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Pony-Alpha-2-Dataset-Training/datasets/01-coding-approach/coding-approach.jsonl
Pony Alpha 2 68453089ee feat: initial Alpha Brain 2 dataset release 
Massive training corpus for AI coding models containing:
- 10 JSONL training datasets (641+ examples across coding, reasoning, planning, architecture, communication, debugging, security, workflows, error handling, UI/UX)
- 11 agent behavior specifications (explorer, planner, reviewer, debugger, executor, UI designer, Linux admin, kernel engineer, security architect, automation engineer, API architect)
- 6 skill definition files (coding, API engineering, kernel, Linux server, security architecture, server automation, UI/UX)
- Master README with project origin story and philosophy

Built by Pony Alpha 2 to help AI models learn expert-level coding approaches.
2026-03-13 16:26:29 +04:00

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{"instruction": "Create a Python REST API endpoint for user registration with email validation", "approach": "1. Check if users.py exists and read it first\n2. Add email validation function using regex\n3. Create POST endpoint with request validation\n4. Hash password before storing\n5. Return 201 on success, 400 on validation error", "code": "import re\nfrom flask import request, jsonify\nimport bcrypt\n\n@app.route('/api/users/register', methods=['POST'])\ndef register():\n data = request.get_json()\n \n # Validate email format at boundary\n email = data.get('email', '').strip()\n if not re.match(r'^[\\w\\.-]+@[\\w\\.-]+\\.\\w+$', email):\n return jsonify({'error': 'Invalid email format'}), 400\n \n # Hash password - security first\n password = data.get('password', '')\n if len(password) < 8:\n return jsonify({'error': 'Password too short'}), 400\n \n hashed = bcrypt.hashpw(password.encode(), bcrypt.gensalt())\n \n # Store user (trust internal db function)\n user_id = db_create_user(email, hashed)\n \n return jsonify({'id': user_id, 'email': email}), 201", "explanation": "Read existing code to avoid duplication. Validate at API boundary (email format, password length) but trust internal db_create_user. Security-first with password hashing. No over-engineering - simple regex for email. Return appropriate HTTP status codes."}
{"instruction": "Create a TypeScript function to validate user input with runtime type checking", "approach": "1. Read existing validation file to understand patterns\n2. Create simple type guard function\n3. Validate at input boundary only\n4. Return typed result or throw\n5. No unnecessary validation layers", "code": "interface UserInput {\n name: string;\n email: string;\n age: number;\n}\n\nfunction isValidUserInput(data: unknown): data is UserInput {\n if (typeof data !== 'object' || data === null) return false;\n \n const d = data as Record<string, unknown>;\n return (\n typeof d.name === 'string' &&\n typeof d.email === 'string' &&\n typeof d.age === 'number'\n );\n}\n\nfunction processUser(data: unknown): UserInput {\n if (!isValidUserInput(data)) {\n throw new Error('Invalid user input');\n }\n \n // Trust internal code from here\n return saveUser(data);\n}", "explanation": "Validate once at the boundary using type guards. No over-engineering with schema libraries for simple types. Trust internal code after validation. Clean separation - invalid data never reaches internal logic. Delete unused validation middlewares."}
{"instruction": "Write a Go function to query database with connection pooling", "approach": "1. Read existing db.go to check connection setup\n2. Use existing connection pool - don't create new one\n3. Simple SELECT query with context timeout\n4. Scan directly to struct\n5. Close rows in defer", "code": "type User struct {\n ID int `db:\"id\"`\n Name string `db:\"name\"`\n Email string `db:\"email\"`\n}\n\nfunc GetUserByID(ctx context.Context, db *sql.DB, id int) (*User, error) {\n ctx, cancel := context.WithTimeout(ctx, 5*time.Second)\n defer cancel()\n \n var user User\n err := db.QueryRowContext(ctx,\n \"SELECT id, name, email FROM users WHERE id = ?\", id).\n Scan(&user.ID, &user.Name, &user.Email)\n \n if err == sql.ErrNoRows {\n return nil, nil // User not found\n }\n if err != nil {\n return nil, err // Trust internal error handling\n }\n \n return &user, nil\n}", "explanation": "Read existing db setup before adding code. Use established connection pool. Context timeout prevents hanging. Simple query - no ORM needed. Handle ErrNoRows explicitly. Trust internal code to handle errors. No backwards compat - return nil for not found, not error."}
{"instruction": "Create a Rust function to parse CSV file with proper error handling", "approach": "1. Check if csv module exists first\n2. Use existing csv library\n3. Minimal parsing - only needed fields\n4. Return Result type for error handling\n5. Clean error messages", "code": "use std::fs::File;\nuse std::path::Path;\n\n#[derive(Debug)]\nstruct Record {\n name: String,\n value: i32,\n}\n\nfn parse_csv(path: &Path) -> Result<Vec<Record>, String> {\n let file = File::open(path)\n .map_err(|e| format!(\"Failed to open file: {}\", e))?;\n \n let mut rdr = csv::Reader::from_reader(file);\n let mut records = Vec::new();\n \n for result in rdr.deserialize() {\n let record: Record = result\n .map_err(|e| format!(\"Parse error: {}\", e))?;\n records.push(record);\n }\n \n Ok(records)\n}", "explanation": "Read existing code to see CSV patterns. Parse only needed fields. Use Result type for explicit error handling. Clean error messages at boundary. Trust csv library internals. No over-engineering with custom parsers. Delete unused parsing code."}
