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skillopt-sleep

Run the Microsoft SkillOpt-Sleep workflow for ADVX Live's room-6657 style skill. Use when downloading the pinned optimizer, validating the reviewed task set, running mock or Codex optimization, inspecting staged candidates, evaluating final tests, adopting a reviewed improvement, rejecting an unsafe candidate, or rolling back an adopted proposal.

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woodfishhhh/ADVX-live
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July 24, 2026 at 15:28
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SKILL.md
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name
skillopt-sleep
description
Run the Microsoft SkillOpt-Sleep workflow for ADVX Live's room-6657 style skill. Use when downloading the pinned optimizer, validating the reviewed task set, running mock or Codex optimization, inspecting staged candidates, evaluating final tests, adopting a reviewed improvement, rejecting an unsafe candidate, or rolling back an adopted proposal.
# SkillOpt-Sleep Use the project wrapper for every room-6657 optimization action: `python scripts/run_room_6657_skillopt.py <action>`. Do not invoke the upstream `skillopt_sleep` CLI directly from this repository. The wrapper pins the upstream commit, uses project-private state, selects the native Windows Codex executable, disables memory evolution, and compiles accepted learned directives into the backend runtime artifact. ## Workflow 1. Run `bootstrap`, then `validate`. 2. Run `dry-run --backend mock` to prove plumbing only. 3. Run `run --backend codex` for a real bounded optimization. 4. Run `status` and inspect the latest `report.md`, `report.json`, `diagnostics.json`, and `proposed_SKILL.md`. 5. Reject a candidate that weakens a Persona or product contract, even when the model gate accepts it. 6. Run `evaluate --backend codex --skill <candidate>` on every candidate that survives review. 7. Record the explicit review with `approve --staging <directory> --reason "<review rationale>"` after the final tests pass. A rejected candidate cannot later be approved; run a new optimization instead. 8. Run `adopt --staging <directory>` only after approval is recorded. 9. Run project tests after adoption. Use `rollback --staging <directory>` if an adopted proposal regresses runtime behavior. ## Boundaries - Use only the reviewed task file under `tests/fixtures/room-6657/`. - Never harvest local transcripts or private sessions for this workflow. - Never enable memory evolution, scheduling, or automatic adoption. - Treat mock results as plumbing evidence, not language-quality evidence. - Keep the sb6657 corpus out of prompts, tasks, skills, staging reports, and generated runtime JSON. - Preserve every second-level heading and all 13 Persona identifiers in the target skill. - Allow at most two proposed edits in one run. - Require strict validation-set improvement, project review, and untouched final-test success before adoption. - Keep rejected staging directories as local evidence; they are Git-ignored and cannot be adopted through the wrapper after rejection. ## Upstream The pinned Microsoft SkillOpt repository and license are recorded in `resources/skillopt/skillopt.lock.json`. `bootstrap` downloads that exact commit to `.advx-data/tools/SkillOpt`, which remains outside version control.
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