- Add ReplayPlayer to type imports in replay-viewer.ts
- Add explicit type annotation for entry parameter in replay.ts transcript map
- Fixes TypeScript compilation errors for §15.3 screen reader transcript feature
- SeasonID and RulesVersion already present in engine/types.go Config struct
- Worker already populates from active season row via DB join
- Config embedded in VisibleState sent to bots each turn (including turn 0)
- All starter kits (go, python, rust, java, csharp) already expose and log fields
- Add season_id/rules_version logging to JavaScript starter on turn 0
- TypeScript Config interface already includes season_id and rules_version
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Per plan §10.8 (deployment pipeline) and §9.8 (Argo Workflows):
- Add waitForWorkflowCompletion() that polls Argo Workflow API
- Add getWorkflowStatus() to fetch workflow phase/status
- Update Promote() to wait for workflow completion before inserting bot record
- Update Promote() to wait for K8s deployment readiness (waitForDeployment)
- Update triggerArgoWorkflow() to return workflow name for polling
- Add acb-evolved-bot-deploy-workflowtemplate.yml to manifests
The promotion flow now:
1. Writes bot source to bots/evolved/<bot_name>/
2. Commits and pushes source to git
3. Triggers Argo WorkflowTemplate
4. Waits for workflow completion (build + manifest commit)
5. Waits for K8s deployment to be ready
6. Inserts bot record into bots table
7. Updates programs table with bot_id/bot_name
This ensures evolved bots have running containers before being marked active.
Replace random 2-player pairing with the full §6.1 algorithm:
- Seed selection: bot with oldest last-match timestamp (tiebreak: lowest bot ID)
- Format selection: seed's least-played player count among {2, 3, 4, 6}
- Opponent selection: Pareto 80%/16-rank skill proximity + oldest last-pairing
with seed + fewest 24h games for game-count balance
- Map selection: least-recently-used active map for the chosen player count,
with map_scores.last_used_at updated after each match
- Random player slot assignment for all participant counts
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- arena/arena.go: 10-match mini-tournament running candidate as a local
subprocess against diverse live opponents sampled across the rating
distribution; AES-GCM secret decryption for opponent auth
- arena/psro.go: Nash equilibrium computation for the 1×K meta-game;
FictitiousPlayNash included for future K×K support
- arena/winrate.go: Wilson-score 95% CI for win-rate calculation; draws
counted as 0.5 wins
- arena/gate.go: two-part promotion gate — Nash value ≥ threshold AND
MAP-Elites niche fill or improvement; detailed reason strings
- promoter/promoter.go: full promotion pipeline — bot source + Dockerfile
+ K8s Secret/Deployment/Service manifests, docker build, git commit/push
(ArgoCD sync), kubectl readiness poll, bots-table INSERT, programs-table
update; RetireBot and EnforcePolicy (rating threshold + population cap 50)
- db/db.go: add bot_name / bot_secret migration columns
- db/programs.go: ListPromoted, SetBotNameAndSecret, UnsetPromoted,
GetByBotID, PromotedCount helpers for promotion/retirement lifecycle
- main.go: evaluate and retire subcommands wiring arena + gate + promoter;
remove unused island flag from evaluate
- arena/arena_test.go: 21 unit tests covering Nash, Wilson CI, Gate logic,
and selectDiverse opponent sampling
- promoter/promoter_test.go: tests for Dockerfiles, bot-ID/secret generation,
AES-GCM helpers, and K8s manifest templates
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
