Add nightly Moonbeam argument leaderboard extraction, API, and muzzle.lol review UI

README.md

@@ -254,20 +254,20 @@ docker logs <container-id> | jq .
 
 ### AI Features (Optional)
 
-- **Daily Memory Job** - Summarizes conversations daily at 3 AM (requires OpenAI API key)
+- **Nightly Analysis Sequence** - Runs memory extraction, argument analysis, and trait synthesis daily at 3 AM (requires OpenAI API key)
 - **Sentiment Analysis** - Analyzes message tone
 - **AI Summaries** - Generates summaries of message threads
 
 ### Scheduled Jobs
 
 Most scheduled jobs run inside the backend Node.js process using `node-cron`. They are started automatically when the server connects to the database.
 
-| Job              | Schedule                         | Location    | Description                                                                        |
-| ---------------- | -------------------------------- | ----------- | ---------------------------------------------------------------------------------- |
-| **Daily Memory** | `0 3 * * *` (3 AM ET)            | In-process  | Extracts AI memories from all Slack channels                                       |
-| **Fun Fact**     | `0 9 * * *` (9 AM ET)            | In-process  | Posts daily facts, joke, quote, and on-this-day event to Slack                     |
-| **Pricing**      | `10 * * * *` (every hour at :10) | In-process  | Recalculates item prices based on median reputation                                |
-| **Health Check** | `*/5 * * * *` (every 5 min)      | Bash script | Checks the `/health` endpoint from outside the process and alerts Slack on failure |
+| Job                           | Schedule                         | Location    | Description                                                                                     |
+| ----------------------------- | -------------------------------- | ----------- | ----------------------------------------------------------------------------------------------- |
+| **Nightly Analysis Sequence** | `0 3 * * *` (3 AM ET)            | In-process  | Runs memory extraction, selective argument leaderboard extraction, and trait synthesis in order |
+| **Fun Fact**                  | `0 9 * * *` (9 AM ET)            | In-process  | Posts daily facts, joke, quote, and on-this-day event to Slack                                  |
+| **Pricing**                   | `10 * * * *` (every hour at :10) | In-process  | Recalculates item prices based on median reputation                                             |
+| **Health Check**              | `*/5 * * * *` (every 5 min)      | Bash script | Checks the `/health` endpoint from outside the process and alerts Slack on failure              |
 
 #### Fun Fact Job environment variables
 

packages/backend/src/ai/ai.constants.ts

@@ -207,3 +207,52 @@ Output format:
 - If no strong traits are present, return []`;
 
 export const DAILY_MEMORY_JOB_CONCURRENCY = 50;
+export const DAILY_ARGUMENT_JOB_CONCURRENCY = 50;
+
+export const ARGUMENT_EXTRACTION_PROMPT = `You are a highly selective argument detection tool reviewing one Slack channel's last 24 hours of conversation.
+
+Your job is to identify every clearly real argument between humans in this channel, if any clearly happened, and determine who won each one.
+
+You must be INTOLERANT OF FALSE POSITIVES.
+Prefer false negatives over false positives.
+If there is any meaningful doubt that the conversation was a real argument, return [].
+
+ONLY treat something as an argument when ALL of the following are true:
+- at least two identifiable human participants directly disagreed
+- the disagreement involved competing viewpoints, not just different preferences stated once
+- there was sustained back-and-forth with rebuttals or direct challenges
+- the winner can be identified from the substance of the exchange
+
+Return [] for:
+- jokes, banter, teasing, sarcasm, or friendly ribbing
+- brief disagreements without sustained rebuttals
+- brainstorming, clarification, or neutral discussion
+- factual Q&A where one person is simply correct
+- bot interactions or people reacting to Moonbeam
+- any conversation where the winner is ambiguous
+- weak or low-substance disagreements that do not merit leaderboard tracking
+
+Return ONLY a JSON array.
+
+Each array item must be a JSON object in this exact shape:
+{
+  "summary": "short summary of the argument",
+  "participants": [
+    { "slackId": "U123", "name": "Alice", "viewpoint": "their side of the argument" }
+  ],
+  "winnerSlackId": "U123",
+  "pointValue": 4
+}
+
+Rules for valid JSON output:
+- return [] if no conversation clearly qualifies
+- include 0 or more argument objects; do not invent arguments just to fill the array
+- each argument object must include at least 2 participants
+- every participant must be a human from the conversation
+- the winnerSlackId must match one of the listed participants
+- pointValue must be an integer from 0 to 5 based on substance/depth
+- reserve 4-5 for long, detailed, high-signal arguments
+- omit any weak or ambiguous disagreement instead of returning a low-confidence object
+- do not include markdown, prose, or extra keys
+
+If no conversation clearly qualifies, return the exact JSON array [] and nothing else.`;

packages/backend/src/ai/ai.service.ts

@@ -26,16 +26,11 @@ import { SlackService } from '../shared/services/slack/slack.service';
 import { SlackPersistenceService } from '../shared/services/slack/slack.persistence.service';
 import { MuzzlePersistenceService } from '../muzzle/muzzle.persistence.service';
 import OpenAI from 'openai';
-import type {
-  ResponseOutputMessage,
-  ResponseOutputItem,
-  ResponseOutputText,
-  ResponseOutputRefusal,
-} from 'openai/resources/responses/responses';
 import type { Part } from '@google/genai';
 import { GoogleGenAI } from '@google/genai';
 import sharp from 'sharp';
 import { extractParticipantSlackIds } from './helpers/extractParticipantSlackIds';
+import { extractOpenAiResponseText } from './helpers/extractOpenAiResponseText';
 import { TraitService } from '../trait/trait.service';
 
 interface ReleaseCommit {
@@ -51,17 +46,6 @@ interface ReleaseMetadata {
 
 const isRecord = (value: unknown): value is Record<string, unknown> => typeof value === 'object' && value !== null;
 
