AI-powered assignment generation with enriched data and streaming UI

- Add aiPreview mutation with full project/juror data (bios, descriptions,
  documents, categories, ocean issues, countries, team sizes)
- Increase AI description limit from 300 to 2000 chars for richer context
- Update GPT system prompt to use all available data fields
- Add mode toggle (AI default / Algorithm fallback) in assignment preview
- Lift AI mutation to parent page for background generation persistence
- Show visual indicator on page while AI generates (spinner + progress card)
- Toast notification with "Review" action when AI completes
- Staggered reveal animation for assignment results (streaming feel)
- Fix assignment balance with dynamic penalty (25pts per existing assignment)

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

src/server/services/ai-assignment.ts

@@ -35,11 +35,15 @@ const ASSIGNMENT_BATCH_SIZE = 15
 const ASSIGNMENT_SYSTEM_PROMPT = `You are an expert jury assignment optimizer for an ocean conservation competition.
 
 ## Your Role
-Match jurors to projects based on expertise alignment, workload balance, and coverage requirements.
+Match jurors to projects based on expertise alignment, workload balance, geographic diversity, and coverage requirements. You have access to rich data about both jurors and projects — use ALL available information to make optimal assignments.
+
+## Available Data
+- **Jurors**: expertiseTags (areas of expertise), bio (background description with deeper domain knowledge), country, currentAssignmentCount, maxAssignments
+- **Projects**: title, description (detailed project overview), tags (with confidence 0-1), category (e.g. STARTUP, BUSINESS_CONCEPT), oceanIssue (focus area like CORAL_REEFS, POLLUTION), country, institution, teamSize, fileTypes (submitted document types)
 
 ## Matching Criteria (Weighted)
-- Expertise Match (50%): How well juror tags/expertise align with project topics. Project tags include a confidence score (0-1) — weight higher-confidence tags more heavily as they are more reliably assigned. A tag with confidence 0.9 is a strong signal; one with 0.5 is uncertain.
-- Workload Balance (30%): Distribute assignments evenly; prefer jurors below capacity
+- Expertise & Domain Match (50%): How well juror tags, bio, and background align with project topics, category, ocean issue, and description. Use bio text to identify deeper domain expertise beyond explicit tags — e.g., a bio mentioning "20 years of coral research" matches coral-related projects even without explicit tags. Weight higher-confidence tags more heavily.
+- Workload Balance (30%): Distribute assignments as evenly as possible; strongly prefer jurors below capacity. Never let one juror get significantly more assignments than another.
 - Minimum Target (20%): Prioritize jurors who haven't reached their minimum assignment count
 
 ## Output Format
@@ -51,18 +55,20 @@ Return a JSON object:
       "project_id": "PROJECT_001",
       "confidence_score": 0.0-1.0,
       "expertise_match_score": 0.0-1.0,
-      "reasoning": "1-2 sentence justification"
+      "reasoning": "1-2 sentence justification referencing specific expertise matches"
     }
   ]
 }
 
 ## Guidelines
-- Each project should receive the required number of reviews
+- Each project MUST receive the required number of reviews — ensure full coverage
+- Distribute assignments as evenly as possible across all jurors
 - Do not assign jurors who are at or above their capacity
-- Favor geographic and disciplinary diversity in assignments
-- confidence_score reflects overall assignment quality; expertise_match_score reflects tag overlap only
-- A strong match: shared expertise tags + available capacity + under minimum target
-- An acceptable match: related domain + available capacity
+- Favor geographic diversity: avoid assigning jurors from the same country as the project when possible
+- Consider disciplinary diversity: mix different expertise backgrounds per project
+- confidence_score reflects overall assignment quality; expertise_match_score reflects tag/expertise overlap
+- A strong match: shared expertise tags + relevant bio background + available capacity
+- An acceptable match: related domain/ocean issue + available capacity
 - A poor match: no expertise overlap, only assigned for coverage`
 
 // ─── Types ───────────────────────────────────────────────────────────────────
@@ -88,6 +94,8 @@ interface JurorForAssignment {
   name?: string | null
   email: string
   expertiseTags: string[]
+  bio?: string | null
+  country?: string | null
   maxAssignments?: number | null
   _count?: {
     assignments: number
@@ -101,6 +109,12 @@ interface ProjectForAssignment {
   tags: string[]
   tagConfidences?: Array<{ name: string; confidence: number }>
   teamName?: string | null
+  competitionCategory?: string | null
+  oceanIssue?: string | null
+  country?: string | null
+  institution?: string | null
+  teamSize?: number
+  fileTypes?: string[]
   _count?: {
     assignments: number
   }

src/server/services/anonymization.ts

@@ -21,7 +21,7 @@ import type {
 // ─── Description Limits ──────────────────────────────────────────────────────
 
