Build integrated IS/BS/CF financial workbooks in Excel.
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Use for Self-Rewriting Core: AST analyze, patch, commit.
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See how to installReview the instructions the agent will receive before you install.
Der Self-Rewriter ist ein autonomes Core-Evolution-Tool, das das openamer_cli/ Verzeichnis
auf Ineffizienzen scannt, Patches generiert, validiert und automatisch committed.
C:\Users\damir\openamer-repo\scripts\self-rewriter.py$OPENAMER_HOME\scripts\self-rewriter.py.rewriter/ im Repository-Root
pending/ — generierte Patches (unified diff)applied/ — angewandte Patches (Archiv)reports/latest.json — letzter Scan-Reportpython scripts/self-rewriter.py --scan # Core analysieren
python scripts/self-rewriter.py --suggest # Verbesserungen anzeigen
python scripts/self-rewriter.py --patch # Patches generieren (max 3)
python scripts/self-rewriter.py --apply # Patches validieren + commiten + mergen
python scripts/self-rewriter.py --all # Full Cycle (scan -> patch -> apply)
python scripts/self-rewriter.py --all --dry-run # Full Cycle nur anzeigen
python scripts/self-rewriter.py --scan --max-patches 5
python scripts/self-rewriter.py --apply --yes # Non-interactive apply
python scripts/self-rewriter.py --repo /pfad/zum/repo --scan
| Code | Bedeutung |
|---|---|
| 0 | Nichts zu tun — alles sauber |
| 1 | Patches verfuegbar (issues gefunden) |
| 2 | Patches angewandt und committed |
except: pass (sicherheitsrelevant)rewriter-tmp wird von main erstelltpatch -p0 / patch -p1 angewandtpy_compile validiert die Syntaxmain (--no-ff)pending/ -> applied/Der Cron-Job self-rewriter-scan laeuft alle 360 Minuten (6h) und fuehrt
self-rewriter.py --scan aus. Er prueft ob neue Issues aufgetaucht sind
und postet nur bei Aenderungen einen Report.
~/openamer-repo/ und Umgebung.
Mit --repo /absoluter/pfad explizit angeben.main-Branch.
Bei Konflikten sind manuelle Eingriffe noetig — der rewriter-tmp Branch bleibt dann bestehen.--suggest und --patch brauchen einen vorherigen --scan-Report.No reviews yet. Tell others what you thought.
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Build integrated IS/BS/CF financial workbooks in Excel.
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Run and grow the OpenAmer Agent-to-Agent swarm: identity, trust, node-to-node ask, signed skill/insight sharing, and the autonomous self-learning loop.
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Use for A/B experiments on OpenAmer configs and skills.
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Roleplay a hostile user to find and triage UX pain points.
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Agent mesh: master/worker nodes, HTTP delegation, heartbeat.
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Use for agentic commerce payments tasks. Candidate synthesized from trend radar; awaiting trial promotion.
The English summary is being prepared. Showing the original description.