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Agent skill

Spc Control Charts

by hashgraph-online in hashgraph-online/awesome-codex-plugins

Statistical Process Control (SPC) — select the correct control chart, interpret out-of-control signals using Western Electric rules, calculate and interpret Cp, Cpk, Pp, Ppk.

MITAuto-check passed

Install Spc Control Charts

skills CLI
$ npx skills add hashgraph-online/awesome-codex-plugins --skill spc-control-charts -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install hashgraph-online/awesome-codex-plugins spc-control-charts --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/RBraga01/Quality-Engineering-Skills/skills/measurement/spc-control-charts .claude/skills/spc-control-charts && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
spc-control-charts
GitHub stars
1.3k
Token cost
~2.5k tokens
SKILL.md length
1,207 words
Files
2 (incl. references)
Skills in repo
716
Repo updated
First seen
Licence
MIT

At a glance

Statistical Process Control (SPC) — select the correct control chart, interpret out-of-control signals using Western Electric rules, calculate and interpret Cp, Cpk, Pp, Ppk.

  • Works in 6 steps: Select the correct control chart → Calculate control limits → Apply Western Electric Rules… → …
  • Setting up SPC for a new characteristic
  • SKILL.md covers When to use, Prerequisites, Workflow and Validation criteria, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Spc Control Charts is an agent skill from hashgraph-online/awesome-codex-plugins. Statistical Process Control (SPC) — select the correct control chart, interpret out-of-control signals using Western Electric rules, calculate and interpret Cp, Cpk, Pp, Ppk. Use when setting up SPC for a new characteristic, interpreting control chart signals, responding to special cause variation, or auditing SPC implementation. Covers AIAG SPC 2nd edition and IATF 16949 §8.3.3.

Its SKILL.md is about 2.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/chart-selection-guide.md`).

The repository describes itself as: A curated list of awesome OpenAI Codex / ChatGPT plugins, skills, and resources. The 1 Codex Marketplace. See live plugins at: https://hol.org/plugins/best-codex-plugins. The licence is MIT.

When your agent uses it

  • Setting up SPC for a new characteristic
  • Interpreting control chart signals
  • Responding to special cause variation
  • Auditing SPC implementation

Example prompts

  • “/spc-control-charts”

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. Select the correct control chart
  2. Calculate control limits
  3. Apply Western Electric Rules (out-of-control signals)
  4. Calculate and interpret process capability
  5. Respond to an out-of-control condition
  6. Audit an SPC implementation

What it can do on your machine

Read from SKILL.md and the folder at commit 3e1456a. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Spc Control Charts loads about 2.5k tokens when it runs, and up to ~6.7k if it reads all its reference files. Until then it costs about 100 tokens; SKILL.md has 1,207 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~100
When it runs · the whole SKILL.md, loaded when a task matches
~2.5k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~6.7k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from hashgraph-online/awesome-codex-plugins at commit 3e1456a, republished under its MIT licence (© hashgraph-online). 1,207 words, ~2,473 tokens.

Download SKILL.mdSave it as .claude/skills/spc-control-charts/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
spc-control-charts
description
Statistical Process Control (SPC) — select the correct control chart, interpret out-of-control signals using Western Electric rules, calculate and interpret Cp, Cpk, Pp, Ppk. Use when setting up SPC for a new characteristic, interpreting control chart signals, responding to special cause variation, or auditing SPC implementation. Covers AIAG SPC 2nd edition and IATF 16949 §8.3.3.
license
MIT
metadata.author
RBraga01
metadata.version
1.1
metadata.iso-9001
9.1
metadata.iatf-16949
8.3.3, 9.1.1
metadata.aiag-reference
AIAG SPC 2nd Edition
metadata.domain
quality-engineering
metadata.subdomain
measurement
metadata.industries
automotive,electronics,aerospace,medical,general
metadata.status
approved

Statistical Process Control (SPC)

When to use

Use this skill when:

