Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub Β· AI
Metaskill
Teaches AI agents how to learn better by enforcing deep correction, transfer learning, and proactive pattern recognition. Use when an error occurs and needs...
skill openclawclawhub Free
Teaches AI agents how to learn better by enforcing deep correction, transfer learning, and proactive pattern recognition. Use when an error occurs and needs...
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
- SKILL.md, config.yaml, scripts/deep-correct.sh, scripts/eval.sh, scripts/llm_extract.py, scripts/llm_provider.py
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
- 1.3.0
Provenance
- Publisher
- fahrulalwan
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
3 Core Components
Deep Self-Correction (deep-correct.sh) β 3-level breakdown on errors: Surface: What specifically failed Principle: The underlying rule/constraint violated Habit: Concrete behavioral change to prevent recurrence Transfer Learning (transfer-check.sh) β Before a task, search past learnings for analogous patterns. Maps domains (e.g., "auth" β "security") to prevent siloed learning. Proactive Pattern Recognition (success-capture.sh) β Log what worked and why, building a repository of successful patterns.
Usage
# When an error occurs bash skills/metaskill/scripts/deep-correct.sh "description of the error" # Before starting a complex task bash skills/metaskill/scripts/transfer-check.sh "description of the new task" # After successful execution bash skills/metaskill/scripts/success-capture.sh "what worked" "why it worked" # Monthly health eval bash skills/metaskill/scripts/eval.sh --save
Configuration (LLM Provider)
Metaskill uses two provider tiers β fast (extraction) and deep (transfer/eval). Edit config.yaml to match your setup: # config.yaml providers: fast: anthropic # change to: openai | ollama | gemini deep: anthropic ProviderEnv VarNotesanthropicANTHROPIC_API_KEYDefaultopenaiOPENAI_API_KEYollama(none needed)Local, freegeminiGOOGLE_API_KEY Ollama example (fully local, no API key): providers: fast: ollama deep: ollama models: ollama: fast: llama3.2 deep: llama3.1:70b If no provider is available, metaskill falls back to manual/heuristic mode (still works, but less precise extraction).
Integration with Self-Improving-Agent
Writes to skills/self-improving-agent/.learnings/ if present, otherwise falls back to its own .learnings/ directory. No extra setup needed.
AGENTS.md Wiring (Mandatory)
Add to pre-task checklist: Run transfer-check.sh before any major task Run deep-correct.sh immediately after any error (not just LEARNINGS.md append) Run success-capture.sh after complex task completes successfully
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
4 Scripts1 Docs1 Config
- SKILL.md
- scripts/deep-correct.sh
- scripts/eval.sh
- scripts/llm_extract.py
- scripts/llm_provider.py
- config.yaml