Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub ยท Developer Tools
Cx Agent Studio
Guide and instructions for using Google Customer Experience Agent Studio (CX Agent Studio). Use when creating conversational agents, writing or structuring i...
skill openclawclawhub Free
Guide and instructions for using Google Customer Experience Agent Studio (CX Agent Studio). Use when creating conversational agents, writing or structuring i...
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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
- references/agents.md, references/best-practices.md, references/callbacks.md, references/evaluation.md, references/flows.md, references/guardrails.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
- Yash-Kavaiya
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
CX Agent Studio
Customer Experience Agent Studio (CX Agent Studio) is a minimal code conversational agent builder built on the Agent Development Kit (ADK), representing the evolution of Dialogflow CX.
Core Capabilities
AI-Augmented Building: Generate agents using Gemini with a 1-2 sentence goal. Bi-directional Streaming: Ultra-low latency voice interactions. Asynchronous Tool Calling: Maintains natural conversation flow during backend calls.
1. Generating an Agent with AI
To generate an agent automatically: Provide a clear 1-2 sentence goal. Optionally provide up to 5 knowledge documents (under 8MB total) like FAQs or tool catalogs. Note: Only works for the root agent and empty agents.
2. Architecture & Design
Agents: Root (steering) agents orchestrate tasks and delegate to sub-agents. Read references/agents.md. Flows: Integrate legacy Dialogflow CX flows for deterministic business logic (auth, sequential validation). Read references/flows.md. Variables: Store and retrieve runtime conversation data. Read references/variables.md.
3. Writing Agent Instructions
Agent instructions guide the model's behavior, persona, and tool/agent usage. Syntax References: Variables: {variable_name} Tools: {@TOOL: tool_name} Sub-Agents: {@AGENT: Agent Name} For complex instructions or recommended XML formatting, read: references/instructions.md Best Practices: Start simple, use specific/structured instructions, flat parameter structures. Read references/best-practices.md.
4. Tools & Callbacks
Tools: Connect your agent to external systems. Wrap complex APIs in Python tools to reduce context overhead. Read references/tools.md. Callbacks: Advanced Python hooks (before_agent_callback, after_model_callback, etc.) to control execution, validate states, or inject custom JSON payloads. Read references/callbacks.md.
5. Guardrails & Safety
Guardrails: Protect against prompt attacks and enforce Responsible AI policies. Read references/guardrails.md.
6. Agent Evaluation
Evaluation ensures agent performance via automated test cases. Scenario Test Cases: AI-generated simulated user conversations based on a user goal. Golden Test Cases: Specific, ideal conversation paths for regression testing. For detailed evaluation metrics, personas, and test case creation, read: references/evaluation.md
Category context
Code helpers, APIs, CLIs, browser automation, testing, and developer operations.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
6 Docs
- references/agents.md
- references/best-practices.md
- references/callbacks.md
- references/evaluation.md
- references/flows.md
- references/guardrails.md