Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub · AI
AI Agent Helper
AI Agent 設定同優化助手 - Prompt Engineering、Task Decomposition、Agent Loop設計
skill openclawclawhub Free
AI Agent 設定同優化助手 - Prompt Engineering、Task Decomposition、Agent Loop設計
⬇ 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
- 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
- Katrina-jpg
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
AI Agent Helper
幫你setup同優化AI Agents既技能。
功能
📝 Prompt Engineering - 整高質量system prompts 🔄 Task Decomposition - 將複雜任務拆解 ⚙️ Agent Loop設計 - ReAct/ReAct/Chain-of-Thought 🎯 Tool Selection - 最佳化agent既tool usage
使用場景
"帮我整prompt" / "點樣set AI agent" / "優化agent response"
技術
System Prompt優化 Few-shot examples Output parsing (JSON/structured) Error handling patterns Token優化
範例
# Good prompt structure system = """你係{role}。 目標：{goal} 限制：{constraints} Output格式：{format}"""
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
1 Docs
- SKILL.md