- Send system prompt as role:system instead of merging into the user message
(models treat system messages as authoritative -> better tool selection)
- Add full 14-tool catalog + multi-hop instruction to the system prompt
- Raise MAX_TOOL_ROUNDS 4->6 so multi-hop queries complete
- Raise conversation history 3->8 exchanges (less repeat questioning)
- Append guild/channel scope hint to each user turn
- Add saturating toolErrors counter + structured warn log per tool failure
so chatbot tool failures are observable instead of silently absorbed
Root cause: gateway migration 0016 removed the per-user reputation feature
(DROP TABLE user_reputations), but the backend still LEFT JOINed
pgUserReputationsTable in dashboard listUsers/getUserDetail and the chatbot
get_user_reputation tool. Against the live DB these queries raised 42P01
(undefined_table) -> the new /users page could never load (oRPC WS error).
Fix:
- dashboard.repository.ts: remove reputation columns/join from listUsers and
getUserDetail (data sourced only from messages + user_profiles).
- chatbot.tools.ts: get_user_reputation now returns honest 'unavailable'
(feature removed) instead of querying the dropped table.
- chatbot.toolDefs.ts: update tool description so the LLM doesn't advertise
a dead feature.
- frontend types/users view: drop trust_score/clean_message_streak/
total_infractions/last_infraction_at; derive risk label from real flagged%
and add warn_count to the inspector (real available data).
Verified: backend+frontend tsc clean, biome clean, 37 unit tests pass,
query tested against live DB (returns real members), build green.
The chatbot agent now has 14 tools (was 4) so it can answer about ANY
server situation from live data instead of a static snapshot:
- get_server_stats (now also returns clean count)
- get_top_channels, get_recent_activity, get_top_flagged
- search_messages (LIKE keyword search)
- get_user_messages, get_user_profile, get_user_reputation
- get_channel_culture
- get_message_detail (full AI analysis of one message)
- get_message_reviews (human moderation queue by status)
- get_voice_recordings (with transcriptions)
- get_moderation_timeline (daily flagged/warn/clean trend)
- get_corrections (AI false-positive correction history)
Security/quality:
- Every executor now uses parameterized drizzle queries (eq/like/and).
The old code interpolated model-supplied IDs into sql.raw() — a SQL
injection vector. Removed.
- Split static tool *definitions* into chatbot.toolDefs.ts (no DB import)
so the LLM-facing schema can be unit-tested without loading the
database/config layer. chatbot.tools.ts keeps only the executor.
Verified: tsc + biome clean, 40 backend tests pass (4 new covering the
tool-contract: names unique, required args declared, full situation
coverage).
Co-Authored-By: Claude Opus 5 (Nous Research)
Backend:
- New chatbot.tools.ts: 4 tools (get_server_stats, get_top_channels,
get_recent_activity, get_top_flagged) with real DB executors
- chatbot.service: agentic loop — stream:true, parse SSE, execute
tool_calls, feed results back, up to 4 rounds
- controller: resolve userId from X-User-Id header (no-login device
uuid) with auth middleware precedence; history/clear scoped per user
Frontend:
- use-chatbot-user: mint UUID in localStorage, send as X-User-Id
- chatbotApi.send/getHistory/clearHistory accept userId header
- client.ts: apiRequest supports custom headers per call
- provider: history load + send + clear keyed to device user id
asepharyana
asepharyana
