DGR — Decision‑Grade Reasoning (Governance Protocol)

Purpose: produce an auditable, machine‑validated decision record for review and storage.

Slug: dgr · Version: 1.0.4 · Modes: dgr_min / dgr_full / dgr_strict · Output: schema-valid JSON

What this skill does

DGR is a reasoning governance protocol that produces a machine‑validated, auditable artifact describing:

• the decision context,
• explicit assumptions and risks,
• a recommendation with rationale,
• and a consistency check.

This skill is designed for high‑stakes or review‑required decisions where you want traceability and structured review.

How to use

1. Ask your question — Provide a decision request or problem context
2. Pick mode: dgr_min | dgr_full | dgr_strict
3. Store JSON artifact in ticket / incident / audit log

What this skill is NOT (non‑claims)

This skill does NOT guarantee:

• correctness, optimality, or truth,
• elimination of hallucinations,
• legal/medical/financial advice suitability,
• or regulatory compliance by itself.

DGR improves process quality (clarity, traceability, reviewability) — not outcome certainty.

When to use

Use when you need:

• an auditable record of reasoning,
• explicit assumptions/risks surfaced,
• reviewer‑friendly structure,
• a consistent output format across tasks and models.

Inputs

• A user request/question (free text).
• Optional: context identifiers (ticket ID, policy name), and desired mode: dgr_min, dgr_full, or dgr_strict.

Mode Behavior

Outputs

A single JSON artifact matching schema.json.

Minimum acceptance criteria (see schema.json):

• at least 1 assumption
• at least 1 risk
• recommendation present
• consistency_check present

Safety / governance boundaries

• Always ask for clarification if key decision inputs are missing.
• If the decision is high‑risk, escalate via recommendation.review_required = true.
• If uncertainty is high, explicitly state uncertainty and limit scope.
• Do not fabricate sources or cite documents you did not see.

Files in this skill

• prompt.md — operational instructions
• schema.json — output schema (stub aligned to DGR spec)
• examples/*.md — example inputs and outputs
• field_guide.md — how to interpret DGR artifact fields