Instead of spawning separate processes or using OpenRouter, MoA now:
- Queries external API models (Kimi, GLM) in parallel for opinions
- Injects opinions into the SDK arbiter's prompt
- The existing subscription-based arbiter aggregates all perspectives
No extra SDK processes, no OpenRouter dependency. Per-model config via
MOA_REF_MODELS + MOA_{NAME}_MODEL/BASE_URL/API_KEY env vars.
When MOA_ENABLED=true, arbiter queries multiple LLM models in parallel
via OpenAI-compatible API, then an aggregator model synthesizes the
final verdict from all opinions. Falls back to single-agent arbiter
when MoA is disabled.
Config: MOA_BASE_URL, MOA_API_KEY, MOA_REFERENCE_MODELS, MOA_AGGREGATOR_MODEL
- Add Codex as alternative agent type (agentType: 'codex' per group)
- Codex container runner with session resume and 100-turn limit
- Dual Discord bot support (DISCORD_BOT_TOKEN + DISCORD_CODEX_BOT_TOKEN)
- Each bot handles only its agentType's registered groups
- Discord typing indicator refreshes every 8s (was single-shot, expired after ~10s)
- Agent runner 100-turn limit to prevent infinite bot-to-bot loops
- Apple Container runtime support (convert-to-apple-container skill)
- Session commands (/compact) support
- DB migration for agent_type column
* refactor: multi-channel infrastructure with explicit channel/is_group tracking
- Add channels[] array and findChannel() routing in index.ts, replacing
hardcoded whatsapp.* calls with channel-agnostic callbacks
- Add channel TEXT and is_group INTEGER columns to chats table with
COALESCE upsert to protect existing values from null overwrites
- is_group defaults to 0 (safe: unknown chats excluded from groups)
- WhatsApp passes explicit channel='whatsapp' and isGroup to onChatMetadata
- getAvailableGroups filters on is_group instead of JID pattern matching
- findChannel logs warnings instead of silently dropping unroutable JIDs
- Migration backfills channel/is_group from JID patterns for existing DBs
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* feat: skills engine v0.1 — deterministic skill packages with rerere resolution
Three-way merge engine for applying skill packages on top of a core
codebase. Skills declare which files they add/modify, and the engine
uses git merge-file for conflict detection with git rerere for
automatic resolution of previously-seen conflicts.
Key components:
- apply: three-way merge with backup/rollback safety net
- replay: clean-slate replay for uninstall and rebase
- update: core version updates with deletion detection
- rebase: bake applied skills into base (one-way)
- manifest: validation with path traversal protection
- resolution-cache: pre-computed rerere resolutions
- structured: npm deps, env vars, docker-compose merging
- CI: per-skill test matrix with conflict detection
151 unit tests covering merge, rerere, backup, replay, uninstall,
update, rebase, structured ops, and edge cases.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* feat: add Discord and Telegram skill packages
Skill packages for adding Discord and Telegram channels to NanoClaw.
Each package includes:
- Channel implementation (add/src/channels/)
- Three-way merge targets for index.ts, config.ts, routing.test.ts
- Intent docs explaining merge invariants
- Standalone integration tests
- manifest.yaml with dependency/conflict declarations
Applied via: npx tsx scripts/apply-skill.ts .claude/skills/add-discord
These are inert until applied — no runtime impact.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* remove unused docs (skills-system-status, implementation-guide)
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