-const isResponseOutputMessage = (block: ResponseOutputItem): block is ResponseOutputMessage => block.type === 'message';
-
-const isResponseOutputText = (block: ResponseOutputText | ResponseOutputRefusal): block is ResponseOutputText =>
-  block.type === 'output_text';
-
-const extractAndParseOpenAiResponse = (response: OpenAI.Responses.Response): string | undefined => {
-  const textBlock = response.output.find(isResponseOutputMessage);
-  const outputText = textBlock?.content.find(isResponseOutputText)?.text;
-  return outputText?.trim();
-};
-
 const ensureSentenceCaseAndPunctuation = (text: string): string => {
   const trimmed = text.trim();
   if (!trimmed) {
@@ -151,7 +135,7 @@ export class AIService {
         user: `${userId}-DaBros2016`,
       })
       .then((x) => {
-        return extractAndParseOpenAiResponse(x);
+        return extractOpenAiResponseText(x);
       })
       .then(async (result) => {
         await this.redis.removeInflight(userId, teamId);
@@ -205,7 +189,7 @@ export class AIService {
         input: REDPLOY_MOONBEAM_TEXT_PROMPT,
         user: 'Moonbeam',
       })
-      .then((x) => extractAndParseOpenAiResponse(x));
+      .then((x) => extractOpenAiResponseText(x));
 
     const aiImage = this.gemini.models
       .generateContent({
@@ -370,7 +354,7 @@ export class AIService {
     return this.openAi.responses
       .create({ model: GPT_MODEL, input: text, user: 'Moonbeam', instructions: CORPO_SPEAK_INSTRUCTIONS })
       .then((x) => {
-        return extractAndParseOpenAiResponse(x);
+        return extractOpenAiResponseText(x);
       })
       .catch(async (e) => {
         logError(this.aiServiceLogger, 'Failed to generate corpo-speak response', e, {
@@ -427,7 +411,7 @@ export class AIService {
         input: prompt,
         user: `${user_id}-DaBros2016`,
       })
-      .then((x) => extractAndParseOpenAiResponse(x))
+      .then((x) => extractOpenAiResponseText(x))
       .then(async (result) => {
         await this.redis.removeInflight(user_id, team_id);
         if (!result) {
@@ -527,7 +511,7 @@ export class AIService {
         input,
         user: `participation-${channelId}-${teamId}-DaBros2016`,
       })
-      .then((x) => extractAndParseOpenAiResponse(x))
+      .then((x) => extractOpenAiResponseText(x))
       .then((result) => {
         this.aiServiceLogger.info('Received participation model response', {
           teamId,

packages/backend/src/ai/helpers/extractOpenAiResponseText.ts

@@ -0,0 +1,10 @@
+import type OpenAI from 'openai';
+
+export const extractOpenAiResponseText = (response: OpenAI.Responses.Response): string | undefined => {
+  const textBlock = response.output.find((item) => item.type === 'message');
+  if (textBlock && 'content' in textBlock) {
+    const outputText = textBlock.content.find((item) => item.type === 'output_text');
+    return outputText?.text.trim();
+  }
+  return undefined;
+};

packages/backend/src/ai/memory/memory.job.ts

@@ -7,8 +7,8 @@ import { AIService } from '../ai.service';
 import { logger } from '../../shared/logger/logger';
 import { DAILY_MEMORY_JOB_CONCURRENCY, GATE_MODEL, MEMORY_EXTRACTION_PROMPT } from '../ai.constants';
 import { MOONBEAM_SLACK_ID } from '../ai.constants';
-import type OpenAI from 'openai';
 import { extractParticipantSlackIds } from '../helpers/extractParticipantSlackIds';
+import { extractOpenAiResponseText } from '../helpers/extractOpenAiResponseText';
 
 interface ExtractionResult {
   slackId: string;
@@ -17,15 +17,6 @@ interface ExtractionResult {
   existingMemoryId: number | null;
 }
 
-const extractAndParseOpenAiResponse = (response: OpenAI.Responses.Response): string | undefined => {
-  const textBlock = response.output.find((item) => item.type === 'message');
-  if (textBlock && 'content' in textBlock) {
-    const outputText = textBlock.content.find((item) => item.type === 'output_text');
-    return outputText?.text.trim();
-  }
-  return undefined;
-};
-
 export class MemoryJob {
   private historyService = new HistoryPersistenceService();
   private memoryPersistenceService = new MemoryPersistenceService();
@@ -111,7 +102,7 @@ export class MemoryJob {
           instructions: prompt,
           input: conversationHistory,
         })
-        .then((response) => extractAndParseOpenAiResponse(response));
+        .then((response) => extractOpenAiResponseText(response));
 
       if (!result) {
         this.jobLogger.warn('Extraction returned no result');