Finding
IronClaw (github.com/nearai/ironclaw) — AI agent that generates tool/skill definitions from natural language descriptions at runtime, without manually writing SKILL.md files.
The pattern: user describes a capability → agent generates a structured skill definition (YAML frontmatter + body) → skill is registered in the registry and immediately available.
Applicability to Zeph
Zeph has skill-creator bundled skill that guides users through SKILL.md authoring. IronClaw's pattern would automate this: given a natural language description, the agent generates a complete SKILL.md, validates it, and registers it.
Proposed design:
/skill create <description> command: sends description to LLM with SKILL.md schema as few-shot template
- Agent generates SKILL.md with correct frontmatter (name, description, triggers, category)
- Validation: run
skill-audit on generated skill before registration
- User reviews and approves before activation
Connection to self-learning: this complements the existing skill evolution system — users could create skills from scratch via NL, then improve them via the [skills.learning] feedback loop.
Source
- github.com/nearai/ironclaw — IronClaw agent with dynamic skill generation
- Zeph skill-creator:
skills/skill-creator/SKILL.md
Finding
IronClaw (github.com/nearai/ironclaw) — AI agent that generates tool/skill definitions from natural language descriptions at runtime, without manually writing SKILL.md files.
The pattern: user describes a capability → agent generates a structured skill definition (YAML frontmatter + body) → skill is registered in the registry and immediately available.
Applicability to Zeph
Zeph has
skill-creatorbundled skill that guides users through SKILL.md authoring. IronClaw's pattern would automate this: given a natural language description, the agent generates a complete SKILL.md, validates it, and registers it.Proposed design:
/skill create <description>command: sends description to LLM with SKILL.md schema as few-shot templateskill-auditon generated skill before registrationConnection to self-learning: this complements the existing skill evolution system — users could create skills from scratch via NL, then improve them via the
[skills.learning]feedback loop.Source
skills/skill-creator/SKILL.md