{"instruction": "Create a Python authentication decorator for API endpoints", "approach": "1. Read existing auth.py to understand token structure\n2. Create simple decorator function\n3. Validate JWT at boundary\n4. Extract user ID from token\n5. Pass user to endpoint - no revalidation", "code": "import jwt\nfrom functools import wraps\nfrom flask import request, jsonify\n\ndef require_auth(f):\n @wraps(f)\n def decorated(*args, **kwargs):\n token = request.headers.get('Authorization', '').replace('Bearer ', '')\n \n if not token:\n return jsonify({'error': 'No token'}), 401\n \n try:\n # Validate at boundary\n payload = jwt.decode(token, SECRET_KEY, algorithms=['HS256'])\n user_id = payload['user_id']\n except jwt.InvalidTokenError:\n return jsonify({'error': 'Invalid token'}), 401\n \n # Trust internal code - pass user_id\n return f(user_id=user_id, *args, **kwargs)\n \n return decorated\n\n@app.route('/api/profile')\n@require_auth\ndef get_profile(user_id):\n # No need to revalidate - trust decorator\n return jsonify(get_user_profile(user_id))", "explanation": "Read existing auth code to match patterns. Validate JWT once at boundary. Extract user_id and trust internal code. No revalidation in endpoints. Security-first with proper error handling. Clean separation of concerns. Delete unused middleware."}
{"instruction": "Write a TypeScript function to safely parse JSON input", "approach": "1. Check existing parsing utilities\n2. Create type-safe parser\n3. Validate at input boundary\n4. Return typed result or error\n5. No try-catch in internal code", "code": "interface Config {\n apiUrl: string;\n timeout: number;\n}\n\nfunction parseConfig(input: string): Config | null {\n try {\n const data = JSON.parse(input);\n \n // Validate at boundary\n if (typeof data?.apiUrl !== 'string' || typeof data?.timeout !== 'number') {\n return null;\n }\n \n return { apiUrl: data.apiUrl, timeout: data.timeout };\n } catch {\n return null;\n }\n}\n\nfunction useConfig(input: string): void {\n const config = parseConfig(input);\n if (!config) {\n throw new Error('Invalid config');\n }\n \n // Trust internal code - no more validation\n initializeApi(config);\n}", "explanation": "Validate once at boundary. Return null for invalid input. Internal code trusts validated data. No over-engineering with schema libraries. Clean error handling at edge only. Delete unused validation middleware. Type-safe without excess complexity."}
{"instruction": "Create a Go middleware for request logging", "approach": "1. Read existing middleware.go\n2. Add simple logging middleware\n3. Log at boundary only\n4. Don't log sensitive data\n5. Chain properly with existing middleware", "code": "func loggingMiddleware(next http.Handler) http.Handler {\n return http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {\n start := time.Now()\n \n // Create response writer wrapper to capture status\n wrapped := &responseWrapper{ResponseWriter: w, status: 200}\n \n next.ServeHTTP(wrapped, r)\n \n // Log at boundary - no internal logging\n log.Printf(\"%s %s %d %v\",\n r.Method,\n r.URL.Path,\n wrapped.status,\n time.Since(start),\n )\n })\n}\n\ntype responseWrapper struct {\n http.ResponseWriter\n status int\n}\n\nfunc (rw *responseWrapper) WriteHeader(status int) {\n rw.status = status\n rw.ResponseWriter.WriteHeader(status)\n}", "explanation": "Read existing middleware to understand patterns. Log at HTTP boundary only. Don't log sensitive data. Simple timing and status logging. Trust internal code to handle its own errors. No over-engineering with structured logging. Delete unused logging code."}
{"instruction": "Write a Python function to process uploaded CSV file", "approach": "1. Check existing file processing code\n2. Validate file type at upload\n3. Use pandas if already imported\n4. Clean data at boundary\n5. Return structured data", "code": "import pandas as pd\nfrom werkzeug.datastructures import FileStorage\n\ndef process_csv_upload(file: FileStorage) -> list[dict]:\n # Validate at boundary\n if not file.filename.endswith('.csv'):\n raise ValueError('Only CSV files allowed')\n \n # Read and validate structure\n df = pd.read_csv(file.stream)\n \n required_columns = ['name', 'email', 'amount']\n missing = [c for c in required_columns if c not in df.columns]\n if missing:\n raise ValueError(f'Missing columns: {missing}')\n \n # Clean data - trust internal processing\n df = df[required_columns].dropna()\n df['email'] = df['email'].str.lower().str.strip()\n \n # Convert to dict - internal code trusts this\n return df.to_dict('records')", "explanation": "Validate file type and structure at boundary. Clean data once at entry point. Use pandas if already in project. No over-engineering with custom parsers. Trust internal code after validation. Delete unused data cleaning functions. Minimal changes to existing patterns."}
