo-mfg-fmea" 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 12d 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.
This is a copy
92% identical to algo-mfg-fmea — 8 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.
How it starts
The opening of the file, as written. The whole thing — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.
FMEA (Failure Mode and Effects Analysis)
Overview
FMEA systematically identifies potential failure modes, their effects, causes, and current controls. Each failure is scored on Severity (S), Occurrence (O), and Detection (D) on 1-10 scales. RPN = S × O × D prioritizes which risks to address first. AIAG-VDA FMEA (2019) replaces RPN with Action Priority (AP) matrix.
When to Use
Trigger conditions:
- Designing new products/processes and identifying risks proactively
- Systematically evaluating existing failure modes for prioritization
- Meeting automotive (IATF 16949) or medical device (ISO 13485) quality requirements
When NOT to use:
- For root cause analysis of a known problem (use fishbone/5-why)
- For statistical analysis of defect data (use SPC or Pareto)
Algorithm
IRON LAW: Severity Can NEVER Be Reduced by Design Changes
Severity is determined by the EFFECT on the customer. A brake failure
is always severity 10, regardless of how unlikely or detectable it is.
FMEA reduces risk by: lowering Occurrence (better design/process) or
improving Detection (better testing/inspection). NEVER inflate
Detection scores to lower RPN artificially.
Phase 1: Input Validation
Define scope: Design FMEA (DFMEA) or Process FMEA (PFMEA). Assemble cross-functional team. Prepare: process flow diagram or system block diagram. Gate: Scope defined, team assembled, reference diagrams available.
Phase 2: Core Algorithm
- List all potential failure modes for each function/process step
- For each failure mode, identify: effect on customer, root cause(s), current prevention controls, current detection controls
- Score: Severity (1-10), Occurrence (1-10), Detection (1-10)
- Classic RPN: RPN = S × O × D. Prioritize high RPNs.
- AIAG-VDA AP: Use the S-O-D combination matrix to assign Action Priority: High, Medium, Low.
- Define recommended actions for High-priority items with responsibility and target dates
Phase 3: Verification
Review: are all functions/steps covered? Do severity scores match actual customer impact? Are detection scores realistic (not overly optimistic)? Gate: Complete coverage, realistic scoring, actions assigned for high-priority items.
What ships with it
3 files 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.
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.
- 12d ago First seen · 89 lines · 73 tokens per session scan A 35ff81be6069
"algo-mfg-fmea" is a skill published in the GitHub repository charlieviettq/awesome-agent-skill (25 stars, last pushed 1mo ago), licensed MIT. It adds 73 tokens to every session and 1,192 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 92% identical to algo-mfg-fmea, differing in 8 lines, and is treated as a copy.
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