Skill: abeltennyson/abe-dgr (version 1.0.0)

--- name: dgr description: Audit-ready decision artifacts for LLM outputs — assumptions, risks, recommendation, and review gating (schema-valid JSON). homepage: https://www.heybossai.com/skills/dgr metadata: clawdbot: emoji: "🧭" category: "reasoning" --- # 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 | Mode | Speed | Detail Level | Clarifications | Review Required | Use Case | |------|-------|--------------|---------------|----------------|----------| | `dgr_min` | Fastest | Minimal compliant output | Only critical gaps | Risk-based | Quick decisions, low stakes | | `dgr_full` | Moderate | Fuller decomposition + alternatives | More proactive | Balanced | Standard decision support | | `dgr_strict` | Slower | Conservative analysis | More questioning | Default on ambiguity | High-stakes, uncertain contexts | ## 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 ## Quick start 1) Provide a decision request. 2) Choose a mode (`dgr_min` default). 3) The skill returns a JSON artifact suitable for review and storage. ## Changelog **1.0.4** — Remove redundant SKILLBOSS_SUMMARY.md; summary now sourced from SKILL.md front-matter. **1.0.3** — Tighten front-matter description for better conversion, add reasoning category, compress identity block for faster scanning. **1.0.2** — Add SkillBoss front-matter metadata with emoji and homepage for improved discovery and presentation. **1.0.0** — Initial public release of DGR skill bundle with auditable decision reasoning framework, governance protocols, and structured output format. > Note: This is an **opt‑in** reasoning mode. It is meant to be used alongside human decision‑making, not as a replacement.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)