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 msa-gauge-rrgit 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/msa-gauge-rr)<a href="https://agentmods.dev/skills/rbraga01/quality-engineering-skills/msa-gauge-rr"><img src="https://agentmods.dev/badge/skills/rbraga01/quality-engineering-skills/msa-gauge-rr/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/msa-gauge-rr"><img src="https://agentmods.dev/badge/skills/rbraga01/quality-engineering-skills/msa-gauge-rr.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 | $0.00088 | $0.02346 |
| Opus 5.5 | $0.00035 | $0.00938 |
| Sonnet 5.5 | $0.00018 | $0.00469 |
| Haiku 4.5 | $0.00009 | $0.00235 |
Grade A, and why
msa-gauge-rr 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 2mo 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 — 221 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Measurement System Analysis (MSA) / Gauge R&R
When to use
Use this skill when:
- Qualifying a measurement system for a new part or process (PPAP requirement)
- Interpreting Gauge R&R results — is this gauge acceptable?
- Auditing a supplier's MSA study for correctness and adequacy
- Selecting the right study type for a given measurement situation
- Investigating a quality problem where measurement error may be a factor
- Responding to a customer request for MSA data on a specific characteristic
Prerequisites
- The characteristic to be measured (product or process)
- The gauge or measurement system to be studied
- Production parts spanning the expected process variation (10 parts minimum)
- At least 2 trained appraisers who normally perform the measurement
- The specification (tolerance) for the characteristic
Workflow
Step 1 — Select the MSA study type
| Study type | When to use |
|---|---|
| Gauge R&R (crossed) | Variable data, 2–3 appraisers, each measures all parts (most common) |
| Gauge R&R (nested) | Variable data, parts are destroyed during measurement (e.g., tensile test) |
| Attribute MSA | Pass/fail, go/no-go, visual inspection — data is not a number |
| Bias study | Accuracy of a single gauge vs. a reference standard |
| Linearity study | Whether gauge accuracy is consistent across its measurement range |
| Stability study | Whether gauge accuracy drifts over time |
For PPAP: Crossed Gauge R&R is required for all variable gauges on special characteristics.
Step 2 — Crossed Gauge R&R study procedure
Setup:
- Minimum 10 parts selected to represent the full process variation range (not cherry-picked from centre of tolerance)
- Minimum 2 appraisers (3 preferred)
- Minimum 2 trials per appraiser per part (3 preferred)
- Parts randomly numbered and labelled — appraisers must not see each other's measurements
- Measurement conditions must match normal production conditions
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.
- 2mo ago First seen · 221 lines · 88 tokens per session scan A 77dfaa8c0438
msa-gauge-rr is a skill published in the GitHub repository RBraga01/Quality-Engineering-Skills (43 stars, last pushed 7d ago), licensed MIT. It adds 88 tokens to every session and 2,346 once invoked, about $0.0004 per session on Opus 5.5. 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.
msa-gauge-rr compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| msa-gauge-rrRBraga01/Quality-Engineering-Skills | Skill | 43 | 7d ago | MIT | A | 88 | Claude Code, Codex |
| flow-nexus-neuralproffesor-for-testing/agentic-qe | Skill | 525 | yesterday | MIT | A | 21 | Claude Code |
| agent-matrix-optimizerproffesor-for-testing/agentic-qe | Skill | 525 | yesterday | MIT | A | 21 | Claude Code |
| reliability-engineeringxjtulyc/awesome-rosetta-skills | Skill | 35 | 6mo ago | none | A | 33 | Claude Code, Codex |
| instrument-data-to-allotropeanthropics/knowledge-work-plugins | Skill | 35k | 2d ago | Apache-2.0 | A | 123 | Claude Code |
| exploratory-data-analysisK-Dense-AI/scientific-agent-skills | Skill | 56k | 4d ago | MIT | A | 83 | Claude Code |
| phylogeneticsK-Dense-AI/scientific-agent-skills | Skill | 56k | 4d ago | MIT | A | 71 | Claude Code, Codex |