
# Unfamiliar Pipeline Test

**Timestamp:** 2026-03-14 03:50:11 UTC
**Target repo:** `/home/erinmeaker/Documents/source/lifeLevel`

## Phase 3: Static Analysis

Files: 61
Modules: 30
Entry points: 2

Top scored files:
  backend/tests/conftest.py: 150 (entry point, hub (imported by 6 files))
  backend/app.py: 100 (entry point)
  backend/config.py: 50 (hub (imported by 3 files))
  backend/database.py: 50 (hub (imported by 15 files))
  backend/tests/test_activities_queries.py: 50 (complex (score: 73), test file)
Module size distribution: {1: 24, 2: 3, 4: 1, 6: 1, 21: 1}
Singleton modules: 24
Total import edges: 54
Edges per file: 0.89
Provider: glm
Model override: glm-4.7-Flash

## Phase 6: Briefing Generation

Token budget: 8,000
Context size: 28,767 chars (~7,191 tokens)
Model class: ChatZhipuAI
Mission model class: ChatZhipuAI
Max output tokens: 4095

### Briefing Result

Context tokens: ~7,191
Summary length: 824 chars
Tech stack: ['Flask (Python)', 'React (TypeScript)', 'SQLite', 'Vite', 'pytest', 'Flask-CORS', 'click']
Modules described: 30
Security posture: The application uses environment-based configuration with no hardcoded secrets. Database connections are managed through context managers with proper transaction handling. The backup command includes 

**Full summary:**

```
This is a skill tracking application called 'lifeLevel' that allows users to practice skating skills through a structured progression system. The backend is built with Flask and uses SQLite for data persistence, featuring modules for activities, logs, and progress tracking. Users can log completed activities to earn XP, which advances them through levels and branches within a skill. The frontend is a React/TypeScript application with components for displaying activities, progress visualization, and user interaction. The system includes database migrations, seed data functionality, and CLI commands for database initialization and backup. The architecture follows a feature-based pattern with separate modules for activities, logs, and progress, and uses dependency injection for database and configuration management.
```

  [0] backend: Main backend module containing the Flask application factory, configuration mana
  [1] frontend/src/features/activities/components: React components for displaying and interacting with activities, including activ
  [2] frontend/src/features/progress/components: React components for visualizing progress data, including branch breakdowns, pro
  [3] frontend/src/features/activities: Frontend API layer and type definitions for the activities feature, handling dat
  [4] frontend/src/features/progress: Frontend API layer and type definitions for the progress feature, handling data 
  [5] frontend/src/shared/components: Shared UI components used across the application, including error boundaries and
  [6] backend/features/activities: Backend API endpoints and query logic for activities, including listing activiti
  [7] backend/features/logs: Backend API endpoints and query logic for logging activities, creating log entri
  [8] backend/features/progress: Backend logic for calculating and tracking progress, including level calculation
  [9] backend/features/shared: Shared backend utilities and helper functions used across features, including cu
  [10] backend/models: Database models defining the schema for skills, branches, levels, activities, lo
  [11] backend/schema: Database schema definitions and migration management, including SQL migration sc
  [12] backend/tests (security): Test suite covering queries, routes, and level calculations, with fixtures for i
  [13] frontend/src: Main frontend application entry point and routing, including the App component a
  [14] backend (utilities): Additional backend utilities including database seeding functionality and CLI co
  [15] backend/requirements.txt: Description not provided by LLM.
  [16] backend/tests/__init__.py: Description not provided by LLM.
  [17] frontend/.prettierrc: Description not provided by LLM.
  [18] frontend/eslint.config.js: Description not provided by LLM.
  [19] frontend/package-lock.json: Description not provided by LLM.
  [20] frontend/package.json: Description not provided by LLM.
  [21] frontend/src/App.tsx: Description not provided by LLM.
  [22] frontend/src/features/activities/components/LevelUpOverlay.tsx: Description not provided by LLM.
  [23] frontend/src/features/progress/components/CompactProgressBar.tsx: Description not provided by LLM.
  [24] frontend/src/main.tsx: Description not provided by LLM.
  [25] frontend/src/shared/branchColors.ts: Description not provided by LLM.
  [26] frontend/src/shared/components/ErrorState.tsx: Description not provided by LLM.
  [27] frontend/src/shared/constants.ts: Description not provided by LLM.
  [28] frontend/src/shared/utils.ts: Description not provided by LLM.
  [29] frontend/vite.config.ts: Description not provided by LLM.
Cooldown 60s before mission generation...