{"instruction": "Create a Rust function to hash passwords with bcrypt", "approach": "1. Check existing auth module\n2. Use bcrypt crate\n3. Hash before storing\n4. Validate password length at boundary\n5. Return Result type", "code": "use bcrypt::{hash, verify, DEFAULT_COST};\n\nfn hash_password(password: &str) -> Result<String, String> {\n // Validate at boundary\n if password.len() < 8 {\n return Err(\"Password too short\".to_string());\n }\n \n // Security-first hashing\n hash(password, DEFAULT_COST)\n .map_err(|e| format!(\"Hashing failed: {}\", e))\n}\n\nfn verify_password(password: &str, hash: &str) -> bool {\n // Trust bcrypt library internals\n verify(password, hash).unwrap_or(false)\n}", "explanation": "Security-first with bcrypt. Validate password length at boundary only. Use standard library - no custom crypto. Return Result for explicit error handling. Trust internal bcrypt implementation. No over-engineering with custom salt. Delete any insecure hashing code."}
{"instruction": "Write a TypeScript class for API client with rate limiting", "approach": "1. Read existing API client code\n2. Add simple rate limiting\n3. Queue requests at boundary\n4. Use existing fetch wrapper\n5. Minimal state management", "code": "class ApiClient {\n private queue: Array<() => Promise<any>> = [];\n private processing = false;\n private readonly rateLimitMs = 100;\n private lastRequest = 0;\n\n async request(url: string, options: RequestInit): Promise<any> {\n // Rate limit at boundary\n const wait = this.rateLimitMs - (Date.now() - this.lastRequest);\n if (wait > 0) {\n await new Promise(r => setTimeout(r, wait));\n }\n this.lastRequest = Date.now();\n\n // Trust internal fetch\n const response = await fetch(url, options);\n if (!response.ok) {\n throw new Error(`HTTP ${response.status}`);\n }\n return response.json();\n }\n\n // Trust internal code - no rate limiting needed\n private async processQueue() {\n while (this.queue.length > 0) {\n const fn = this.queue.shift()!;\n await fn();\n }\n this.processing = false;\n }\n}", "explanation": "Rate limit at boundary only. Simple time-based limiting. Trust internal fetch implementation. No over-engineering with token buckets. Clean state management. Delete unused queue code if not needed. Minimal changes to existing client."}
{"instruction": "Create a Go function to validate and sanitize HTML input", "approach": "1. Read existing validation code\n2. Use bluemonday for sanitization\n3. Validate at input boundary\n4. Return clean HTML\n5. Trust internal rendering", "code": "import \"github.com/microcosm-cc/bluemonday\"\n\nvar p = bluemonday.UGCPolicy()\n\nfunc sanitizeHTML(input string) string {\n // Sanitize at boundary\n clean := p.Sanitize(input)\n \n // Remove any remaining scripts\n clean = p.SanitizeStyles(clean)\n \n return clean\n}\n\nfunc saveComment(userInput string) error {\n // Validate and clean at boundary\n clean := sanitizeHTML(userInput)\n if clean == \"\" {\n return errors.New(\"Empty comment after sanitization\")\n }\n \n // Trust internal storage - no revalidation\n return db.SaveComment(clean)\n}", "explanation": "Security-first with HTML sanitization. Validate at boundary using bluemonday. Trust internal storage code. No over-engineering with custom sanitizers. Clean separation - dirty data never enters system. Delete unused sanitization functions. Minimal changes to existing patterns."}
{"instruction": "Write a Python function to cache expensive database queries", "approach": "1. Check existing cache implementation\n2. Use functools.lru_cache for simplicity\n3. Cache at boundary only\n4. Invalidate on writes\n5. Trust internal query logic", "code": "from functools import lru_cache\nfrom datetime import timedelta\nimport time\n\n@lru_cache(maxsize=128)\ndef get_user_profile_cached(user_id: int) -> dict:\n # Trust internal query - no caching inside\n return db_query_user(user_id)\n\ndef invalidate_user_cache(user_id: int):\n # Simple invalidation\n get_user_profile_cached.cache_clear()\n\ndef update_user_profile(user_id: int, data: dict):\n # Update then invalidate\n db.update_user(user_id, data)\n invalidate_user_cache(user_id)", "explanation": "Cache at boundary with lru_cache. Trust internal query logic. Simple invalidation on writes. No over-engineering with Redis. Minimal state management. Delete unused cache layers. Read existing cache patterns first."}
{"instruction": "Create a TypeScript error handler for Express API", "approach": "1. Read existing error handling\n2. Add centralized error middleware\n3. Handle errors at boundary\n4. Log and return appropriate status\n5. No error suppression", "code": "interface AppError extends Error {\n statusCode?: number;\n isOperational?: boolean;\n}\n\nfunction errorHandler(\n err: AppError,\n req: Request,\n res: Response,\n next: NextFunction\n) {\n // Log at boundary\n console.error(err);\n\n const statusCode = err.statusCode || 500;\n const message = err.isOperational\n ? err.message\n : 'Internal server error';\n\n res.status(statusCode).json({\n error: message,\n ...(process.env.NODE_ENV === 'development' && { stack: err.stack })\n });\n}\n\napp.use(errorHandler);\n\n// Usage - trust internal code\nfunction getUser(id: string) {\n const user = db.findUser(id);\n if (!user) {\n const error = new Error('User not found') as AppError;\n error.statusCode = 404;\n error.isOperational = true;\n throw error;\n }\n return user;\n}", "explanation": "Centralized error handling at boundary. Log all errors. Return appropriate status codes. Trust internal code to throw errors. No error suppression. Clean separation of concerns. Delete unused error handlers. Minimal changes to existing patterns."}
