Refocusing
SkillAI & modelsUse when a long-running agent may have lost the product outcome, when context was compacted, when work has crossed a major boundary, or when a fresh path-based trace is needed before the next consequential action. Not for fresh-session orientation, waking an idle seat, or checkpoints.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Refocusing skill
What this skill tells your AI
The instructions your AI receives, as published by mvschwarz/openrig in packages/daemon/assets/plugins/openrig-core/skills/refocusing/SKILL.md and read by ahel’s review.
Refocus preserves a long session's earned expertise while re-grounding it in current intent and lived context. It is not a restart, wake, or phase checkpoint.
Run the bundled trace from this skill directory instead of reconstructing the hierarchy from memory:
python3 scripts/trace-to-root.py --trees both --depth light
Use --trees topology|work|both to select context domains and --depth light|full to control how
much each node contributes. Light work traces compose intent: and name notes; full traces include
the complete node and notes bodies. The script resolves topology.root and workspace.root with
rig config get. When a current node cannot be derived, set OPENRIG_REFOCUS_TOPOLOGY_NODE or
OPENRIG_REFOCUS_WORK_NODE, or pass the matching --*-start option.
Read references/refocus.md when changing the automatic hook or its content ladder. A missing chain file is evidence: report the gap and continue; never follow pointers to invent a second parent.
Signals
- GitHub stars
- 67
- Forks
- 12
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
refocusing- Source
- github.com/mvschwarz/openrig