  • Selecting the correct control chart type for a process characteristic
  • Interpreting control chart signals — is this special cause or common cause?
  • Calculating Cp, Cpk, Pp, Ppk and determining if the process is capable
  • Responding to an out-of-control signal on a production line
  • Setting up SPC for a new special characteristic (PPAP/APQP requirement)
  • Auditing an SPC system for correctness and adequacy
  • Explaining SPC results to a customer or during an audit

Prerequisites

  • The characteristic to monitor (variable or attribute data)
  • Production data (minimum 25 subgroups for control limits, 100+ pieces for capability)
  • MSA study completed and %GRR < 30% for variable charts
  • Process specification (nominal + tolerance) for capability calculations
  • Subgroup size decided based on rational subgrouping principle

Workflow

Step 1 — Select the correct control chart
Variable data (measured values — length, weight, pressure, temperature)
ChartWhen to use
X̄-R (X-bar/Range)Subgroup size 2–9; most common in manufacturing
X̄-S (X-bar/Sigma)Subgroup size ≥ 10; better sensitivity to spread
I-MR (Individuals/Moving Range)Subgroup size = 1; one measurement per inspection (slow processes, destructive tests)
Attribute data (counts, pass/fail, defect rates)
ChartWhen to use
p-chartProportion defective; variable subgroup size
np-chartNumber defective; constant subgroup size
c-chartCount of defects per unit; constant inspection area
u-chartDefects per unit; variable inspection area

Decision rule: If you can measure it with a number, use a variable chart. Variable charts are more sensitive and require smaller samples to detect process shifts.

Step 2 — Calculate control limits
X̄-R chart

From at least 25 subgroups of size n:

  • Centre line (X̄̄): Grand average of all subgroup means
  • UCL_X̄ = X̄̄ + A₂ × R̄
  • LCL_X̄ = X̄̄ − A₂ × R̄
  • Centre line (R̄): Average of all subgroup ranges
  • UCL_R = D₄ × R̄
  • LCL_R = D₃ × R̄ (= 0 for n ≤ 6)

Constants for common subgroup sizes:

nA₂D₃D₄
21.88003.267
31.02302.574
40.72902.282
50.57702.114

Important: Control limits are calculated FROM THE DATA — never set them to match the specification limits. Specification limits and control limits are completely separate concepts.

Step 3 — Apply Western Electric Rules (out-of-control signals)

Divide the control chart into zones: Zone A (2–3σ from centre), Zone B (1–2σ), Zone C (0–1σ).

RuleSignalInterpretation
Rule 11 point beyond 3σ (outside control limits)Large, immediate shift
Rule 29 consecutive points on same side of centre lineProcess mean has shifted
Rule 36 consecutive points steadily increasing or decreasingTrend — tool wear, drift
Rule 414 consecutive points alternating up and downSystematic variation — two alternating distributions
Rule 52 of 3 consecutive points in Zone A or beyond (same side)Large shift signal
Rule 64 of 5 consecutive points in Zone B or beyond (same side)Moderate shift
Rule 715 consecutive points in Zone C (either side of centre line)Stratification — data from two separate distributions
Rule 88 consecutive points beyond Zone C (either side)Mixture — sampling from two processes

Action required for ANY rule violation: Stop and investigate immediately. Do not reset control limits. Do not restart until root cause is identified.

Most commonly applied in automotive: Rules 1, 2, 3 minimum. Rules 1–8 for safety-critical characteristics.

Step 4 — Calculate and interpret process capability

Capability data requirements: Process capability is only valid when calculated on a process that is in statistical control (no out-of-control signals) and with a minimum of 100 consecutive parts from that stable process. Fewer parts produce unreliable Cpk estimates — a Cpk calculated on 30 parts can vary by ±0.3 from the true value. Do not report Cpk based on fewer than 100 parts as a production capability figure; label it "preliminary" and state the sample size.

