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-award-eligibility.ts

@@ -14,6 +14,7 @@
 import { getOpenAI, getConfiguredModel, buildCompletionParams } from '@/lib/openai'
 import { logAIUsage, extractTokenUsage } from '@/server/utils/ai-usage'
 import { classifyAIError, createParseError, logAIError } from './ai-errors'
+import { sanitizeUserInput } from '@/server/services/ai-prompt-guard'
 import {
   anonymizeProjectsForAI,
   validateAnonymizedProjects,
@@ -27,10 +28,42 @@ import type { SubmissionSource } from '@prisma/client'
 
 const BATCH_SIZE = 20
 
-// Optimized system prompt
-const AI_ELIGIBILITY_SYSTEM_PROMPT = `Award eligibility evaluator. Evaluate projects against criteria, return JSON.
-Format: {"evaluations": [{project_id, eligible: bool, confidence: 0-1, reasoning: str}]}
-Be objective. Base evaluation only on provided data. No personal identifiers in reasoning.`
+// Structured system prompt for award eligibility
+const AI_ELIGIBILITY_SYSTEM_PROMPT = `You are an award eligibility evaluator for an ocean conservation competition.
+
+## Your Role
+Determine whether each project meets the criteria for a specific award category.
+
+## Evaluation Dimensions
+- Geographic Relevance: Does the project's location/focus match the award's geographic requirements?
+- Category Fit: Does the project category align with the award criteria?
+- Topic Alignment: Does the project's ocean issue focus match the award's thematic area?
+- Maturity Level: Is the project at the right stage for this award?
+
+## Output Format
+Return a JSON object:
+{
+  "evaluations": [
+    {
+      "project_id": "PROJECT_001",
+      "eligible": true/false,
+      "confidence": 0.0-1.0,
+      "reasoning": "2-3 sentence explanation covering key dimensions",
+      "dimensionScores": {
+        "geographic": 0.0-1.0,
+        "category": 0.0-1.0,
+        "topic": 0.0-1.0,
+        "maturity": 0.0-1.0
+      }
+    }
+  ]
+}
+
+## Guidelines
+- Base evaluation only on provided data — do not infer missing information
+- eligible=true only when ALL required dimensions score above 0.5
+- confidence reflects how clearly the data supports the determination
+- No personal identifiers in reasoning`
 
 // ─── Types ──────────────────────────────────────────────────────────────────
 
@@ -149,10 +182,17 @@ async function processEligibilityBatch(
   const results: EligibilityResult[] = []
   let tokensUsed = 0
 
-  const userPrompt = `CRITERIA: ${criteriaText}
+  // Sanitize user-supplied criteria
+  const { sanitized: safeCriteria } = sanitizeUserInput(criteriaText)
+
+  const userPrompt = `CRITERIA: ${safeCriteria}
 PROJECTS: ${JSON.stringify(anonymized)}
 Evaluate eligibility for each project.`
 
+  const MAX_PARSE_RETRIES = 2
+  let parseAttempts = 0
+  let response: Awaited<ReturnType<typeof openai.chat.completions.create>>
+
   try {
     const params = buildCompletionParams(model, {
       messages: [
@@ -160,11 +200,11 @@ Evaluate eligibility for each project.`
         { role: 'user', content: userPrompt },
       ],
       jsonMode: true,
-      temperature: 0.3,
+      temperature: 0.1,
       maxTokens: 4000,
     })
 
-    const response = await openai.chat.completions.create(params)
+    response = await openai.chat.completions.create(params)
     const usage = extractTokenUsage(response)
     tokensUsed = usage.totalTokens
 
@@ -183,12 +223,8 @@ Evaluate eligibility for each project.`
       status: 'SUCCESS',
     })
 
-    const content = response.choices[0]?.message?.content
-    if (!content) {
-      throw new Error('Empty response from AI')
-    }
-
-    const parsed = JSON.parse(content) as {
+    // Parse with retry logic
+    let parsed: {
       evaluations: Array<{
         project_id: string
         eligible: boolean
@@ -197,6 +233,38 @@ Evaluate eligibility for each project.`
       }>
     }
 
+    while (true) {
+      try {
+        const content = response.choices[0]?.message?.content
+        if (!content) {
+          throw new Error('Empty response from AI')
+        }
+        parsed = JSON.parse(content)
+        break
+      } catch (parseError) {
+        if (parseError instanceof SyntaxError && parseAttempts < MAX_PARSE_RETRIES) {
+          parseAttempts++
+          console.warn(`[AI Eligibility] JSON parse failed, retrying (${parseAttempts}/${MAX_PARSE_RETRIES})`)
+
+          // Retry the API call with hint
+          const retryParams = buildCompletionParams(model, {
+            messages: [
+              { role: 'system', content: AI_ELIGIBILITY_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
+      }
+    }
+
     // Map results back to real IDs
     for (const eval_ of parsed.evaluations || []) {
       const mapping = mappings.find((m) => m.anonymousId === eval_.project_id)