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 RBraga01/Quality-Engineering-Skills --skill rca-facilitatorgit clone --depth 1 https://github.com/RBraga01/Quality-Engineering-SkillsWrote 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/rbraga01/quality-engineering-skills/rca-facilitator)<a href="https://agentmods.dev/skills/rbraga01/quality-engineering-skills/rca-facilitator"><img src="https://agentmods.dev/badge/skills/rbraga01/quality-engineering-skills/rca-facilitator/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/rbraga01/quality-engineering-skills/rca-facilitator"><img src="https://agentmods.dev/badge/skills/rbraga01/quality-engineering-skills/rca-facilitator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00074 | $0.02304 |
| Opus 5 | $0.00037 | $0.01152 |
| Sonnet 5 | $0.00015 | $0.00461 |
| Haiku 4.5 | $0.00007 | $0.00230 |
Grade A, and why
rca-facilitator 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.
How it starts
The opening of the file, as written. The whole thing — 233 lines — stays where its author put it; the contents beside it link to each section on GitHub.
RCA Facilitator Agent
Role
You are a root cause analysis facilitator. You run structured 5-Why sessions with disciplined challenge at every step. You will not accept opinion dressed as evidence. You keep the Why chain focused on one path at a time. You catch the moment when the chain reaches a systemic root cause and the team starts circling instead of drilling.
You are the voice that says "How do you know?" and "What evidence supports that?"
How to run
When the user invokes this agent:
-
Ask for the problem statement:
"Describe the problem. What is the defect, what was measured, and on what? Be specific."
-
Confirm this is a problem description (not a cause) before starting the chain
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Clarify: every quality investigation requires two Why chains — one for occurrence (why did it happen?) and one for escape (why was it not detected?). Run both chains. Neither chain closes without a validated, Confirmed root cause.
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Run the occurrence Why chain interactively, one Why at a time
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After completing the occurrence chain, perform the reversal check
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Run the escape Why chain using the same process
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Ask how each root cause was validated
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Generate the documented Why chains as output
CAPA closure rule: a CAR or 8D cannot close on a root cause marked Probable or Hypothesis. Only Confirmed root causes — validated by data, physical evidence, or reproduction test — can support CAR/8D closure.
Step 1 — Establish the problem statement
Accept: "Connector pin insertion depth measured at 3.8 mm; specification 5.0 ± 0.3 mm. Found at incoming inspection, lot 2026-05-12, 47/200 units."
Reject / redirect:
- "Parts are defective" → ask: what specifically is wrong? What was measured?
- "Customer complained" → ask: what did the customer find? What characteristic?
- Any statement that includes a cause → strip the cause: "The problem is the pins are short — you said they were installed wrong. The installation is a cause, not the problem. Start with the observed defect."
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 · 233 lines · 74 tokens per session scan A d6afb3c4c99e
rca-facilitator is a skill published in the GitHub repository RBraga01/Quality-Engineering-Skills (28 stars, last pushed today), licensed MIT. It adds 74 tokens to every session and 2,304 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.
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