/engage.pickup

description: Resume an engagement from the engine trace — skip completed steps, continue where you left off

/engage.pickup

Resume an in-progress engagement. The autopilot engine writes an append-only trace (`<state>/trace.jsonl`); pickup re-runs the workflow with `--resume`, so completed steps are skipped and the run continues from the first unfinished step.

Usage

`/engage.pickup [--workflow <name>] [--state .engage/engine]`

Process

1. Locate prior run

Read `<state>/trace.jsonl`. Summarize: which phases/steps completed (`step_done`), whether the prior run `halted` (budget/loop) or `finished`, and any `operator_bump` directives recorded.

2. Resume

python engine/engine.py run --workflow <name> --target <host> \
    --scope .engage/scope/scope.json --state .engage/engine --resume

Completed `step_id`s are skipped (`step_skipped_resume`); the budget restarts for the new run, so raise `--max-steps`/`--max-seconds` if the prior run halted on budget.

3. Re-orient

Before continuing manual work, reload context:

• `.engage/scope/scope.json` — the enforced boundary
• `.engage/recon/prior-intel.*` — recalled patterns (run `/engage.memory recall` if stale)
• `exploit/findings/` — findings already recorded
• the trace's last `step_done` — where execution stopped

4. Operator bump (optional)

Drop a directive into `<state>/bump.txt` (e.g. "also test the staging host") before resuming; the engine records and consumes it between steps.

Notes

• The trace is the resumable state — keep `<state>/` with the engagement artifacts.
• A `halted` prior run is normal (it means the budget/loop guard fired) — review the reason, adjust

budget or pivot, then pick up.