How do I install the Pg Workflow skill?

Run npx skillmds@latest add exekiel179/pg-workflow in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Pg Workflow safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Pg Workflow?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Pg Workflow free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Pg Workflow?

Exekiel179 (@exekiel179) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Pg Workflow by exekiel179 — Agent Skill

Name: Pg Workflow
Author: Exekiel179

Pg Workflow

Run and resume the stateful Pingouin psychology statistics workflow. Use when the user wants an end-to-end, auditable analysis from intake through screening, analysis, approval, reporting, and archive, or asks to continue an existing analysis run.

Exekiel179 2ab01a0 2 files · 2.3 KB Updated Sep 17, 2026

File contents

PG Workflow

Use this skill as the cross-platform orchestration entry point. Claude Code users may use the /pg-* commands; Codex and other agents should invoke this skill directly.

Load

Read these references in order:

../../references/workflow-contract.md
../../references/archive-contract.md
../../references/intake-checklist.md when starting a new run
../../references/supervision-gates.md before approval
../../references/pingouin-optimization.md before generating Pingouin code

Use ../../scripts/workflow_engine.py for every state transition. Never edit run-manifest.json status by hand.

Dispatch

Find the active run under archive/analysis-runs/, or initialize one with scripts/init_analysis_run.py.
Read the manifest status.
Execute only the next allowed stage from workflow-contract.md.
Save the stage artifacts before advancing the state.
If approval returns REVISE, repair and return to analyzed; if BLOCKED, stop and explain the missing decision or data.
Finish only after workflow_engine.py check <run> passes at complete.

Required Handoff Block

Before each stage, return:

Run: <run-id>
State: <current>
Next: <target state and stage>
Inputs: <files/data available>
Outputs: <files this stage will create>
Guardrail: <highest-risk issue>

Hard Rules

Do not run inferential analysis before screening artifacts exist.
Do not report conclusions before an approved or approved_with_notes state.
Do not claim results from code that has not produced stored numerical output.
Do not copy raw participant data into an archive unless the user explicitly confirms the privacy handling.
Keep the S0-S5 audit line in the final handoff.

---name: pg-workflowdescription: Run and resume the stateful Pingouin psychology statistics workflow. Use when the user wants an end-to-end, auditable analysis from intake through screening, analysis, approval, reporting, and archive, or asks to continue an existing analysis run.---# PG WorkflowUse this skill as the cross-platform orchestration entry point. Claude Code users may use the `/pg-*` commands; Codex and other agents should invoke this skill directly.## LoadRead these references in order:1. `../../references/workflow-contract.md`2. `../../references/archive-contract.md`3. `../../references/intake-checklist.md` when starting a new run4. `../../references/supervision-gates.md` before approval5. `../../references/pingouin-optimization.md` before generating Pingouin codeUse `../../scripts/workflow_engine.py` for every state transition. Never edit `run-manifest.json` status by hand.## Dispatch1. Find the active run under `archive/analysis-runs/`, or initialize one with `scripts/init_analysis_run.py`.2. Read the manifest status.3. Execute only the next allowed stage from `workflow-contract.md`.4. Save the stage artifacts before advancing the state.5. If approval returns `REVISE`, repair and return to `analyzed`; if `BLOCKED`, stop and explain the missing decision or data.6. Finish only after `workflow_engine.py check <run>` passes at `complete`.## Required Handoff BlockBefore each stage, return:```markdownRun: <run-id>State: <current>Next: <target state and stage>Inputs: <files/data available>Outputs: <files this stage will create>Guardrail: <highest-risk issue>```## Hard Rules- Do not run inferential analysis before screening artifacts exist.- Do not report conclusions before an `approved` or `approved_with_notes` state.- Do not claim results from code that has not produced stored numerical output.- Do not copy raw participant data into an archive unless the user explicitly confirms the privacy handling.- Keep the S0-S5 audit line in the final handoff.

Frequently asked questions