Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub · AI
Decision-Grade Reasoning (DGR)
Audit-ready decision artifacts for LLM outputs — assumptions, risks, recommendation, and review gating (schema-valid JSON).
skill openclawclawhub Free
Audit-ready decision artifacts for LLM outputs — assumptions, risks, recommendation, and review gating (schema-valid JSON).
⬇ 0 downloads ★ 0 stars Unverified but indexed
Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- field_guide.md, prompt.md, schema.json, SKILL.md, examples/access_request.md, examples/incident_triage.md
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.4
Provenance
- Publisher
- sapenov
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
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
Ask your question — Provide a decision request or problem context Pick mode: dgr_min | dgr_full | dgr_strict 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
ModeSpeedDetail LevelClarificationsReview RequiredUse Casedgr_minFastestMinimal compliant outputOnly critical gapsRisk-basedQuick decisions, low stakesdgr_fullModerateFuller decomposition + alternativesMore proactiveBalancedStandard decision supportdgr_strictSlowerConservative analysisMore questioningDefault on ambiguityHigh-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
Provide a decision request. Choose a mode (dgr_min default). The skill returns a JSON artifact suitable for review and storage.
Changelog
1.0.4 — Remove redundant CLAWHUB_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 ClawHub 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.
Category context
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
5 Docs1 Config
- SKILL.md
- examples/access_request.md
- examples/incident_triage.md
- field_guide.md
- prompt.md
- schema.json