outcome-update

Outcome Update

Update only the reusable playbook and completion gate for an outcome loop. This is observer mode: inspect prior runs and Superdense reward evidence, then improve run.md and, when repeated misses show a reusable completion gap, gate.md for future runs.

Read references/outcome-loop.md before editing.

Workflow

1. Locate the outcome folder and read goal.md, run.md, gate.md, and runs/.
2. Identify runs since ## Update Marker in run.md. If no marker exists, review all completed run folders and add ## Update Marker after updating.
3. Inspect Superdense evidence related to those runs:
   • session IDs listed in work.md,
   • artifact IDs,
   • externalization target IDs,
   • relevant cohorts or version chains,
   • reward snapshots already stored in Superdense.
   • hypotheses and experiments referenced in work.md,
   • open/refuted/supported hypotheses from superdense hypothesis list --project <project-id>,
   • open or due experiments from superdense experiment list --project <project-id>.
4. Look for macro improvements:
   • levers that seem weak, strong, or under-instrumented,
   • lever statuses to promote, exhaust, retire, or keep because they are Pareto-best on a non-headline reward dimension or guardrail,
   • realized explore/exploit mix versus the target ratio,
   • hypotheses that should be pruned from future selection because they were refuted,
   • experiments that need more reps, are due for verdict, or are inconclusive because instrumentation is missing,
   • novelty gaps in untested lever regions,
   • actions that repeatedly create friction,
   • missing preflight checks,
   • repeated required-gate failures or warning misses,
   • diagnostic measurements that explain the north star poorly,
   • target repo/account workflow gaps,
   • Superdense reward-layer bottlenecks.
5. Render due verdicts with superdense experiment verdict <id> when an experiment has enough reps and a mature reward window. Use verdicts to update lever status and the Selection Policy, but do not duplicate reward snapshots into markdown.
6. Retune the target explore ratio in run.md as evidence accumulates: higher when uncertainty and novelty gaps dominate, lower when a proven lever has headroom and supported hypotheses.
7. Edit run.md for playbook improvements and gate.md for reusable completion checks or failure-policy refinements. Do not edit goal.md, old run folders, or target repos. Do not create a new run.
8. Keep goal.md protected. If evidence suggests the north star or guardrails are wrong, add a clearly marked "Recommended goal review" section to run.md instead of changing goal.md.
9. Preserve useful existing playbook content. Make focused improvements that the next outcome-run can execute without guessing.
10. Update ## Update Marker in run.md to the latest reviewed run id or timestamp.
11. Commit the playbook and gate changes, for example git add run.md gate.md && git commit -m "outcome: update playbook (runs through <marker>)". If any reviewed runs/<run-id>/ files are still uncommitted, include them in the same commit.