~/.neuralcleave/skills/<name>/skill.py.
Anatomy of a skill
A skill module contains either plain functions, auto-wrapped as tools, or an explicitPlugin subclass for full control over metadata and lifecycle hooks.
subprocess, ctypes, winreg, msvcrt, pty, tty, termios, fcntl) are rejected at write/proposal time.
Two ways a skill gets written
1. You write it — immediate, trusted
2. The agent writes it — proposed for review
When the agent itself calls thewrite_skill tool during a conversation, the code is validated and queued as a pending proposal — not written to disk or loaded. A human decides:
Managing installed skills
skills write with the same name — that clears the quarantine flag.
Multi-step tool chains
Skills participate the same way any tool does in multi-step tool chains — the pipeline calls a tool, feeds the result back to the LLM, which can call another tool, up tomax_tool_steps (default 5) per turn.
Example conversation
neuralcleave skills review approve a1b2c3d4) writes the file, loads it, and makes celsius_to_fahrenheit callable in the very next turn.
Skills gallery
~/.neuralcleave/skills/ can also be seeded from the bundled example skills — see Skills Gallery for the full list (calendar, GitHub, Jira, Linear, Notion, weather, and more).