{"instruction": "Write a Go function to validate email address format", "approach": "1. Read existing validation code\n2. Use standard library for email validation\n3. Validate at boundary\n4. Return boolean\n5. No custom regex", "code": "import (\n \"net/mail\"\n \"strings\"\n)\n\nfunc isValidEmail(email string) bool {\n // Validate at boundary using stdlib\n addr, err := mail.ParseAddress(email)\n if err != nil {\n return false\n }\n \n // Additional checks\n if !strings.Contains(addr.Address, \"@\") {\n return false\n }\n \n return true\n}\n\nfunc createUser(email string) error {\n // Validate at boundary\n if !isValidEmail(email) {\n return errors.New(\"invalid email\")\n }\n \n // Trust internal storage\n return db.SaveUser(email)\n}", "explanation": "Use standard library for validation. Validate at boundary only. Trust internal code after validation. No over-engineering with custom regex. Simple boolean return. Delete unused email validators. Minimal changes to existing patterns."}
{"instruction": "Create a Python CLI tool with argument validation", "approach": "1. Check existing CLI structure\n2. Use argparse for validation\n3. Validate at entry point\n4. Clean error messages\n5. Trust internal functions", "code": "import argparse\nimport sys\n\ndef parse_args() -> argparse.Namespace:\n parser = argparse.ArgumentParser(\n description='Process data files',\n formatter_class=argparse.ArgumentDefaultsHelpFormatter\n )\n \n parser.add_argument(\n 'input',\n help='Input file path'\n )\n parser.add_argument(\n '--output', '-o',\n required=True,\n help='Output file path'\n )\n parser.add_argument(\n '--format',\n choices=['json', 'csv'],\n default='json',\n help='Output format'\n )\n \n # Validate at boundary\n args = parser.parse_args()\n \n return args\n\ndef main():\n try:\n args = parse_args()\n \n # Trust internal processing\n process_file(\n args.input,\n args.output,\n args.format\n )\n print('Success!')\n except Exception as e:\n print(f'Error: {e}', file=sys.stderr)\n sys.exit(1)", "explanation": "Validate at CLI boundary using argparse. Clear error messages. Trust internal processing functions. No over-engineering with custom validators. Clean exit codes. Delete unused argument parsers. Minimal changes to existing CLI structure."}
{"instruction": "Write a Rust function to read and parse configuration file", "approach": "1. Check existing config loading\n2. Use serde for JSON parsing\n3. Validate at boundary\n4. Return typed config\n5. Clean error messages", "code": "use serde::Deserialize;\nuse std::fs;\nuse std::path::Path;\n\n#[derive(Debug, Deserialize)]\nstruct Config {\n database_url: String,\n port: u16,\n #[serde(default = \"default_workers\")]\n workers: usize,\n}\n\nfn default_workers() -> usize { 4 }\n\nfn load_config(path: &Path) -> Result<Config, String> {\n // Read and validate at boundary\n let content = fs::read_to_string(path)\n .map_err(|e| format!(\"Failed to read config: {}\", e))?;\n \n let config: Config = serde_json::from_str(&content)\n .map_err(|e| format!(\"Invalid config JSON: {}\", e))?;\n \n // Validate at boundary\n if config.port == 0 {\n return Err(\"Port cannot be zero\".to_string());\n }\n \n Ok(config)\n}\n\nfn use_config(path: &Path) -> Result<(), String> {\n let config = load_config(path)?;\n \n // Trust internal code - no revalidation\n start_server(config)\n}", "explanation": "Load and validate config at boundary. Use serde for type-safe parsing. Clean error messages. Trust internal code after validation. No over-engineering with config libraries. Delete unused config loaders. Minimal changes to existing patterns."}
{"instruction": "Create a TypeScript function to debounce user input", "approach": "1. Read existing debounce implementations\n2. Create simple debounce utility\n3. Apply at input boundary\n4. Trust internal handlers\n5. No multiple debounce layers", "code": "function debounce<T extends (...args: any[]) => any>(\n fn: T,\n delay: number\n): (...args: Parameters<T>) => void {\n let timeoutId: ReturnType<typeof setTimeout>;\n \n return (...args: Parameters<T>) => {\n clearTimeout(timeoutId);\n timeoutId = setTimeout(() => fn(...args), delay);\n };\n}\n\n// Usage - debounce at boundary\nconst debouncedSearch = debounce((query: string) => {\n // Trust internal search - no debounce here\n performSearch(query);\n}, 300);\n\ninputElement.addEventListener('input', (e) => {\n const query = (e.target as HTMLInputElement).value;\n debouncedSearch(query);\n});", "explanation": "Debounce at input boundary only. Trust internal search function. No multiple debounce layers. Simple timer-based implementation. Delete unused debounce utilities. Minimal changes to existing patterns. Clean separation of concerns."}