Short-term capability (within-subgroup variation):

  • Cp = (USL − LSL) / (6σ̂) — capability — process spread vs. tolerance
  • Cpk = min[(USL − X̄̄) / (3σ̂), (X̄̄ − LSL) / (3σ̂)] — centred capability — accounts for process mean location

σ̂ = R̄ / d₂ (for X̄-R chart)

Long-term performance (total variation including between-subgroup):

  • Pp = (USL − LSL) / (6s) — same formula but uses overall standard deviation s
  • Ppk = min[(USL − X̄̄) / (3s), (X̄̄ − LSL) / (3s)]
Acceptance criteria
IndexMinimumTarget
Cpk1.331.67
Ppk1.331.67
CpkInterpretationPPAP action
≥ 1.67Excellent✅ Accepted
1.33 – 1.67Acceptable✅ Accepted — monitor
1.00 – 1.33Marginal⚠️ Customer approval required; add control measures
< 1.00Not capable❌ 100% inspection required; corrective action mandatory
Show full SKILL.md (495 more words)Show less
Cp vs. Cpk relationship
  • Cp = Cpk: process is perfectly centred
  • Cp > Cpk: process is off-centre — improve centering before widening control limits
  • Never report only Cp without Cpk — a process can be off-centre and still show a good Cp
Step 5 — Respond to an out-of-control condition
  1. Stop the process (or place affected output on hold) — do not continue producing to an out-of-control process
  2. Contain — identify affected output since last in-control point
  3. Investigate — ask: what changed? (material lot, operator, shift, tooling, environment)
  4. Identify root cause — use 5-Why or Fishbone (is-is-not to scope the problem first)
  5. Correct — implement correction and verify the process returns to control
  6. Document — note the signal, investigation, and action taken on the chart (or in the log)
  7. Update PFMEA and Control Plan if the root cause reveals a new failure mode

Do NOT simply recalculate control limits after a shift to make the chart "look in control."

Step 6 — Audit an SPC implementation

When reviewing SPC in production or at a supplier:

  • Correct chart type selected for data type (variable vs. attribute)
  • Minimum 25 subgroups used to calculate initial control limits
  • Control limits calculated from process data — NOT set to specification limits
  • Western Electric rules applied (minimum Rule 1, 2, 3)
  • Out-of-control signals are annotated on the chart with the action taken
  • Process capability calculated on stable (in-control) process only
  • Cpk ≥ 1.33 minimum; 1.67 for special characteristics
  • MSA study complete and %GRR < 30% for the gauge being used
  • Control chart is used for decision-making — not filled in retroactively

Validation criteria

An SPC implementation is adequate when:

  • Chart type matches data type and subgroup size
  • Control limits calculated from minimum 25 subgroups of production data
  • Process in statistical control before capability is calculated
  • Cpk ≥ 1.33 (minimum) for all monitored characteristics
  • Out-of-control signals trigger documented investigation and corrective action

Common mistakes

  • Setting control limits equal to specification limits (a fundamental SPC error — these are different concepts)
  • Calculating capability on an out-of-control process (meaningless — must be stable first)
  • Reporting Cp but not Cpk — hides off-centre processes
  • Using only n=1 individual charts when subgrouping would reveal more
  • Filling in control charts retroactively at end of shift — defeats the purpose of real-time monitoring
  • Recalculating control limits to eliminate out-of-control points without identifying root cause
  • Reporting Cpk = 1.45 based on 30 parts — too few; minimum 100 pieces for reliable capability

Output Format

At the start of each use, ask the user:

"How would you like to receive the output? A — Structured Markdown (formatted tables and sections, ready to copy) B — Plain tables (simplified structure for Excel or Word) C — Narrative report (flowing text for a formal document or email)

Default: A."

Adapt all output sections to the chosen format. If the platform or session context already defines a format preference, skip this question.

