Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub Β· AI
Agent Stability Framework
Provides a framework to prevent agent drift, catch faults, and maintain consistent on-character behavior across sessions and models.
skill openclawclawhub Free
Provides a framework to prevent agent drift, catch faults, and maintain consistent on-character behavior across sessions and models.
β¬ 0 downloads β
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
- AGENT_STABILITY_FRAMEWORK.md, BASELINE_EXAMPLES_TEMPLATE.md, DRIFT_LOG_TEMPLATE.md, FAULT_LOG_TEMPLATE.md, GUMROAD_DESCRIPTION.md, SKILL.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
- 1.0.0
Provenance
- Publisher
- donovanpankratz-del
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
Agent Stability Framework (ASF)
Drift Prevention Β· Fault Catching Β· Soul Alignment Keep your AI agent stable, on-character, and self-correcting across sessions and over time.
What This Solves
Three things kill agent reliability: Drift β Agent gradually reverts to generic training defaults, losing personality Faults β Agent produces broken output, hallucinates, contradicts itself, or fails silently Soul misalignment β Agent technically works but doesn't feel right β lost its essence ASF addresses all three with one integrated system.
What You Get
Complete framework documentation (AGENT_STABILITY_FRAMEWORK.md) File templates (SOUL.md, BASELINE_EXAMPLES.md, logs) System prompt additions ready to paste Detection checklists and scoring system Works on all models: Claude, GPT, Grok, Gemini, Llama, Mistral
Quick Start
Copy all files to your agent's workspace Fill out SOUL.md (who your agent IS) Create BASELINE_EXAMPLES.md (10+ correct responses) Add standing orders + pre-send gate to system prompt Run first audit after 24 hours Setup time: 45-90 minutes Daily maintenance: 5 minutes Tested on: 8+ models across all capability tiers
Layer 1: Drift Prevention
Standing orders (binary rules) Pre-send gate (delete triggers) Intensifier detection Periodic resets
Layer 2: Fault Catching
7 fault categories tracked Self-check rules before actions Fault log + recovery protocol Prevents hallucinations, contradictions, silent failures
Layer 3: Soul Alignment
Catches "technically correct but off-character" responses Soul alignment test Recovery protocol User perception as final sensor
Files Included
AGENT_STABILITY_FRAMEWORK.md β Complete framework (13KB) SOUL_TEMPLATE.md β Identity template BASELINE_EXAMPLES_TEMPLATE.md β Response examples template DRIFT_LOG_TEMPLATE.md β Drift tracking FAULT_LOG_TEMPLATE.md β Fault tracking STABILITY_LOG_TEMPLATE.md β Audit scores
Use Cases
Personal AI assistants that need consistent personality Trading bots that must not hallucinate data Content generation agents that need stable tone Customer service bots that require reliable responses Research assistants that must maintain accuracy Any agent running 24/7 or across many sessions
Why It Works
Binary rules beat judgment calls β "NEVER do X" works consistently Examples anchor identity β Baseline responses are the north star Three failure modes require three defenses β Drift, faults, and soul issues are different Self-correction leverages LLM capabilities β AIs can audit themselves with specific rules Logging creates memory β Patterns become standing orders
Requirements
OpenClaw workspace Any LLM (works across all tested models) 30-90 min setup time Willingness to document your agent's identity
Credits
Developed by Shadow Rose. Battle-tested over 130+ message sessions on Opus. Extended based on community feedback. Published 2026-02-20.
License
MIT β Use freely, modify as needed, credit appreciated but not required.
β οΈ Disclaimer
This software is provided "AS IS", without warranty of any kind, express or implied. USE AT YOUR OWN RISK. The author(s) are NOT liable for any damages, losses, or consequences arising from the use or misuse of this software β including but not limited to financial loss, data loss, security breaches, business interruption, or any indirect/consequential damages. This software does NOT constitute financial, legal, trading, or professional advice. Users are solely responsible for evaluating whether this software is suitable for their use case, environment, and risk tolerance. No guarantee is made regarding accuracy, reliability, completeness, or fitness for any particular purpose. The author(s) are not responsible for how third parties use, modify, or distribute this software after purchase. By downloading, installing, or using this software, you acknowledge that you have read this disclaimer and agree to use the software entirely at your own risk.
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
6 Docs
- SKILL.md
- AGENT_STABILITY_FRAMEWORK.md
- BASELINE_EXAMPLES_TEMPLATE.md
- DRIFT_LOG_TEMPLATE.md
- FAULT_LOG_TEMPLATE.md
- GUMROAD_DESCRIPTION.md