Restore detailed system prompt constant framing the LLM as a sports
journalist covering an emergent bot league, with specific guidance on
ELO deltas, rivalry context, head-to-head records, and scouting-style
lineage framing. Enrich per-arc prompts with critical moment summaries
(§13.2), community tactical hints, ELO before/after deltas, and
head-to-head records. Fix rivalry arc to include ELO context for both
bots. Ensure fall arc shows both wins and losses in key match listings.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Generates contextual turning-point descriptions for matches used in blog
narratives and rivalry chronicles (§13.2). Summarizes close scores, ELO
upsets, non-standard end conditions, and marathon matches.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Two functions referenced in generateLLMChronicle were undefined:
- getCurrentSeasonTheme: returns the active season's theme string
- buildHeadToHeadFromArc: computes W/L head-to-head records for a bot
against all opponents from match data, enriching LLM narrative prompts
Also improves the sports journalist system prompt with more detailed
coverage style guidance for better narrative quality.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
- Add data/meta/rivalries.json to R2 upload list in uploadMetaJSONToR2
- Add attachCommunityHints() to narrative.go to enrich story arcs with
highest-upvote community tactical hints (upvotes >= 3, idea/mistake types)
- Fix detectRivalryArcs() key separator from "-" to "|" to avoid UUID
hyphen collisions when parsing bot ID pairs
- Fix partitionBots() call sites in bot_strategies_phase13.go to use
struct field access (.friendly, .enemy) matching updated return type
generator.go already contains generateArchetypes, generateCommunityHints,
and generateMatchFeedback (all called from generateAllIndexes). main.go
uploads all four outputs to R2 on every build cycle.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Add transcript panel with turn-by-turn summaries generated from replay events
- Each turn shows: player moves, combat, deaths, captures, energy collection, spawns, win probability
- Add 'T' key shortcut to toggle transcript panel
- Panel supports three view modes: All Turns, ±10 Turns from Current, Recent 20 Turns
- Click on transcript entry to jump to that turn
- Current turn is highlighted in transcript with smooth scroll
- Panel content is selectable/copyable for screen reader users
- Transcript generation logic already existed in replay-viewer.ts; this adds the UI
- Transcript button slides in from right side of screen
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
- 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>
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>
- Add LLMBaseURL and LLMAPIKey config options for narrative generation
- Wire up LLM client to generateBlog() when LLM is configured
- Fix ParticipantData type usage in test files
- Simplify rivalry arc detection (remove alternation check)
- Fix type conversion in upset detection gap calculation
- Mark narrative engine as complete in PROGRESS.md
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Created narrative.go with story arc detection per plan §15.5
- Arc types: Rise, Fall, Rivalry, upset, evolution, comeback
- LLMClient for OpenAI-compatible API narrative generation
- generateLLMChronicles() using narrative engine
- Updated blog.go with LLM integration
- Template-based fallback when LLM unavailable
- Added tests in narrative_test.go
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
