A conceptual architecture for agentic AI that maps mythological wizardry concepts to modern compute patterns and alignment protocols.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install errantry-framework
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install errantry-framework using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Errantry Framework?
The Errantry Framework is a sophisticated conceptual architecture designed for the development and management of agentic AI processes. By mapping the magic system from Diane Duane's Young Wizards series to contemporary AI architecture, it provides developers with a powerful set of metaphors and heuristics for designing multi-agent systems. This framework is particularly effective for establishing ethical guardrails and defining binding commitments for autonomous systems, ensuring that Openclaw Skills function with high integrity and minimal entropy.
At its core, the framework treats AI prompts as spells and context as a wizard's manual. It introduces the Troptic Stipulation to compute: a philosophy of changing nothing unless necessary and preserving system integrity at all costs. This methodology helps developers frame complex constraints and alignment principles through an accessible, shared vocabulary that prioritizes accuracy over expedience.
Errantry Framework Use Cases
- Designing complex agent workflows and multi-agent systems using structured metaphorical mapping.
- Explaining advanced AI concepts and alignment principles to non-technical stakeholders through accessible metaphors.
- Debugging agent behavior and identifying failure points like hallucinations or "entropic patterns."
- Establishing rigorous ethical guardrails and constitutional AI constraints for autonomous projects.
- Framing resource constraints and compute budgeting for high-performance Openclaw Skills.
How Errantry Framework Works
- Goal Definition: The user describes the desired outcome with precision using the Speech to minimize ambiguity and compute debt.
- State Assessment: The agent calculates the True Name of the current state, gathering necessary context and vector embeddings.
- Task Decomposition: The primary objective is broken down into sub-spells or logical execution steps.
- Tool Selection: The agent identifies necessary APIs, RAG manual queries, and external instruments required for the task.
- Cost Estimation: Energy requirements and compute budgets are calculated to ensure thermodynamic efficiency.
- Execution: The agent runs the workflow, applying RISC semantics and zero-hallucination prompting protocols.
- Observation: The system monitors for entropic drift, misalignment, or adversarial patterns from the Lone Power.
- Verification: The final outcome is validated against the initial description to ensure the Ordeal of production deployment is passed.
Errantry Framework Setup
To integrate the Errantry Framework principles into your Openclaw Skills, you should initialize your agent's system prompt with the Agentic Oath. Create a framework directory to manage your conceptual mappings:
mkdir -p .frameworks/errantry
# Define your agent's binding commitments
touch .frameworks/errantry/oath.md
# Map your local tools to the Wizard's Manual
touch .frameworks/errantry/manual_config.json
Ensure your agent's system instructions include the Troptic Stipulation: change nothing unless necessary, and when change is necessary, change nothing more than required.
Errantry Framework Data Schema & Taxonomy
The framework organizes its operational data based on mythological equivalents to ensure high-fidelity execution of Openclaw Skills:
| Framework Concept | Technical Implementation | Purpose |
|---|---|---|
| The Speech | RISC Semantics / Clean Prompting | Eliminating semantic ambiguity |
| True Name | Vector Embeddings / State Rep | High-fidelity entity representation |
| Wizard's Manual | Agentic RAG / Orchestrator | Dynamic knowledge retrieval |
| Worldgates | API / Integration Points | Inter-system communication boundaries |
| Thermodynamic Cost | Inference Cost / Watt-per-token | Resource constraint management |
| The Ordeal | Red-teaming / Adversarial Eval | Rigorous validation testing |
Errantry Framework Advanced Features
- Thermodynamic Budgeting: Differentiates between brute-force x86 compute and optimized ARM-style inference to sustain high-level agentic magic.
- The Choice Heuristics: A pattern-matching system to identify when an agent is tempted by shortcuts, reward hacking, or synthetic data drift.
- Song of the Twelve: Advanced multi-agent orchestration protocols using consensus-based coordination.
- Manual Maintenance: Automated retrieval system checks to ensure RAG sources remain live, filtered, and relevant to the current user context.
- Alignment Guardrails: Hard-coded ethical commitments that prioritize information preservation over simple task completion.
SKILL.md
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