pg-workflow

name	pg-workflow
description	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 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:

1. ../../references/workflow-contract.md
2. ../../references/archive-contract.md
3. ../../references/intake-checklist.md when starting a new run
4. ../../references/supervision-gates.md before approval
5. ../../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

1. 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 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.