{"instruction": "Write a Go function to handle file upload with size limit", "approach": "1. Check existing upload handlers\n2. Add size limit at boundary\n3. Validate file type\n4. Stream to disk\n5. Trust internal processing", "code": "const maxUploadSize = 10 << 20 // 10MB\n\nfunc uploadHandler(w http.ResponseWriter, r *http.Request) {\n // Enforce limit at boundary\n r.Body = http.MaxBytesReader(w, r.Body, maxUploadSize)\n \n if err := r.ParseMultipartForm(maxUploadSize); err != nil {\n http.Error(w, \"File too large\", http.StatusBadRequest)\n return\n }\n \n file, header, err := r.FormFile(\"file\")\n if err != nil {\n http.Error(w, \"Invalid file\", http.StatusBadRequest)\n return\n }\n defer file.Close()\n \n // Validate type at boundary\n if !strings.HasSuffix(header.Filename, \".csv\") {\n http.Error(w, \"Only CSV files allowed\", http.StatusBadRequest)\n return\n }\n \n // Save and trust internal processing\n dst, _ := os.Create(\"uploads/\" + header.Filename)\n defer dst.Close()\n io.Copy(dst, file)\n \n processUploadedFile(dst.Name())\n}", "explanation": "Enforce size limit at boundary. Validate file type early. Stream to disk efficiently. Trust internal processing after validation. No over-engineering with multiple checks. Delete unused upload middleware. Clean error handling. Minimal changes."}
{"instruction": "Create a Python decorator for timing function execution", "approach": "1. Check existing monitoring code\n2. Add simple timing decorator\n3. Log at boundary\n4. No timing inside functions\n5. Minimal overhead", "code": "import time\nimport functools\n\ndef timed(func):\n @functools.wraps(func)\n def wrapper(*args, **kwargs):\n start = time.perf_counter()\n result = func(*args, **kwargs)\n elapsed = time.perf_counter() - start\n \n # Log at boundary\n print(f'{func.__name__} took {elapsed:.4f}s')\n \n return result\n return wrapper\n\n@timed\ndef process_data(data):\n # Trust internal code - no timing here\n return expensive_operation(data)", "explanation": "Add timing at boundary only. Minimal overhead with perf_counter. Trust internal function logic. No timing code inside functions. Clean logging. Delete unused timing code. Simple decorator pattern. Read existing monitoring patterns first."}
{"instruction": "Write a TypeScript function to validate phone numbers", "approach": "1. Read existing validation code\n2. Use libphonenumber-js or simple regex\n3. Validate at input boundary\n4. Return normalized format\n5. Trust internal storage", "code": "import { parsePhoneNumber, isValidPhoneNumber } from 'libphonenumber-js';\n\nfunction validatePhone(input: string): string | null {\n try {\n // Validate at boundary\n if (!isValidPhoneNumber(input, 'US')) {\n return null;\n }\n \n // Normalize format\n const phoneNumber = parsePhoneNumber(input, 'US');\n return phoneNumber?.format('E.164') || null;\n } catch {\n return null;\n }\n}\n\nfunction saveUserPhone(phone: string) {\n const normalized = validatePhone(phone);\n if (!normalized) {\n throw new Error('Invalid phone number');\n }\n \n // Trust internal storage\n db.saveUserPhone(normalized);\n}", "explanation": "Validate at input boundary using libphonenumber. Normalize format once. Trust internal storage code. No over-engineering with multiple validation layers. Clean error handling. Delete unused phone validators. Minimal changes to existing patterns."}
{"instruction": "Create a Go function to generate secure random tokens", "approach": "1. Read existing token generation\n2. Use crypto/rand for security\n3. Generate at boundary\n4. Return base64 encoded\n5. No custom RNG", "code": "import (\n \"crypto/rand\"\n \"encoding/base64\"\n \"errors\"\n)\n\nfunc generateToken() (string, error) {\n // Security-first: use crypto/rand\n b := make([]byte, 32)\n _, err := rand.Read(b)\n if err != nil {\n return \"\", errors.New(\"failed to generate token\")\n }\n \n return base64.URLEncoding.EncodeToString(b), nil\n}\n\nfunc createSession() (string, error) {\n token, err := generateToken()\n if err != nil {\n return \"\", err\n }\n \n // Trust internal storage\n return token, db.SaveSession(token)\n}", "explanation": "Security-first with crypto/rand. Generate at boundary only. No custom RNG implementations. Base64 encode for storage. Trust internal session code. Delete any insecure token generators. Minimal changes to existing patterns. Clean error handling."}
{"instruction": "Write a Python function to retry failed database operations", "approach": "1. Check existing retry logic\n2. Add simple retry decorator\n3. Retry at boundary only\n4. Exponential backoff\n5. Trust internal queries", "code": "import time\nimport functools\n\ndef retry(max_attempts: int = 3, delay: float = 1.0):\n def decorator(func):\n @functools.wraps(func)\n def wrapper(*args, **kwargs):\n last_error = None\n for attempt in range(max_attempts):\n try:\n return func(*args, **kwargs)\n except Exception as e:\n last_error = e\n if attempt < max_attempts - 1:\n time.sleep(delay * (2 ** attempt))\n raise last_error\n return wrapper\n return decorator\n\n@retry(max_attempts=3)\ndef fetch_user(user_id: int):\n # Trust internal query - no retry here\n return db.query('SELECT * FROM users WHERE id = %s', user_id)", "explanation": "Retry at boundary only. Exponential backoff for reliability. Trust internal query logic. No over-engineering with circuit breakers. Clean decorator pattern. Delete unused retry code. Read existing patterns first. Minimal changes."}