## Phase 7: Mission Generation

Created fresh model for missions: ChatZhipuAI
Categories: ['testing']
Token budget per category: ~1,142

### Category: testing

5 missions, 2 chains

### The Test Fixture Mystery
**Difficulty:** quick

*The night was dark and the test suite was silent. You needed to understand how the fixtures were setting the stage for every investigation. Without knowing the setup, you couldn't trust any of the evidence you'd find later.*

Investigate the test configuration and fixtures to understand how the test suite sets up the database and test data.

**Files to investigate:**
- `backend/tests/conftest.py` — Contains the test fixtures that set up the database, create test users, and provide reusable test data.

**Completion:** Identify and explain at least 3 different fixtures used in the test suite and how they prepare the test environment.

*The pieces of the puzzle fell into place. You now understand how the test fixtures prepare the scene, creating a controlled environment where every test is an isolated investigation. The stage was set, and you were ready to dig deeper.*

### The Query Trail
**Difficulty:** medium
**Prerequisites:** The Test Fixture Mystery

*The data was scattered across the database, and you needed to know if the queries were pulling the right threads. Every query was a potential weak link in the chain of evidence.*

Follow the data trail through the query tests to understand how database operations are verified and validated.

**Files to investigate:**
- `backend/tests/test_activities_queries.py` — Tests for activities-related database queries, verifying correct data retrieval and filtering.
- `backend/tests/test_log_queries.py` — Tests for log-related database queries, checking log entry retrieval and aggregation.
- `backend/tests/test_progress_queries.py` — Tests for progress-related database queries, validating progress tracking and XP calculations.

**Completion:** Explain how at least two different query tests verify database operations and what assertions they use.

*You traced the data through the query tests, seeing exactly how each operation was verified. The queries were solid, pulling the right threads at the right time. The evidence was consistent, and the database was telling the truth.*

### The Route Detective
**Difficulty:** medium
**Prerequisites:** The Test Fixture Mystery

*The routes were the arteries of the application, carrying requests and responses through the system. But were they carrying the right cargo? You needed to check the endpoints yourself.*

Investigate the route tests to understand how API endpoints are verified and what edge cases are covered.

**Files to investigate:**
- `backend/tests/test_activities_routes.py` — Tests for activities API endpoints, verifying request handling and response formatting.
- `backend/tests/test_log_routes.py` — Tests for log API endpoints, checking log creation, retrieval, and validation.
- `backend/tests/test_progress_routes.py` — Tests for progress API endpoints, validating progress tracking and level calculations.

**Completion:** Identify at least one test that covers an error scenario and explain how the route handles it.

*You examined the route tests, seeing how each endpoint was put through its paces. The routes were handling requests correctly, but you noticed some gaps in the coverage. The investigation wasn't complete, but you had a clear picture of what needed to be fixed.*

### The Leveling Up Enigma
**Difficulty:** deep_dive
**Prerequisites:** The Query Trail

*The leveling system was a puzzle wrapped in an enigma. XP accumulated, levels advanced, and branches opened up. But how did the math work? You needed to crack the code behind the progression.*

Unravel the mystery of level calculations by investigating how the test suite verifies the progression system.

**Files to investigate:**
- `backend/tests/test_level_calculator.py` — Comprehensive tests for the level calculation logic, covering various XP scenarios and progression paths.

**Completion:** Explain the level calculation logic and identify at least 3 different test cases that verify different progression scenarios.

*The enigma was solved. You understood how the level calculations worked, tracking XP accumulation and level progression through the branches. The math was sound, and the tests proved it. The progression system was working exactly as designed.*

### The Coverage Conundrum
**Difficulty:** medium
**Prerequisites:** The Route Detective
**Security relevant:** Yes

*The city was full of shadows, and the test suite was hiding some of them. You needed to find the gaps in coverage—the untested code that could be hiding vulnerabilities or bugs.*

Investigate the test suite to understand what code is being tested and what gaps remain in the coverage.

**Files to investigate:**
- `backend/tests/__init__.py` — Test suite initialization and coverage analysis, identifying which files are tested and which remain in the shadows.

**Completion:** Identify at least 3 files that are not covered by tests and explain why this is a concern.

*You found the shadows in the coverage. Some files were completely untested, leaving potential vulnerabilities exposed. The investigation revealed that while the core features were covered, the edges were dark. It was time to bring more light to the codebase.*

## Summary

Total missions generated: 5
Categories tested: 1
Difficulty breakdown: {'quick': 1, 'medium': 3, 'deep_dive': 1}
Root missions (no prereqs): 1