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Cx Agent Studio
by
Yash Kavaiya
· GitHub ↗
· v1.0.0
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Install in OpenClaw
/install cx-agent-studio
Description
Guide and instructions for using Google Customer Experience Agent Studio (CX Agent Studio). Use when creating conversational agents, writing or structuring i...
README (SKILL.md)
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.
Quick Actions
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}
- Variables:
- 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. Readreferences/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
Usage Guidance
This skill is a documentation-only guide for building CX Agent Studio agents and appears internally consistent. It does not ask for credentials or install code. However, the guide encourages adding Python tools and callbacks — any Python tool or connector you attach to agents can execute arbitrary code and call external services, so: (1) review and vet any Python code or third-party connectors before enabling them, (2) avoid uploading sensitive documents to RAG/data stores you don't control, (3) enable guardrails, logging, and data-redaction settings if you use third-party integrations, and (4) audit permissions for any connectors (e.g., Salesforce, Google APIs) you configure. If you want a higher assurance, ask the publisher for provenance (homepage, owner identity) or request an explicit list of required connectors and example tool code to review before installation.
Capability Analysis
Type: OpenClaw Skill
Name: cx-agent-studio
Version: 1.0.0
The skill bundle, primarily documentation, describes a platform (CX Agent Studio) that allows for the execution of arbitrary Python code as 'tools' and 'callbacks' (`references/tools.md`, `references/callbacks.md`). These Python hooks can inspect and modify model requests/responses, tool arguments/results, and the agent's internal state (`context.state`), offering extensive control over the agent's behavior. While presented as legitimate development features, these capabilities represent a significant attack surface (e.g., potential for RCE, data manipulation, or exfiltration) if not properly secured or if malicious code is introduced by a developer or via prompt injection. The documentation itself does not contain malicious code or instructions for the OpenClaw agent to perform harmful actions, but it highlights inherently risky capabilities within the described platform.
Capability Assessment
Purpose & Capability
The name/description (CX Agent Studio guidance) matches the content: design notes, instruction syntax, callbacks, tools, and evaluation guidance. There are no unrelated requirements (no env vars, binaries, or installs) that would be inconsistent with the stated purpose.
Instruction Scope
SKILL.md and referenced docs stay within builder guidance. They explicitly recommend creating Python tools and callbacks to wrap external APIs and manipulate state — this is expected for an agent-builder but means any code you or your team add (Python tools/callbacks) can run arbitrary logic and access data. The skill itself contains no executable code.
Install Mechanism
No install spec and no code files that would be written to disk. Instruction-only skills are lowest-risk from an installation perspective.
Credentials
No required environment variables, credentials, or config paths are declared. The guide discusses integrating connectors and tools in general terms but does not request secrets itself.
Persistence & Privilege
Skill flags are default (always:false, agent-invocable allowed). It does not request permanent presence or modify other skills or system settings. Autonomous invocation is allowed by platform default and not itself a reason to distrust this instruction-only skill.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install cx-agent-studio - After installation, invoke the skill by name or use
/cx-agent-studio - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release of cx-agent-studio.
- Provides guides and instructions for using Google Customer Experience Agent Studio.
- Covers AI-augmented agent building, bi-directional voice streaming, and asynchronous tool integration.
- Includes syntax and best practices for agent instructions and XML formatting.
- Explains connecting tools, using callbacks, and establishing guardrails for safety.
- Details methods for agent evaluation using scenario and golden test cases.
Metadata
Frequently Asked Questions
What is 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... It is an AI Agent Skill for Claude Code / OpenClaw, with 409 downloads so far.
How do I install Cx Agent Studio?
Run "/install cx-agent-studio" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Cx Agent Studio free?
Yes, Cx Agent Studio is completely free (open-source). You can download, install and use it at no cost.
Which platforms does Cx Agent Studio support?
Cx Agent Studio is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Cx Agent Studio?
It is built and maintained by Yash Kavaiya (@yash-kavaiya); the current version is v1.0.0.
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