Competition/Round architecture: full platform rewrite (Phases 1-9)

Replace Pipeline/Stage system with Competition/Round architecture.
New schema: Competition, Round (7 types), JuryGroup, AssignmentPolicy,
ProjectRoundState, DeliberationSession, ResultLock, SubmissionWindow.
New services: round-engine, round-assignment, deliberation, result-lock,
submission-manager, competition-context, ai-prompt-guard.
Full admin/jury/applicant/mentor UI rewrite. AI prompt hardening with
structured prompts, retry logic, and injection detection. All legacy
pipeline/stage code removed. 4 new migrations + seed aligned.

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

src/server/services/ai-assignment.ts

@@ -31,10 +31,39 @@ import {
 
 const ASSIGNMENT_BATCH_SIZE = 15
 
-// Optimized system prompt
-const ASSIGNMENT_SYSTEM_PROMPT = `Match jurors to projects by expertise. Return JSON assignments.
-Each: {juror_id, project_id, confidence_score: 0-1, expertise_match_score: 0-1, reasoning: str (1-2 sentences)}
-Distribute workload fairly. Avoid assigning jurors at capacity.`
+// Structured system prompt for assignment
+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.
+
+## Matching Criteria (Weighted)
+- Expertise Match (50%): How well juror tags/expertise align with project topics
+- Workload Balance (30%): Distribute assignments evenly; prefer jurors below capacity
+- Minimum Target (20%): Prioritize jurors who haven't reached their minimum assignment count
+
+## Output Format
+Return a JSON object:
+{
+  "assignments": [
+    {
+      "juror_id": "JUROR_001",
+      "project_id": "PROJECT_001",
+      "confidence_score": 0.0-1.0,
+      "expertise_match_score": 0.0-1.0,
+      "reasoning": "1-2 sentence justification"
+    }
+  ]
+}
+
+## Guidelines
+- Each project should receive the required number of reviews
+- 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
+- A poor match: no expertise overlap, only assigned for coverage`
 
 // ─── Types ───────────────────────────────────────────────────────────────────
 
@@ -126,6 +155,10 @@ async function processAssignmentBatch(
     batchMappings
   )
 
+  const MAX_PARSE_RETRIES = 2
+  let parseAttempts = 0
+  let response: Awaited<ReturnType<typeof openai.chat.completions.create>>
+
   try {
     const params = buildCompletionParams(model, {
       messages: [
@@ -133,11 +166,10 @@ async function processAssignmentBatch(
         { role: 'user', content: userPrompt },
       ],
       jsonMode: true,
-      temperature: 0.3,
+      temperature: 0.1,
       maxTokens: 4000,
     })
 
-    let response
     try {
       response = await openai.chat.completions.create(params)
     } catch (apiError) {
@@ -167,20 +199,8 @@ async function processAssignmentBatch(
       status: 'SUCCESS',
     })
 
-    const content = response.choices[0]?.message?.content
-    if (!content) {
-      // Check if response indicates an issue
-      const finishReason = response.choices[0]?.finish_reason
-      if (finishReason === 'content_filter') {
-        throw new Error('AI response was filtered. Try a different model or simplify the project descriptions.')
-      }
-      if (!response.choices || response.choices.length === 0) {
-        throw new Error(`No response from model "${model}". This model may not exist or may not be available. Please verify the model name.`)
-      }
-      throw new Error(`Empty response from AI model "${model}". The model may not support this type of request.`)
-    }
-
-    const parsed = JSON.parse(content) as {
+    // Parse with retry logic
+    let parsed: {
       assignments: Array<{
         juror_id: string
         project_id: string
@@ -190,6 +210,46 @@ async function processAssignmentBatch(
       }>
     }
 
+    while (true) {
+      try {
+        const content = response.choices[0]?.message?.content
+        if (!content) {
+          // Check if response indicates an issue
+          const finishReason = response.choices[0]?.finish_reason
+          if (finishReason === 'content_filter') {
+            throw new Error('AI response was filtered. Try a different model or simplify the project descriptions.')
+          }
+          if (!response.choices || response.choices.length === 0) {
+            throw new Error(`No response from model "${model}". This model may not exist or may not be available. Please verify the model name.`)
+          }
+          throw new Error(`Empty response from AI model "${model}". The model may not support this type of request.`)
+        }
+        parsed = JSON.parse(content)
+        break
+      } catch (parseError) {
+        if (parseError instanceof SyntaxError && parseAttempts < MAX_PARSE_RETRIES) {
+          parseAttempts++
+          console.warn(`[AI Assignment] JSON parse failed, retrying (${parseAttempts}/${MAX_PARSE_RETRIES})`)
+
+          // Retry the API call with hint
+          const retryParams = buildCompletionParams(model, {
+            messages: [
+              { role: 'system', content: ASSIGNMENT_SYSTEM_PROMPT },
+              { role: 'user', content: userPrompt + '\n\nIMPORTANT: Please ensure valid JSON output.' },
+            ],
+            jsonMode: true,
+            temperature: 0.1,
+            maxTokens: 4000,
+          })
+          response = await openai.chat.completions.create(retryParams)
+          const retryUsage = extractTokenUsage(response)
+          tokensUsed += retryUsage.totalTokens
+          continue
+        }
+        throw parseError
+      }
+    }
+
     // De-anonymize and add to suggestions
     const deanonymized = deanonymizeResults(
       (parsed.assignments || []).map((a) => ({