| name | skill-opt-v1 |
| description | Project already-captured traces into scored-rollout rows for the SkillOpt optimizer. |
| mode | agent-skill |
| requires | ["ot workflow optimize","ot trace query"] |
skill-opt-v1
Scored-rollout projection for the SkillOpt text-space skill optimizer
(arXiv 2605.23904; design in kb/br/66-skillopt-text-space-skill-optimizer.md).
scripts/build_rows.py reads each already-captured trace from the local bucket,
scores it with opentraces.quality.engine.assess_trace, and emits one row per
trace. The trace's overall_utility (in [0,1] after scaling) is the rollout
score; the failed and passed quality checks become failure_tags and
success_tags, which the optimizer's reflection step and the held-out
validation gate consume.
This workflow is the forward-pass-over-captured-evidence layer. It does not run
an agent; the live re-rollout of a candidate skill is a later slice. The
opentraces workflow optimize consumer reads these rows, splits them into a
train and a held-out selection set by trace-id hash, proposes bounded
add/delete/replace edits, accepts only strictly-improving candidates, and
exports best_skill.md plus edit_apply_report.json.
Row shape
{
"trace_id": "…",
"project_slug": "…",
"session_id": "…",
"score": 0.62,
"overall_utility": 62.0,
"failure_tags": ["rl.RL1_grounded_outcome", "training.T3_clean_diff"],
"success_tags": ["conformance.C1_schema_version"],
"summary": "task description (truncated)",
"skill_digest": null
}
Scope
The run packet's scope may carry project_slug (or project) to narrow the
bucket scan to one project; otherwise every project's traces are projected.