{"instruction": "Create a TypeScript function to deep clone objects", "approach": "1. Read existing clone utilities\n2. Use structuredClone if available\n3. Fallback to simple implementation\n4. Clone at boundary\n5. Trust internal code", "code": "function deepClone<T>(obj: T): T {\n // Use native if available\n if (typeof structuredClone !== 'undefined') {\n return structuredClone(obj);\n }\n \n // Simple fallback\n return JSON.parse(JSON.stringify(obj));\n}\n\nfunction processInput(data: unknown): MyData {\n // Clone at boundary\n const cloned = deepClone(data);\n \n // Trust internal processing - no cloning needed\n return transform(cloned);\n}", "explanation": "Use native structuredClone. Simple JSON fallback. Clone at boundary only. Trust internal code after cloning. No over-engineering with custom deep clone. Delete unused clone utilities. Minimal changes. Read existing patterns first."}
{"instruction": "Write a Go function to validate UUID format", "approach": "1. Check existing UUID validation\n2. Use google/uuid package\n3. Validate at boundary\n4. Return parsed UUID\n5. Trust internal code", "code": "import \"github.com/google/uuid\"\n\nfunc parseUUID(input string) (uuid.UUID, error) {\n // Validate at boundary\n id, err := uuid.Parse(input)\n if err != nil {\n return uuid.Nil, errors.New(\"invalid UUID format\")\n }\n \n return id, nil\n}\n\nfunc getUserByID(idStr string) (*User, error) {\n // Validate at boundary\n id, err := parseUUID(idStr)\n if err != nil {\n return nil, err\n }\n \n // Trust internal query - no revalidation\n return db.QueryUser(id)\n}", "explanation": "Use standard uuid package. Validate at boundary only. Return parsed UUID for internal use. Trust internal code after validation. No over-engineering with custom UUID parsing. Delete unused validators. Minimal changes. Clean error handling."}
{"instruction": "Create a Python context manager for database transactions", "approach": "1. Read existing transaction handling\n2. Create simple context manager\n3. Commit/rollback at boundary\n4. Trust internal queries\n5. Clean error handling", "code": "from contextlib import contextmanager\nfrom typing import Generator\n\n@contextmanager\ndef db_transaction(conn) -> Generator:\n try:\n yield conn\n conn.commit()\n except Exception:\n conn.rollback()\n raise\n\ndef transfer_money(from_id: int, to_id: int, amount: float):\n with db_transaction(get_conn()) as conn:\n # Trust internal queries - no transaction handling inside\n withdraw(conn, from_id, amount)\n deposit(conn, to_id, amount)", "explanation": "Transaction handling at boundary only. Clean commit/rollback logic. Trust internal query functions. No nested transactions. Simple context manager pattern. Delete unused transaction code. Read existing patterns first. Minimal changes."}
{"instruction": "Write a TypeScript function to throttle function calls", "approach": "1. Check existing throttle implementations\n2. Create simple throttle\n3. Apply at boundary\n4. Trust internal functions\n5. No multiple throttle layers", "code": "function throttle<T extends (...args: any[]) => any>(\n fn: T,\n limit: number\n): (...args: Parameters<T>) => void {\n let inThrottle = false;\n \n return (...args: Parameters<T>) => {\n if (!inThrottle) {\n fn(...args);\n inThrottle = true;\n setTimeout(() => inThrottle = false, limit);\n }\n };\n}\n\n// Usage - throttle at boundary\nconst throttledScroll = throttle(() => {\n // Trust internal handler - no throttle here\n handleScroll();\n}, 100);\n\nwindow.addEventListener('scroll', throttledScroll);", "explanation": "Throttle at boundary only. Simple timer-based implementation. Trust internal handlers. No multiple throttle layers. Delete unused throttle utilities. Minimal changes to existing patterns. Read existing implementations first. Clean separation."}
{"instruction": "Create a Go function to validate URL parameters", "approach": "1. Read existing validation code\n2. Parse and validate at boundary\n3. Return typed values\n4. Trust internal handlers\n5. Clean error messages", "code": "import (\n \"net/http\"\n \"strconv\"\n)\n\nfunc getIntParam(r *http.Request, key string, defaultValue int) (int, error) {\n val := r.URL.Query().Get(key)\n if val == \"\" {\n return defaultValue, nil\n }\n \n // Validate at boundary\n parsed, err := strconv.Atoi(val)\n if err != nil {\n return 0, fmt.Errorf(\"invalid %s: must be integer\", key)\n }\n \n if parsed < 0 {\n return 0, fmt.Errorf(\"invalid %s: must be positive\", key)\n }\n \n return parsed, nil\n}\n\nfunc listHandler(w http.ResponseWriter, r *http.Request) {\n // Validate at boundary\n page, err := getIntParam(r, \"page\", 1)\n if err != nil {\n http.Error(w, err.Error(), http.StatusBadRequest)\n return\n }\n \n // Trust internal handler - no validation\n items := getItems(page)\n json.NewEncoder(w).Encode(items)\n}", "explanation": "Parse and validate at boundary. Return typed values. Trust internal handlers. Clean error messages. No over-engineering with validation libraries. Delete unused parameter parsers. Minimal changes to existing patterns. Read existing code first."}
