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 car-corrective-actiongit 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/car-corrective-action)<a href="https://agentmods.dev/skills/rbraga01/quality-engineering-skills/car-corrective-action"><img src="https://agentmods.dev/badge/skills/rbraga01/quality-engineering-skills/car-corrective-action/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/car-corrective-action"><img src="https://agentmods.dev/badge/skills/rbraga01/quality-engineering-skills/car-corrective-action.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 | $0.00080 | $0.02407 |
| Opus 5 | $0.00040 | $0.01203 |
| Sonnet 5 | $0.00016 | $0.00481 |
| Haiku 4.5 | $0.00008 | $0.00241 |
Grade A, and why
car-corrective-action 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 — 230 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Corrective Action Request (CAR) Writing
When to use
A CAR is written in response to:
- An NCR requiring permanent corrective action
- A customer complaint
- An internal or external audit finding (Major or Minor non-conformance)
- A recurring non-conformance requiring systemic correction
The CAR is the documented evidence that the problem was analysed, corrected, and prevented from recurring. ISO 9001 §10.2.1 requires documented information of the actions taken and their results. For IATF 16949 audit Major NCs, CARs must typically be closed within 90 days; check the applicable CSR for customer-specific closure deadlines.
Key distinction from NCR
| NCR | CAR |
|---|---|
| What is wrong (objective facts) | Why it is wrong + what is being done about it |
| Detection point and evidence | Root cause analysis + actions |
| Severity and disposition | Verification of effectiveness |
| Written immediately | Written after investigation |
A CAR references the NCR but extends it into corrective action territory.
CAR structure
1. Header
| Field | Content |
|---|---|
| CAR number | Traceable to NCR or audit finding |
| NCR / finding reference | Links this CAR to the trigger event |
| Date opened | |
| Owner | Responsible person (name, not function) |
| Target closure date | |
| Closure authority | Named person with authority to close this CAR (quality manager or equivalent) |
| Actual closure date | (filled on closure) |
2. Problem summary
One or two sentences summarising the NCR or finding. Objective, factual. Must match the NCR description exactly — no new interpretation.
Example:
"47 of 200 connector units in lot 2026-05-12-A had pin insertion depth 0.6–1.5 mm below lower specification limit (5.0 ± 0.3 mm). Detected at incoming inspection (NCR-2026-0047)."
3. Immediate containment (if not already in NCR)
Confirm containment is in place. If documented in the NCR, reference it. If not yet done, define it here.
4. Root cause analysis
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.
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 · 230 lines · 80 tokens per session scan A 7a5e08356b56
car-corrective-action is a skill published in the GitHub repository RBraga01/Quality-Engineering-Skills (28 stars, last pushed yesterday), licensed MIT. It adds 80 tokens to every session and 2,407 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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