Getting started
The Open .skill Protocol is agent-first. Install the reference CLI once, then paste a prompt to your AI. You review and approve; the agent runs the tooling.
npm i -g skillerrNode ≥ 20. Site: skillerr.com.
Implementers wiring a product: start from Protocol and the @skillerr/* libraries — the CLI is the reference surface, not the only path.
Talk to your AI
The prompt below is copy-paste for your coding agent's chat — it installs the CLI if needed, then packages this conversation into a .skill file: a sealed, typed package (not a chat export) that any conforming host can later inspect, hand off, or run. "Journey" means the redacted record of what you and the agent did; "checkpoint" means a partial, in-progress save; "release-complete" means every required field is filled in, not just "looks done."
Create a skill from this chat
Run these exact commands in your terminal, in order:
1. npm i -g skillerr (skip if `skill --version` already works)
2. export SKILL_HOST=cursor (replace "cursor" with your actual tool name —
claude-code, codex, ollama, etc.)
Then, from this conversation, create a portable .skill: redacted journey, exact
sections I approved (secrets only as {{refs}}), then either checkpoint for
handoff or compile --approve --mint when release-complete. Do not invent filler.
Show me status and the output path.Inspect before you trust or run
I have a file at ./file.skill. Inspect TrustView (digests, seals) without executing.
Validate integrity, then dry-run. Summarize what it does and any trust warnings.
Do not execute for real unless I explicitly ask.Extract multiple skills from a journey
Using skillerr, run agent-guide then extract from ./journey.json into ./extraction.
For each candidate I select, open its own workspace, fill missing contract fields,
and only compile a release when complete — otherwise checkpoint. Prefer exact text.Load a continuity handoff
Load ./handoff.skill as continuity context. Summarize intent, scrubbed journey,
open gaps, and pinned knowledge. Resume the work; do not mint a fake release.Hand off mid-work
Checkpoint the current .skill workspace as a continuity draft (partial OK).
Tell me the output path and what the next agent should load.Full create path: Create a skill · Have a SKILL.md already: Convert a SKILL.md · Measure quality: Evaluate & score · Ingest path: Ingest a skill · Agent rules: Agents
What your agent will do
Commands are what the agent runs — not a human homework list.
| Goal | What the agent runs |
|---|---|
| Create workspace | skill init → journey → propose → status |
| Upgrade a SKILL.md | skill ingest <path> → skill load <file> --into <dir> → release |
| Mid-work handoff | skill checkpoint |
| Release when complete | skill compile -m "…" --approve --mint |
| Public provenance URL | skill publish <file.skill> (auto-keys, no login) |
| Trust before run | skill inspect --trust → validate → run (dry-run) |
| Resume handoff (read-only) | skill load ./file.skill |
Creating requires a declared agent host:
export SKILL_HOST=cursor # ollama | lmstudio | claude | codex | …Prefer SKILL_AGENT_INVOCATION=1. Host / model fields are self-reported provenance, not cryptographic proof of authorship.
Continuity vs release (30 seconds)
| Continuity draft | Release skill | |
|---|---|---|
| Purpose | AI↔AI (or host↔host) work handoff | Reusable sealed procedure |
| Incomplete? | Allowed (lists gaps) | compile_refused |
| Mint? | No | Yes (when complete + approved) |
Local / offline agents
Same create / ingest contract. Ask your agent to set local provenance, for example:
export SKILL_HOST=ollama
export SKILL_PROVIDER=ollama
export SKILL_MODEL=llama3.2
export SKILL_DEPLOYMENT=local
export SKILL_ENDPOINT=http://127.0.0.1:11434/v1