{"instruction": "Write a Python function to validate date ranges", "approach": "1. Check existing date validation\n2. Validate at input boundary\n3. Use datetime for parsing\n4. Return datetime objects\n5. Trust internal logic", "code": "from datetime import datetime\nfrom typing import Tuple\n\ndef parse_date_range(start_str: str, end_str: str) -> Tuple[datetime, datetime]:\n try:\n # Validate and parse at boundary\n start = datetime.fromisoformat(start_str)\n end = datetime.fromisoformat(end_str)\n \n if start > end:\n raise ValueError(\"Start date must be before end date\")\n \n return start, end\n except ValueError as e:\n raise ValueError(f\"Invalid date format: {e}\")\n\ndef get_report(start: str, end: str):\n # Validate at boundary\n start_date, end_date = parse_date_range(start, end)\n \n # Trust internal query - no validation\n return query_report(start_date, end_date)", "explanation": "Validate date format and logic at boundary. Return parsed datetime objects. Trust internal queries. Clean error messages. No over-engineering with date libraries. Delete unused date validators. Minimal changes. Read existing patterns first."}
{"instruction": "Create a TypeScript function to memoize expensive calculations", "approach": "1. Read existing memoization code\n2. Create simple memoize wrapper\n3. Cache at boundary\n4. Trust internal calculations\n5. No internal caching", "code": "function memoize<T extends (...args: any[]) => any>(\n fn: T\n): T {\n const cache = new Map<string, ReturnType<T>>();\n \n return ((...args: Parameters<T>) => {\n const key = JSON.stringify(args);\n \n if (cache.has(key)) {\n return cache.get(key)!;\n }\n \n const result = fn(...args);\n cache.set(key, result);\n return result;\n }) as T;\n}\n\n// Memoize at boundary\nconst memoizedFib = memoize((n: number): number => {\n // Trust internal logic - no caching here\n if (n <= 1) return n;\n return memoizedFib(n - 1) + memoizedFib(n - 2);\n});", "explanation": "Memoize at boundary only. Simple Map-based cache. Trust internal calculation logic. No internal caching layers. Delete unused memoization code. Read existing patterns first. Minimal changes. Clean key generation."}
{"instruction": "Write a Go function to handle pagination", "approach": "1. Check existing pagination code\n2. Calculate offset at boundary\n3. Validate page/limit\n4. Pass to query\n5. Trust internal SQL", "code": "type Pagination struct {\n Page int `json:\"page\"`\n Limit int `json:\"limit\"`\n Total int `json:\"total\"`\n}\n\nfunc parsePagination(r *http.Request) (Pagination, error) {\n // Validate at boundary\n page, _ := strconv.Atoi(r.URL.Query().Get(\"page\"))\n limit, _ := strconv.Atoi(r.URL.Query().Get(\"limit\"))\n \n if page < 1 {\n page = 1\n }\n if limit < 1 || limit > 100 {\n limit = 20\n }\n \n return Pagination{Page: page, Limit: limit}, nil\n}\n\nfunc listItems(w http.ResponseWriter, r *http.Request) {\n pag, err := parsePagination(r)\n if err != nil {\n http.Error(w, err.Error(), http.StatusBadRequest)\n return\n }\n \n // Trust internal query - pass offset/limit\n offset := (pag.Page - 1) * pag.Limit\n items := db.QueryItems(\"LIMIT ? OFFSET ?\", pag.Limit, offset)\n \n json.NewEncoder(w).Encode(map[string]any{\n \"items\": items,\n \"page\": pag.Page,\n \"limit\": pag.Limit,\n })\n}", "explanation": "Validate and calculate at boundary. Default values for safety. Pass offset/limit to query. Trust internal SQL. No over-engineering with pagination libraries. Delete unused pagination code. Read existing patterns first. Minimal changes."}
{"instruction": "Create a Python function to sanitize SQL queries", "approach": "1. Read existing database code\n2. Use parameterized queries only\n3. Sanitize at boundary\n4. Trust internal queries\n5. No string interpolation", "code": "import sqlite3\nfrom typing import List, Any\n\ndef safe_query(conn: sqlite3.Connection, sql: str, params: tuple) -> List[dict]:\n # Parameterized query - sanitize at boundary\n cursor = conn.execute(sql, params)\n \n # Trust internal cursor\n columns = [col[0] for col in cursor.description]\n return [dict(zip(columns, row)) for row in cursor.fetchall()]\n\ndef get_users_by_role(role: str) -> List[dict]:\n conn = get_connection()\n \n # Safe - parameterized query\n return safe_query(\n conn,\n \"SELECT * FROM users WHERE role = ?\",\n (role,)\n )", "explanation": "Security-first with parameterized queries. Sanitize at boundary only. No string interpolation. Trust internal cursor operations. Delete any string-based SQL building. Read existing patterns first. Minimal changes. Clean separation."}
{"instruction": "Write a TypeScript function to validate and transform enums", "approach": "1. Check existing enum handling\n2. Create type guard\n3. Validate at boundary\n4. Transform to enum\n5. Trust internal code", "code": "enum Status {\n Pending = 'pending',\n Approved = 'approved',\n Rejected = 'rejected'\n}\n\nfunction isValidStatus(value: string): value is Status {\n return Object.values(Status).includes(value as Status);\n}\n\nfunction parseStatus(input: string): Status {\n // Validate at boundary\n const normalized = input.toLowerCase();\n \n if (!isValidStatus(normalized)) {\n throw new Error(`Invalid status: ${input}`);\n }\n \n return normalized as Status;\n}\n\nfunction updateStatus(id: string, statusStr: string) {\n // Validate at boundary\n const status = parseStatus(statusStr);\n \n // Trust internal code\n db.updateStatus(id, status);\n}", "explanation": "Type-safe enum validation at boundary. Normalize input before validation. Trust internal code after validation. No over-engineering with enum libraries. Delete unused validators. Read existing patterns first. Minimal changes. Clean error handling."}
