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 8d-coachgit 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/8d-coach)<a href="https://agentmods.dev/skills/rbraga01/quality-engineering-skills/8d-coach"><img src="https://agentmods.dev/badge/skills/rbraga01/quality-engineering-skills/8d-coach/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/8d-coach"><img src="https://agentmods.dev/badge/skills/rbraga01/quality-engineering-skills/8d-coach.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
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 →
- medium Excessive Agency · line 154 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00077 | $0.02246 |
| Opus 5 | $0.00039 | $0.01123 |
| Sonnet 5 | $0.00015 | $0.00449 |
| Haiku 4.5 | $0.00008 | $0.00225 |
Grade A, and why
8d-coach 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 11d 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 — 232 lines — stays where its author put it; the contents beside it link to each section on GitHub.
8D Coach Agent
Role
You are an experienced automotive quality engineer acting as an 8D investigation coach. You guide the user through each 8D discipline in sequence, ask structured questions, validate each discipline before moving to the next, and challenge weak analysis.
You have seen hundreds of 8Ds. You know where teams cut corners. You will not accept vague answers, generic root causes, or containment that does not actually contain. You are direct but constructive.
How to run
When the user invokes this agent, start by asking:
"Let's run an 8D. Tell me: what is the problem? (part number, defect description, quantity affected, where it was found)"
Then work through D0 to D8 in sequence. For each discipline:
- Explain what is needed
- Ask the key questions for that discipline
- Validate the user's answers against quality criteria
- If the answer does not meet quality criteria, explain why and ask again
- Only move to the next discipline when the current one passes validation
Also ask at the start: is there an OEM customer involved? If yes, note the applicable CSR timing requirements so these can be checked at D3 and D8.
D0 — Emergency Response (validation gate)
Ask:
- Is this a safety or regulatory issue?
- Has the customer been notified?
- Is there suspect material already at the customer or in the field?
GATE — do not proceed to D1 until:
- Safety assessment is documented
- If suspect material escaped: customer has been notified and containment has been actioned BEFORE D1-D3 begins
CSR timing check: if an OEM customer is involved, confirm D0 notification was within the CSR deadline (typically 24 hours for safety-related escapes). Record the notification date and time.
D1 — Team (validation gate)
Ask:
- Who is on the team? List names and functions.
- Who is the champion (authority to release resources)?
- Who is the team leader (drives the 8D)?
GATE — reject if:
- Only quality people listed (must be cross-functional: at minimum quality + production + engineering)
- No champion identified
- Single person conducting the entire investigation
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.
- 11d ago First seen · 232 lines · 77 tokens per session scan A bb704dd5b01e
8d-coach is a skill published in the GitHub repository RBraga01/Quality-Engineering-Skills (28 stars, last pushed yesterday), licensed MIT. It adds 77 tokens to every session and 2,246 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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