# v0.1.0-beta.8

Gitmoot v0.1.0-beta.8 adds ranked SkillOpt exploration as a beta workflow for
improving agent templates with broader human preference feedback before final
A/B validation.

## Features

- ranked SkillOpt review runs with `explore`, `refine`, `distill`, and
  `validate` modes
- N-way review item options through repeated `--option label=path` artifacts
- Markdown and GitHub feedback packets for ranked options and trait notes
- ranked feedback import with derived pairwise preferences for optimizer-ready
  training packages
- `skillopt review status` phase recommendations with ranking stability,
  pairwise preference counts, and advisory next-mode guidance
- clean-temp-home smoke-test documentation for ranked Markdown packets,
  training export inspection, and optional GitHub issue or PR feedback sync
- `gitmoot skillopt train` documentation for session/iteration orchestration,
  optimizer handoff, candidate review, explicit promote/reject decisions, and
  start-next gate enforcement
- `scripts/skillopt-train-smoke.sh` deterministic smoke coverage with fake
  managed generation, fake optimizer handoff, and fake GitHub publication

## Beta Limits

- final promotion should still use fresh A/B validation items by default
- GitHub feedback collection still uses issues or PR comments authored by the
  authenticated GitHub user
- phase recommendations are advisory and do not automatically change modes,
  import candidates, run optimizers, or promote templates
- the external optimizer remains outside the main Gitmoot binary
- train-mode smoke coverage uses fake GitHub and fake optimizer seams; real
  GitHub review publication still depends on authenticated `gh`

For current release artifacts, see
[GitHub releases](https://github.com/jerryfane/gitmoot/releases).
