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Updates the SkillOpt-Sleep plugin on top of the current main. User-facing and engine improvements since the initial drop: * Command renamed /sleep -> /skillopt-sleep across Claude Code + Codex shells; refreshed plugin READMEs and install scripts. * Built-in scheduling (skillopt_sleep/scheduler.py + __main__): schedule / unschedule the nightly cycle without external cron wiring. * Backend robustness: bounded retry with backoff (no more silent empty-string on transient 429/timeout), content-filter-safe rollout prompt, an output-contract guardrail that rejects edits violating the task's required format, and a per-sample cache key so repeated dream rollouts are independent samples (fixes degenerate single-sample reflection). * consolidate / rollout / replay: parallel multi-rollout dreaming, gate-mode controls, TaskRecord.system framing field. Scope: this commit ships only the plugin engine + shells. Research/benchmark harnesses and their data are intentionally not included; the public package has no dependency on them (the one research-evaluator import is now guarded). Marked as an early preview in the README; we'll keep iterating. 99/99 unit tests pass. Co-Authored-By: Claude Opus 4 <noreply@anthropic.com>
60 lines
2.4 KiB
Markdown
60 lines
2.4 KiB
Markdown
# SkillOpt-Sleep — Codex integration
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Give your **Codex** agent a nightly **sleep cycle**: it reviews past sessions
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offline, replays your recurring tasks on your own Codex budget, and consolidates
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what it learns into validated memory + skills behind a held-out gate. Same engine
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as the Claude Code plugin (`skillopt_sleep`), wrapped for Codex.
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> **Verified on Codex:** on the public
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> [gbrain-evals](https://github.com/garrytan/gbrain-evals) `skillopt-v1`
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> benchmark, a deliberately deficient skill goes **0.00 → 1.00** on a held-out
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> set with the Codex backend (incl. the tool-use seed via a real tool loop).
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> See [`../../docs/sleep/FINAL_REPORT.md`](../../docs/sleep/FINAL_REPORT.md).
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## What Codex supports (and what we use)
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Codex (`@openai/codex`) extends via **`AGENTS.md`** instructions, **skills** at
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`~/.agents/skills/<name>/SKILL.md`, and **custom prompts** at
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`~/.codex/prompts/<name>.md` (invoked as `/<name>`). This integration ships all
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three, plus a shared runner.
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## Install
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```bash
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git clone <repo-url> SkillOpt-Sleep
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cd SkillOpt-Sleep
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bash plugins/codex/install.sh # installs the /skillopt-sleep prompt + skill
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export SKILLOPT_SLEEP_REPO="$(pwd)" # so the runner is found from anywhere
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```
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Requires Python ≥ 3.10 and the `codex` CLI on PATH.
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## Use
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```text
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/skillopt-sleep status # what's happened
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/skillopt-sleep dry-run # safe preview, stages nothing
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/skillopt-sleep run # full cycle, stages a reviewed proposal (no live edits)
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/skillopt-sleep adopt # apply the staged proposal (with backup)
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```
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Or call the engine directly:
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```bash
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python -m skillopt_sleep run --project "$(pwd)" --backend codex
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```
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Default backend is `mock` (no API spend). `--backend codex` uses your Codex
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budget for real improvement. All the controllable knobs (`--gate on|off`,
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`--rollouts-k`, `--budget-tokens`, `--preferences`, optimizer/target split) work
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identically — see [`../../docs/sleep/CONTROLLABLE_DREAMING.md`](../../docs/sleep/CONTROLLABLE_DREAMING.md).
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## Notes / status
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- Codex's `exec` runs shell, so the real-tool-loop replay (e.g. the
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`tool_called: search` benchmark seed) works natively.
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- Codex's standalone *plugin-package manifest* format is not yet a stable public
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spec; this integration uses the documented `AGENTS.md` + skills + prompts
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mechanisms, which are stable. If/when a `codex plugin` package format ships,
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we'll add a one-file manifest.
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