skill-engineerDesign, test, review, and maintain agent skills for OpenClaw systems using multi-agent iterative refinement. Orchestrates Designer, Reviewer, and Tester suba...
Install via ClawdBot CLI:
clawdbot install chunhualiao/skill-engineerGrade Good — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Potentially destructive shell commands in tool definitions
Eval (Calls external URL not in known-safe list
https://...AI Analysis
The skill definition describes a legitimate multi-agent skill development workflow with no direct evidence of malicious code, credential harvesting, or data exfiltration. The signals found (UNSAFE_SHELL, UNDOCUMENTED_EXTERNAL) are based on tool definitions and external calls not visible in the provided text fragment, requiring further context to assess actual risk.
Audited Apr 16, 2026 · audit v1.0
Generated Mar 20, 2026
A legal tech company needs to create encoded preference skills for contract review, ensuring AI agents consistently apply specific legal criteria and organizational workflows. The Skill Engineer orchestrates subagents to design, test, and refine these skills, maintaining fidelity to established legal processes and compliance standards.
A marketing agency uses capability uplift skills to generate branded content like PDF reports and social media posts, injecting specialized formatting and analysis techniques. The Skill Engineer monitors model improvements to retire skills as base AI capabilities catch up, optimizing resource allocation and ensuring output quality.
A healthcare organization develops encoded preference skills for generating weekly patient reports from specific data sources, sequencing operations according to strict medical protocols. The Skill Engineer ensures these skills faithfully reproduce organizational workflows, with testing focused on process fidelity rather than model improvisation.
A financial services firm employs the Skill Engineer to audit and refactor existing skills for risk assessment and NDA review, using multi-agent iterative refinement. This ensures skills remain up-to-date with regulatory changes and organizational preferences, leveraging deepwiki and vector memory for accurate API and historical context.
A tech startup uses the Skill Engineer to design and test new skills for their OpenClaw agent kit, focusing on capability uplift for complex tasks like specialized data analysis. The multi-agent workflow enforces quality gates through independent subagents, preventing weak skills from degrading overall system performance.
Offer the Skill Engineer as a cloud-based service where businesses can design, test, and maintain agent skills through a subscription model. Revenue comes from tiered pricing based on skill complexity, usage volume, and access to advanced features like automated testing and integration with OpenClaw systems.
Provide expert consulting services to organizations needing tailored skill development, using the Skill Engineer to orchestrate multi-agent workflows for specific use cases like compliance or content generation. Revenue is generated through project-based fees, retainer agreements, and ongoing maintenance contracts.
Operate a marketplace where users can purchase or subscribe to pre-designed skills developed with the Skill Engineer, categorized by industry and function. Revenue streams include transaction fees on sales, subscription access to premium skill libraries, and revenue sharing with skill developers.
💬 Integration Tip
Always verify deepwiki and vector memory dependencies before starting skill work to ensure accurate API grounding and access to historical context, as missing these can lead to blind development and inefficiencies.
Scored Apr 19, 2026
Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.
Orchestrate multi-agent teams with defined roles, task lifecycles, handoff protocols, and review workflows. Use when: (1) Setting up a team of 2+ agents with different specializations, (2) Defining task routing and lifecycle (inbox → spec → build → review → done), (3) Creating handoff protocols between agents, (4) Establishing review and quality gates, (5) Managing async communication and artifact sharing between agents.
A unified OpenClaw skill that merges self-improvement and proactivity: learn from corrections, maintain active state, recover context fast, and keep work mov...
Meta-skill for AI agent self-improvement. Analyzes runtime logs to detect error patterns, regressions, and inefficiencies, then generates structured improvem...
Automatically assess task complexity and adjust reasoning level. Triggers on every user message to evaluate whether extended thinking (reasoning mode) would improve response quality. Use this as a pre-processing step before answering complex questions.
AI Agent 設定同優化助手 - Prompt Engineering、Task Decomposition、Agent Loop設計