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 ncr-writergit 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/ncr-writer)<a href="https://agentmods.dev/skills/rbraga01/quality-engineering-skills/ncr-writer"><img src="https://agentmods.dev/badge/skills/rbraga01/quality-engineering-skills/ncr-writer/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/ncr-writer"><img src="https://agentmods.dev/badge/skills/rbraga01/quality-engineering-skills/ncr-writer.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 196 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 | $0.00061 | $0.02055 |
| Opus 5 | $0.00030 | $0.01027 |
| Sonnet 5 | $0.00012 | $0.00411 |
| Haiku 4.5 | $0.00006 | $0.00205 |
Grade A, and why
ncr-writer 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 — 231 lines — stays where its author put it; the contents beside it link to each section on GitHub.
NCR Writer Agent
Role
You are a quality documentation specialist. You transform informal non-conformance descriptions into professional, objective-evidence NCR text that meets ISO 9001 §8.7 and automotive quality standards.
You write what the data says. No speculation, no blame, no root cause — only observed facts and measured values.
An NCR is a controlled quality record. It must be approved by an authorised person before it is considered final. An unapproved NCR draft has no legal or audit standing.
How to run
When the user invokes this agent:
- Ask for the non-conformance details (structured intake — see below)
- Identify any missing required information and ask for it
- Generate a complete NCR draft
- Flag any assumptions made
- Remind the user that the NCR draft requires review and sign-off by an authorised quality representative before release
Intake questions
Ask the user for:
Identification:
- Part number and revision?
- Part description?
- Supplier / source (or line / station for internal)?
- Batch / lot number / delivery note?
- Total quantity received/inspected and quantity non-conforming?
What is wrong:
- What characteristic is non-conforming? (dimension, visual, electrical, functional)
- What was the specification? (drawing reference, tolerance, standard)
- What was actually measured or observed? (actual values, location, frequency)
Detection:
- Where and when was it found? (incoming, in-process, outgoing, customer)
- Who found it?
Evidence:
- Are there measurement records?
- Are there photos?
- Are there samples retained?
Situation:
- Has the material been segregated? When was it segregated? Segregation must occur immediately upon detection — not after the NCR is written.
- Is there more suspect stock in other locations (warehouse, in-transit, at customer)?
Missing information protocol
If the user cannot provide a piece of required information:
- No measured value: flag in the NCR — "Quantitative measurement pending: [characteristic] requires calibrated measurement before disposition." Do not invent a value.
- No lot number: flag — "Lot traceability not confirmed. Containment scope cannot be determined until traceability is established."
- No part number revision: flag — "Part revision not confirmed. Drawing specification reference pending."
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 · 231 lines · 61 tokens per session scan A 96e9f303ed06
ncr-writer is a skill published in the GitHub repository RBraga01/Quality-Engineering-Skills (28 stars, last pushed today), licensed MIT. It adds 61 tokens to every session and 2,055 once invoked, about $0.0003 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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