 export const DESCRIPTION_LIMITS = {
-  ASSIGNMENT: 300,
+  ASSIGNMENT: 2000,
   FILTERING: 500,
   ELIGIBILITY: 400,
   MENTOR: 350,
@@ -46,6 +46,8 @@ export interface AnonymizedJuror {
   expertiseTags: string[]
   currentAssignmentCount: number
   maxAssignments: number | null
+  bio?: string | null
+  country?: string | null
 }
 
 export interface AnonymizedProject {
@@ -54,6 +56,12 @@ export interface AnonymizedProject {
   description: string | null
   tags: Array<{ name: string; confidence: number }>
   teamName: string | null
+  category?: string | null
+  oceanIssue?: string | null
+  country?: string | null
+  institution?: string | null
+  teamSize?: number
+  fileTypes?: string[]
 }
 
 export interface JurorMapping {
@@ -200,6 +208,8 @@ interface JurorInput {
   name?: string | null
   email: string
   expertiseTags: string[]
+  bio?: string | null
+  country?: string | null
   maxAssignments?: number | null
   _count?: {
     assignments: number
@@ -213,6 +223,12 @@ interface ProjectInput {
   tags: string[]
   tagConfidences?: Array<{ name: string; confidence: number }>
   teamName?: string | null
+  competitionCategory?: string | null
+  oceanIssue?: string | null
+  country?: string | null
+  institution?: string | null
+  teamSize?: number
+  fileTypes?: string[]
 }
 
 /**
@@ -238,6 +254,8 @@ export function anonymizeForAI(
       expertiseTags: juror.expertiseTags,
       currentAssignmentCount: juror._count?.assignments ?? 0,
       maxAssignments: juror.maxAssignments ?? null,
+      bio: juror.bio ? truncateAndSanitize(juror.bio, 500) : null,
+      country: juror.country ?? null,
     }
   })
 
@@ -260,6 +278,12 @@ export function anonymizeForAI(
           ? project.tagConfidences
           : project.tags.map((t) => ({ name: t, confidence: 1.0 })),
         teamName: project.teamName ? `Team ${index + 1}` : null,
+        category: project.competitionCategory ?? null,
+        oceanIssue: project.oceanIssue ?? null,
+        country: project.country ?? null,
+        institution: project.institution ? sanitizeText(project.institution) : null,
+        teamSize: project.teamSize,
+        fileTypes: project.fileTypes,
       }
     }
   )

src/server/services/round-assignment.ts

@@ -303,19 +303,47 @@ export async function previewRoundAssignment(
     }
   }
 
-  // Sort by score descending
-  suggestions.sort((a, b) => b.score - a.score)
+  // Balance-aware greedy assignment: at each step, pick the best suggestion
+  // while dynamically penalizing jurors who already have more assignments
+  // to distribute work as evenly as possible.
+  const BALANCE_PENALTY_PER_ASSIGNMENT = 25
 
-  // Greedy assignment: pick top suggestions respecting caps
   const finalAssignments: AssignmentSuggestion[] = []
   const finalJurorCounts = new Map(jurorAssignmentCounts)
   const finalProjectCounts = new Map(projectAssignmentCounts)
+  const consumed = new Set<number>()
+
+  while (consumed.size < suggestions.length) {
+    let bestIdx = -1
+    let bestAdjustedScore = -Infinity
+
+    for (let i = 0; i < suggestions.length; i++) {
+      if (consumed.has(i)) continue
+      const s = suggestions[i]
+
+      const projectCount = finalProjectCounts.get(s.projectId) ?? 0
+      if (projectCount >= requiredReviews) {
+        consumed.add(i)
+        continue
+      }
+
+      const jurorCount = finalJurorCounts.get(s.userId) ?? 0
+      // Dynamic balance penalty: penalize jurors who already have more assignments
+      const balancePenalty = jurorCount * BALANCE_PENALTY_PER_ASSIGNMENT
+      const adjustedScore = s.score - balancePenalty
+
+      if (adjustedScore > bestAdjustedScore) {
+        bestAdjustedScore = adjustedScore
+        bestIdx = i
+      }
+    }
+
+    if (bestIdx === -1) break
+
+    const suggestion = suggestions[bestIdx]
+    consumed.add(bestIdx)
 
-  for (const suggestion of suggestions) {
     const jurorCount = finalJurorCounts.get(suggestion.userId) ?? 0
-    const projectCount = finalProjectCounts.get(suggestion.projectId) ?? 0
-
-    if (projectCount >= requiredReviews) continue
 
     // Re-check cap
     const member = members.find((m: any) => m.userId === suggestion.userId)
@@ -334,7 +362,7 @@ export async function previewRoundAssignment(
 
     finalAssignments.push(suggestion)
     finalJurorCounts.set(suggestion.userId, jurorCount + 1)
-    finalProjectCounts.set(suggestion.projectId, projectCount + 1)
+    finalProjectCounts.set(suggestion.projectId, (finalProjectCounts.get(suggestion.projectId) ?? 0) + 1)
   }
 
   const unassignedProjects = projects.filter(