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Verbatim copy of the stdlib-only skillopt_sleep engine + Claude Code plugin surface (skills/hooks/commands/scripts) into engineering/skillopt-sleep/. Gives a local agent a nightly gated self-improvement cycle: read-only harvest of past Claude Code session transcripts -> mine recurring tasks -> offline replay -> held-out-gated CLAUDE.md/SKILL.md edits -> staged for explicit /skillopt-sleep adopt. Nothing live changes without that explicit step. The heavier skillopt training package (needs numpy/openai/azure-* + hand-labeled benchmarks per task) was deliberately not vendored, since it optimizes one narrow scoreable task at a time and doesn't fit this repo's broad domain-expertise skills or no-ML-in-scripts convention. Attribution preserved in plugin.json + LICENSE + README.md (MIT, Microsoft Corporation / Yifan Yang), following the same verbatim-vendor pattern already used for loop-library/. Registered as its own marketplace plugin; headline counters in README.md/CLAUDE.md/ marketplace.json trued up via scripts/derive_counters.py --check. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01TX374i2YGrjNV4Yi3AmaKS
20 lines
826 B
Python
20 lines
826 B
Python
"""SkillOpt-Sleep — nightly offline self-evolution for a local Claude agent.
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A Claude Code plugin engine that gives a user's agent a "sleep cycle":
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harvest the day's real session transcripts, mine recurring tasks, replay
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them offline, and consolidate short-term experience into long-term memory
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(CLAUDE.md) and skills (SKILL.md) behind a SkillOpt validation gate.
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Synthesizes three ideas:
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* SkillOpt — validation-gated bounded text optimization (this repo)
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* Dreams — offline memory consolidation, input never mutated
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* Sleep — short-term experience -> long-term competence, offline
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Public entry points:
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* skillopt_sleep.cli — `python -m skillopt_sleep ...`
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* skillopt_sleep.cycle.run_sleep_cycle(...)
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"""
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from __future__ import annotations
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__all__ = ["__version__"]
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__version__ = "0.2.0"
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