A local-first control layer that keeps a single canonical skill library for Claude Code, OpenAI Codex CLI and Antigravity (Gemini) on the same machine — audited, planned, reversible.
Python · no third-party dependencies · Windows / macOS / Linux
Each agent keeps its own skills folder and its own memory. Skills get copied three or four times, drift apart, and what one agent learns never reaches the others.
Same skill, three folders. Hardcoded paths make identical files look different; real edits land in only one place.
Edit once. Each agent gets a tracked copy with its own paths filled in, and every copy is hash-verified.
One-machine case study: an audit of a single developer workstation. These are not industry statistics — run the audit on your own machine to get yours.
node_modules. Actual instructions and source: ~3,200 files (~55–75 MB).
Three Python scripts: audit_skills.py, the omniagent.py Skill Manager, and the experimental path_adapter.py.
audit_skills.py --output .local/reports
omniagent.py discover
omniagent.py plan --source … --target …
omniagent.py adopt … --yes
omniagent.py apply … --yes --skip-blocked
omniagent.py rollback --transaction ID --yes
.codex/skills/.system runtime is left untouched.
Audit, discover, plan. Review the table, then decide whether to apply. Test against disposable --target directories first.
Three layers. Only the first one ships today; the others wait until it’s solid.