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Install in OpenClaw
/install robust-agent-design
Description
Apply robust Agent design patterns for building fault-tolerant, state-driven automation systems. Use when designing or refactoring systems that require high...
Usage Guidance
This skill appears to be legitimate instructional material with working Python templates. Before using in production: (1) review and test the provided Python code yourself; (2) configure state persistence (avoid leaving sensitive state on disk — use encrypted storage or memory if appropriate); (3) remove or control any simulated randomness and test-only failure rates (e.g., random failures in examples); (4) audit any compensation actions you add to ensure they don't perform unsafe side effects (external calls, destructive operations); and (5) run examples in an isolated environment until you are satisfied with behavior.
Capability Analysis
Type: OpenClaw Skill
Name: robust-agent-design
Version: 1.0.0
The skill bundle provides a comprehensive framework and educational templates for designing robust, fault-tolerant AI agents using state-driven patterns and compensation transactions. The included Python code (agent_template.py and compensation_example.py) and documentation (SKILL.md) are well-structured, follow standard software engineering practices, and contain no evidence of malicious behavior, data exfiltration, or unauthorized execution.
Capability Tags
Capability Assessment
Purpose & Capability
The name/description (robust agent design, fault tolerance, compensation patterns) matches the SKILL.md content and the included Python template/example files. The code and prose focus on state-driven agents, retries, compensation transactions, and persistence — all coherent with the stated purpose.
Instruction Scope
SKILL.md is a design/instruction document and does not instruct the agent to read unrelated host files, call external endpoints, or collect hidden data. The included code examples implement state persistence and compensation logic but do not send data to external services (EmailService/NotificationService are simulated in-memory).
Install Mechanism
There is no install specification; this is instruction-only with example code files. No packages are downloaded or executed automatically as part of installation.
Credentials
The skill requests no environment variables or credentials (good). One design choice to note: the Python template defaults to file-based state persistence and writes a state file under /tmp/agent_<uuid>.state. Persisted state contains metadata and an input checksum (not raw input), but you should consider whether file persistence is acceptable for your environment and whether state files could expose sensitive metadata.
Persistence & Privilege
The skill does not request elevated privileges and always:false. It does write local state files by default (under /tmp) and maintains in-memory logs in examples. This is expected for agent state persistence, but you may want to configure state_persistence to a secure location or memory-only mode before using in production.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install robust-agent-design - After installation, invoke the skill by name or use
/robust-agent-design - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release: robust Agent design patterns for fault-tolerant automation systems
Metadata
Frequently Asked Questions
What is Robust Agent Design?
Apply robust Agent design patterns for building fault-tolerant, state-driven automation systems. Use when designing or refactoring systems that require high... It is an AI Agent Skill for Claude Code / OpenClaw, with 105 downloads so far.
How do I install Robust Agent Design?
Run "/install robust-agent-design" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Robust Agent Design free?
Yes, Robust Agent Design is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Robust Agent Design support?
Robust Agent Design is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Robust Agent Design?
It is built and maintained by bhbb2000 (@bhbb2000); the current version is v1.0.0.
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