Guide autonomous agents through a structured self-teaching loop to create reusable SKILL.md artifacts.
npx skills add https://github.com/jaydeland/Tony --skill teach-agent
Please help me install this Agent Skill. Skill: teach-agent Source: https://github.com/jaydeland/Tony/tree/main/.claude/skills/teach-agent Command: npx skills add https://github.com/jaydeland/Tony --skill teach-agent
Agents often encounter unfamiliar technologies, APIs, or integrations and struggle to expand capabilities without guidance.
The skill defines a self-teaching loop (research → understand → implement → document → validate) and leverages tools like WebSearch, WebFetch, and mcp__zread__search_doc to gather knowledge, understand requirements, and generate a concrete SKILL.md with frontmatter, synopsis, trigger, and implementation for reuse.
Empower an agent to initiate the teach-agent workflow when faced with an unknown tool or domain and follow the five-step loop to produce a new reusable skill.
High-intent search queries and answers about installing and using this skill.
Autonomous agents learn new capabilities by executing a structured self-teaching loop that includes research, understanding, implementation, documentation, and validation. This ensures agents can independently expand their knowledge of unknown technologies, APIs, or integrations while generating a complete and reusable SKILL.md artifact.
The structured self-teaching loop for agent self-learning is a five-step process: research, understand, implement, document, and validate. It leverages tools like WebSearch, WebFetch, and mcp__zread__search_doc to gather knowledge, understand requirements, and generate concrete skill artifacts for reuse.
You create a reusable SKILL.md artifact for an unfamiliar technology by triggering an autonomous self-learning loop when the agent encounters the unknown domain. The loop generates a new SKILL.md file containing frontmatter, a synopsis, a trigger, and implementation details, alongside supporting code and validation artifacts.
Yes, agents can autonomously research and document new integrations without manual coding by following the structured self-teaching workflow. They use research tools to gather knowledge, understand requirements, and generate a concrete SKILL.md with supporting code and documentation for reuse.
The agent self-teaching loop uses WebSearch, WebFetch, and mcp__zread__search_doc to gather knowledge and understand requirements. These tools enable the agent to autonomously research unfamiliar technologies, APIs, or integrations during the research and understanding phases of the loop.
You should initiate an autonomous self-learning workflow for an agent when it encounters unknown technologies, APIs, or integrations and must expand its capabilities. The workflow empowers the agent to research, understand, implement, document, and validate the new skill independently.
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