Display names like "Calm your tits" were causing the LLM to inflate toxicity
scores on completely benign messages. Usernames are now replaced with User1,
User2, etc. before sending to the LLM, then mapped back to real names in the
results.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The triage LLM was blending context message content into its reasoning
for new messages (e.g., citing profanity from context when the new
message was just "I'll be here"). Added per-message [CONTEXT] tags
inline and strengthened the prompt to explicitly forbid referencing
context content in reasoning/scores.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The display name "Calm your tits" was being factored into toxicity
scores. Updated the analysis prompt to explicitly instruct the LLM
to ignore all usernames/display names when scoring messages.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The conversation analysis was re-scoring old messages alongside new ones,
causing users to get penalized repeatedly for already-scored messages.
A "--- NEW MESSAGES ---" separator now marks which messages are new, and
the prompt instructs the LLM to score only those. Also fixes bot-mention
detection to require an explicit @mention in message text rather than
treating reply-pings as scans (so toxic replies to bot warnings aren't
silently skipped).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Switch from per-user message batching to per-channel conversation
analysis. The LLM now sees the full interleaved conversation with
relative timestamps, reply chains, and consecutive message collapsing
instead of isolated flat text per user.
Key changes:
- Fix gpt-5-nano temperature incompatibility (conditional temp param)
- Add mention-triggered scan: users @mention bot to analyze recent chat
- Refactor debounce buffer from (channel_id, user_id) to channel_id
- Replace per-message analyze_message() with analyze_conversation()
returning per-user findings from a single LLM call
- Add CONVERSATION_TOOL schema with coherence, topic, and game fields
- Compact message format: relative timestamps, reply arrows (→),
consecutive same-user message collapsing
- Separate mention scan tasks from debounce tasks
- Remove _store_context/_get_context (conversation block IS the context)
- Escalation timeout config: [30, 60, 120, 240] minutes
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Slim down chat_roast.txt — remove anti-repetition rules that were
compensating for the local model (gpt-4o-mini handles this natively).
Remove disagreement detection from analysis prompt, tool schema, and
sentiment handler. Saves ~200 tokens per analysis call.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
LLM analysis now detects when two users are in a genuine
disagreement. When detected, the bot creates a native Discord
poll with each user's position as an option.
- Disagreement detection added to LLM analysis tool schema
- Polls last 4 hours with 1 hour per-channel cooldown
- LLM extracts topic, both positions, and usernames
- Configurable via polls section in config.yaml
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Send last ~8 messages from all users (not just others) as a
multi-line chat log with relative timestamps so the LLM can
better understand conversation flow and escalation patterns.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Detect when users discuss a game in the wrong channel (e.g. GTA talk
in #warzone) and send a friendly redirect to the correct channel.
Also add sexual_vulgar category and scoring rules so crude sexual
remarks directed at someone aren't softened by "lmao".
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Move the analysis and chat personality system prompts from inline Python
strings to prompts/analysis.txt and prompts/chat_personality.txt for
easier editing. Also add a rule so users quoting/reporting what someone
else said are not penalized for the quoted words.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
