Simple field check

Run isolated E2E tests in devcontainer. $ARGUMENTS specifies runbook name or "new".

Before acting, run python3 scripts/ai-context.py testing. The topic is the source of truth for isolation, runbook quality and reporting rules; this skill retains the execution flow and mdproof recipes.

Flow

Phase 0: Environment Check

1. Confirm devcontainer is running and get container ID:

   CONTAINER=$(docker compose -f .devcontainer/docker-compose.yml ps -q skillshare-devcontainer)
   

   • If empty → prompt user: docker compose -f .devcontainer/docker-compose.yml up -d
   • Ensure CONTAINER is set for all subsequent docker exec calls.

2. Confirm Linux binary is available:

   docker exec $CONTAINER bash -c \
     '/workspace/.devcontainer/ensure-skillshare-linux-binary.sh && ss version'
   

3. Confirm mdproof is installed:

   docker exec $CONTAINER /workspace/.devcontainer/ensure-mdproof.sh
   

   This auto-installs from GitHub release, or falls back to /workspace/bin/mdproof (local dev binary).

4. Check for lessons learned from previous runs:

   test -f /workspace/.mdproof/lessons-learned.md && cat /workspace/.mdproof/lessons-learned.md
   

   If the file exists, read it before writing or debugging runbooks — it contains known gotchas and assertion patterns.

Phase 1: Detect Scope

1. Preview all available runbooks via the container:

   docker exec $CONTAINER mdproof --dry-run --report json /workspace/ai_docs/tests/
   

   This returns JSON with every runbook's steps, commands, and expected assertions — no manual markdown parsing needed. Use this to understand what each runbook covers.