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 control-plangit 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/control-plan)<a href="https://agentmods.dev/skills/rbraga01/quality-engineering-skills/control-plan"><img src="https://agentmods.dev/badge/skills/rbraga01/quality-engineering-skills/control-plan/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/control-plan"><img src="https://agentmods.dev/badge/skills/rbraga01/quality-engineering-skills/control-plan.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 | $0.00081 | $0.02143 |
| Opus 5.5 | $0.00032 | $0.00857 |
| Sonnet 5.5 | $0.00016 | $0.00429 |
| Haiku 4.5 | $0.00008 | $0.00214 |
Grade A, and why
control-plan 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 — 203 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Control Plan
When to use
Use this skill when:
- Creating a new Control Plan for prototype, pre-launch, or production
- Reviewing an existing Control Plan for completeness and accuracy
- Updating the CP after a process change, corrective action (D7), or PFMEA update
- Auditing a supplier's Control Plan during qualification or an IATF audit
- Linking PFMEA controls to the Control Plan after FMEA review
Prerequisites
- Process Flow Diagram (required — CP must mirror the process flow sequence)
- PFMEA (required — CP controls derive from PFMEA recommended actions)
- Drawing with ballooned characteristics and tolerance data
- List of special and significant characteristics (SC, CC, KPC, KCC)
- MSA results for measurement systems referenced in the CP (for production CP)
Workflow
Step 1 — Determine the CP type
| Type | When | Purpose |
|---|---|---|
| Prototype | During prototype builds | Describes dimensional, material, and functional tests in prototype phase |
| Pre-launch | After prototype, before PPAP | Describes controls in place during pilot/pre-production runs |
| Production | After PPAP approval, at SOP | The living document — updated throughout product life |
All three types may coexist during APQP phases. The Production CP is the one submitted as PPAP Element 7.
Step 2 — Build the Control Plan structure
The CP is a table with one row per characteristic per process step. Each row contains:
Header section (document-level):
- Control Plan number and revision
- Part number and revision
- Part name / description
- Supplier / plant
- Supplier code (OEM code)
- Key contact / phone
- Core team (multi-functional)
- Date (original) and date (revised)
- Customer engineering approval (name/date) — if required
- Customer quality approval (name/date) — if required
- Supplier approval (name/date)
Detail columns (one row per characteristic):
| Column | What to enter |
|---|---|
| Part/process number | Reference number from Process Flow |
| Process name / operation description | Name of the process step |
| Machine, device, jig, or tool | Equipment used at this step |
| Number | Characteristic number (links to balloon drawing) |
| Product characteristic | Product feature being controlled (dimension, material property, appearance) |
| Process characteristic | Process parameter being controlled (temperature, pressure, speed, torque) |
| Special characteristic classification | SC, CC, KPC, KCC, *, ▲ per customer symbology |
| Product/process specification / tolerance | Nominal value and tolerance band |
| Evaluation / measurement technique | Gauge type, method, or test used |
| Sample size | Number of parts per sample |
| Frequency | How often samples are taken (every hour, every lot, 100%) |
| Control method | How the process is controlled (SPC chart, go/no-go gauge, visual, 100% inspection) |
| Reaction plan | What to do if out-of-control or out-of-specification (who, what action, containment) |
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 · 203 lines · 81 tokens per session scan A 7333a324c01a
control-plan is a skill published in the GitHub repository RBraga01/Quality-Engineering-Skills (43 stars, last pushed 7d ago), licensed MIT. It adds 81 tokens to every session and 2,143 once invoked, about $0.0003 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.
control-plan compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| control-planRBraga01/Quality-Engineering-Skills | Skill | 43 | 7d ago | MIT | A | 81 | Claude Code, Codex |
| api-testing-patternsproffesor-for-testing/agentic-qe | Skill | 525 | yesterday | MIT | A | 34 | Claude Code |
| accessibility-testingproffesor-for-testing/agentic-qe | Skill | 525 | yesterday | MIT | A | 50 | Claude Code |
| bug-reporting-excellenceproffesor-for-testing/agentic-qe | Skill | 525 | yesterday | MIT | A | 33 | Claude Code |
| code-review-qualityproffesor-for-testing/agentic-qe | Skill | 525 | yesterday | MIT | A | 33 | Claude Code |
| compliance-testingproffesor-for-testing/agentic-qe | Skill | 525 | yesterday | MIT | A | 43 | Claude Code |
| contract-testingproffesor-for-testing/agentic-qe | Skill | 525 | yesterday | MIT | A | 35 | Claude Code |