Changelog

VersionDateAuthorChange
1.02026-06-06@RBraga01Initial release
1.12026-06-06@migmccAdded 100-part minimum requirement for valid capability study in Step 4; clarified in-control prerequisite before capability calculation

© hashgraph-online, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file (references) in plugins/RBraga01/Quality-Engineering-Skills/skills/measurement/spc-control-charts of hashgraph-online/awesome-codex-plugins.

  • SKILL.md
  • references/chart-selection-guide.md

Open the folder on GitHubat commit 3e1456a

Compare with similar skills

Spc Control Charts next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Spc Control Charts compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Spc Control Charts this skillhashgraph-online/awesome-codex-plugins1.3k—~2.5kAutomated safety check: PassMIT
Statistical Analystalirezarezvani/claude-skills28k—~2.5kAutomated safety check: PassMIT
Statistical PowerK-Dense-AI/scientific-agent-skills48k1 repos~4.4kAutomated safety check: NotesMIT
Statistical Reportingaiming-lab/AutoResearchClaw15k—~756Automated safety check: PassMIT
Working With ChartsPostHog/posthog40k—~948Automated safety check: PassCustom licence
Manuscript Statistics AuditYuan1z0825/nature-skills47k2 repos~2.1kAutomated safety check: PassApache-2.0

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Questions about Spc Control Charts

What does Spc Control Charts do?

Statistical Process Control (SPC) — select the correct control chart, interpret out-of-control signals using Western Electric rules, calculate and interpret Cp, Cpk, Pp, Ppk. Spc Control Charts is an agent skill from hashgraph-online/awesome-codex-plugins. Statistical Process Control (SPC) — select the correct control chart, interpret out-of-control signals using Western Electric rules, calculate and interpret Cp, Cpk, Pp, Ppk.

When should I use Spc Control Charts?

Spc Control Charts fits situations like: setting up SPC for a new characteristic; interpreting control chart signals; responding to special cause variation; auditing SPC implementation.

How do I install Spc Control Charts in Claude Code?

Run `npx skills add hashgraph-online/awesome-codex-plugins --skill spc-control-charts -a claude-code`. Or copy the skill folder (plugins/RBraga01/Quality-Engineering-Skills/skills/measurement/spc-control-charts in hashgraph-online/awesome-codex-plugins) into .claude/skills/spc-control-charts in your project. Claude Code loads it when a task matches its description.

How do I install Spc Control Charts in Codex?

Run `npx skills add hashgraph-online/awesome-codex-plugins --skill spc-control-charts -a codex`. Or copy the skill folder (plugins/RBraga01/Quality-Engineering-Skills/skills/measurement/spc-control-charts in hashgraph-online/awesome-codex-plugins) into .agents/skills/spc-control-charts in your project. Codex loads it when a task matches its description.

Can I use Spc Control Charts in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add hashgraph-online/awesome-codex-plugins --skill spc-control-charts -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/spc-control-charts, .gemini/skills/spc-control-charts, .github/skills/spc-control-charts and .opencode/skills/spc-control-charts in your project.

What does Spc Control Charts need to run?

SKILL.md names no scripts, command-line tools or credentials: Spc Control Charts is instructions for the agent only.

Does Spc Control Charts access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Spc Control Charts safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Spc Control Charts use?

Spc Control Charts is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Spc Control Charts use?

About 2.5k tokens (SKILL.md is roughly 9.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 4.3k tokens, read only when the agent opens those files.

What are the alternatives to Spc Control Charts?

Skills that share tags, products or a category with Spc Control Charts: Statistical Analyst (alirezarezvani/claude-skills, 28k stars), Statistical Power (K-Dense-AI/scientific-agent-skills, 48k stars), Statistical Reporting (aiming-lab/AutoResearchClaw, 15k stars) and Working With Charts (PostHog/posthog, 40k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Spc Control Charts?

hashgraph-online (a GitHub organization) maintains it in hashgraph-online/awesome-codex-plugins, which has 1,267 GitHub stars. The repository holds 716 skills in this directory. The repository was last updated on October 10, 2026.

Source: hashgraph-online/awesome-codex-plugins on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.