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handoff.md

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+---
+## HANDOFF CONTEXT
+GOAL
+----
+Continue implementation of IRT-Powered Adaptive Question Bank System after user configures GLM-5 model mapping for specific subagent categories.
+WORK COMPLETED
+--------------
+- Created comprehensive PRD (v1.1) from project-brief.md
+- Resolved 10 critical clarification questions with client:
+  1. Excel Import: Standardized across ALL tryouts
+  2. AI Generation: 1 request = 1 question, admin playground for testing, no approval workflow
+  3. Normalization: Optional manual/automatic control (system handles auto when sufficient data)
+  4. Rollback: Preserve IRT history, apply CTT to new sessions only
+  5. Admin Permissions: Not needed (WordPress handles per-site admins)
+  6. Dashboards: FastAPI Admin only
+  7. Rate Limiting: User-level reuse check + AI generation toggle
+  8. Student UX: Admin sees internal metrics, students only see primary score
+  9. Data Retention: Keep all data
+  10. Reporting: All 4 report types required
+- Created detailed technical implementation plan with 10 parallel subagents:
+  - Deep Agent 1: Core API + CTT Scoring
+  - Deep Agent 2: IRT Calibration Engine (recommended for GLM-5)
+  - Deep Agent 3: CAT Selection Logic (recommended for GLM-5)
+  - Deep Agent 4: AI Generation + OpenRouter (recommended for GLM-5)
+  - Deep Agent 5: WordPress Integration
+  - Deep Agent 6: Reporting System (recommended for GLM-5)
+  - Unspecified-High Agents: Database Schema, Excel Import/Export, Admin Panel, Normalization
+CURRENT STATE
+-------------
+- PRD.md file created (746 lines, v1.1)
+- project-brief.md exists (reference document)
+- No code implementation started yet
+- No git repository initialized
+- Working directory: /Users/dwindown/Applications/tryout-system
+- Session ID: ses_2f1bf9e3cffes96exBxyheOiYT
+PENDING TASKS
+-------------
+1. User configures GLM-5 model mapping for `deep` category (GLM-5 for algorithmic complexity)
+2. User configures GLM-4.7 model mapping for `unspecified-high` category (general implementation)
+3. Initialize git repository
+4. Create project structure (app/, models/, routers/, services/, tests/)
+5. Launch Unspecified-High Agent 1: Database Schema + ORM (BLOCKS all other agents)
+6. After schema complete: Launch Deep Agents 1-3 in parallel (Core API, IRT Calibration, CAT Selection)
+7. Launch Deep Agents 4-6 + Unspecified-High Agents 2-4 in parallel (AI Generation, WordPress, Reporting, Excel, Admin, Normalization)
+8. Integration testing and validation
+KEY FILES
+---------
+- PRD.md - Complete product requirements document (v1.1, 746 lines)
+- project-brief.md - Original technical specification reference
+IMPORTANT DECISIONS
+-------------------
+- 1 request = 1 question for AI generation (no batch)
+- Admin playground for AI testing (no approval workflow for student tests)
+- Normalization: Admin chooses manual/automatic; system handles auto when data sufficient
+- Rollback: Keep IRT historical scores, apply CTT only to new sessions
+- No admin permissions system (WordPress handles per-site admin access)
+- FastAPI Admin only (no custom dashboards)
+- Global AI generation toggle for cost control
+- User-level question reuse check (prevent duplicate difficulty exposure)
+- Admin sees internal metrics, students only see primary score
+- Keep all data indefinitely
+- All 4 report types required (Student, Item, Calibration, Tryout comparison)
+EXPLICIT CONSTRAINTS
+--------------------
+- Excel format is standardized across ALL tryouts (strict parser)
+- CTT formulas must match client Excel 100% (p = Σ Benar / Total Peserta)
+- IRT 1PL Rasch model only (b parameter, no a/c initially)
+- θ and b ∈ [-3, +3], NM and NN ∈ [0, 1000]
+- Normalization target: Mean=500±5, SD=100±5
+- Tech stack: FastAPI, PostgreSQL, SQLAlchemy, FastAPI Admin, OpenRouter (Qwen3 Coder 480B / Llama 3.3 70B)
+- Deployment: aaPanel VPS with Python Manager
+- No type error suppression (no `as any`, `@ts-ignore`)
+- Zero disruption to existing operations (non-destructive, additive)
+GLM-5 MODEL ALLOCATION RECOMMENDATION
+-----------------------------------
+Use GLM-5 for:
+- Deep Agent 2: IRT Calibration Engine (mathematical algorithms, sparse data handling)
+- Deep Agent 3: CAT Selection Logic (adaptive algorithms, termination conditions)
+- Deep Agent 4: AI Generation + OpenRouter (prompt engineering, robust parsing)
+- Deep Agent 6: Reporting System (complex aggregation, multi-dimensional analysis)
+Use GLM-4.7 for:
+- Deep Agent 1: Core API + CTT Scoring (straightforward formulas)
+- Deep Agent 5: WordPress Integration (standard REST API)
+- Unspecified-High Agents: Database Schema, Excel Import/Export, Admin Panel, Normalization (well-defined tasks)
+NOTE: Model mapping is controlled by category configuration in system, not by direct model specification in task() function.
+CONTEXT FOR CONTINUATION
+------------------------
+- User is currently configuring GLM-5 model mapping for specific categories
+- After model mapping is configured, implementation should start with Database Schema (Unspecified-High Agent 1) as it blocks all other work
+- Parallel execution strategy: Never run sequential when parallel is possible - all independent work units run simultaneously
+- Use `task(category="...", load_skills=[], run_in_background=true)` pattern for parallel delegation
+- All delegated work must include: TASK, EXPECTED OUTCOME, REQUIRED TOOLS, MUST DO, MUST NOT DO, CONTEXT (6-section prompt structure)
+- Verify results after delegation: DOES IT WORK? DOES IT FOLLOW PATTERNS? EXPECTED RESULT ACHIEVED?
+- Run `lsp_diagnostics` on changed files before marking tasks complete
+- This is NOT a git repository yet - will need to initialize before any version control operations
+---