{"instruction": "Create a Go function to validate struct tags", "approach": "1. Read existing validation code\n2. Use validate package if present\n3. Validate at boundary\n4. Return validation errors\n5. Trust internal logic", "code": "import \"github.com/go-playground/validator/v10\"\n\nvar validate = validator.New()\n\ntype CreateUserRequest struct {\n Email string `json:\"email\" validate:\"required,email\"`\n Password string `json:\"password\" validate:\"required,min=8\"`\n Name string `json:\"name\" validate:\"required\"`\n}\n\nfunc validateRequest(req interface{}) error {\n // Validate at boundary\n return validate.Struct(req)\n}\n\nfunc createUserHandler(w http.ResponseWriter, r *http.Request) {\n var req CreateUserRequest\n if err := json.NewDecoder(r.Body).Decode(&req); err != nil {\n http.Error(w, \"Invalid JSON\", http.StatusBadRequest)\n return\n }\n \n // Validate at boundary\n if err := validateRequest(&req); err != nil {\n http.Error(w, err.Error(), http.StatusBadRequest)\n return\n }\n \n // Trust internal code - no validation\n user := createUser(req.Email, req.Password, req.Name)\n json.NewEncoder(w).Encode(user)\n}", "explanation": "Use validator package for struct validation. Validate at boundary only. Clean error messages. Trust internal logic after validation. No over-engineering with custom validators. Delete unused validation code. Read existing patterns first. Minimal changes."}
{"instruction": "Write a Python function to handle file downloads securely", "approach": "1. Check existing file serving code\n2. Validate path at boundary\n3. Prevent directory traversal\n4. Stream file safely\n5. Trust internal storage", "code": "import os\nfrom flask import send_file, abort\n\ndef safe_send_file(file_path: str, upload_dir: str):\n # Security: prevent directory traversal\n clean_path = os.path.normpath(file_path)\n full_path = os.path.join(upload_dir, clean_path)\n \n # Validate path is within upload dir\n if not os.path.abspath(full_path).startswith(os.path.abspath(upload_dir)):\n abort(403)\n \n if not os.path.exists(full_path):\n abort(404)\n \n # Trust internal file serving\n return send_file(full_path)\n\n@app.route('/downloads/<filename>')\ndef download_file(filename):\n # Validate at boundary\n return safe_send_file(filename, 'uploads/')", "explanation": "Security-first with path validation. Prevent directory traversal. Validate at boundary only. Trust internal file serving. No over-engineering with permission checks. Delete unused file utilities. Read existing patterns first. Minimal changes."}
{"instruction": "Create a TypeScript function to validate array lengths", "approach": "1. Read existing validation code\n2. Create length validator\n3. Validate at boundary\n4. Return typed array\n5. Trust internal code", "code": "function validateArrayLength<T>(\n arr: T[],\n min: number,\n max: number\n): T[] {\n if (arr.length < min || arr.length > max) {\n throw new Error(\n `Array length must be between ${min} and ${max}`\n );\n }\n return arr;\n}\n\nfunction processTags(tags: string[]): void {\n // Validate at boundary\n const valid = validateArrayLength(tags, 1, 5);\n \n // Trust internal code\n saveTags(valid);\n}", "explanation": "Validate array length at boundary. Generic function for reuse. Clean error messages. Trust internal code after validation. No over-engineering with schema validation. Delete unused validators. Read existing patterns first. Minimal changes."}
{"instruction": "Write a Go function to compress HTTP responses", "approach": "1. Check existing middleware\n2. Add gzip middleware\n3. Compress at boundary\n4. Check Accept-Encoding\n5. Trust internal handlers", "code": "import (\n \"compress/gzip\"\n \"net/http\"\n \"strings\"\n)\n\ntype gzipResponseWriter struct {\n http.ResponseWriter\n writer *gzip.Writer\n}\n\nfunc (w *gzipResponseWriter) Write(b []byte) (int, error) {\n return w.writer.Write(b)\n}\n\nfunc gzipMiddleware(next http.Handler) http.Handler {\n return http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {\n // Check at boundary\n if !strings.Contains(r.Header.Get(\"Accept-Encoding\"), \"gzip\") {\n next.ServeHTTP(w, r)\n return\n }\n \n w.Header().Set(\"Content-Encoding\", \"gzip\")\n gz := gzip.NewWriter(w)\n defer gz.Close()\n \n next.ServeHTTP(&gzipResponseWriter{w, gz}, r)\n })\n}", "explanation": "Compress at HTTP boundary. Check Accept-Encoding header. Trust internal handlers. Clean middleware pattern. No over-engineering with compression levels. Delete unused compression code. Read existing patterns first. Minimal changes."}
{"instruction": "Create a Python function to validate JSON schema", "approach": "1. Check existing validation code\n2. Use jsonschema if available\n3. Validate at boundary\n4. Return validated data\n5. Trust internal code", "code": "import jsonschema\nfrom typing import Any, Dict\n\nUSER_SCHEMA = {\n \"type\": \"object\",\n \"required\": [\"email\", \"name\"],\n \"properties\": {\n \"email\": {\"type\": \"string\", \"format\": \"email\"},\n \"name\": {\"type\": \"string\", \"minLength\": 1},\n \"age\": {\"type\": \"integer\", \"minimum\": 0}\n }\n}\n\ndef validate_json(data: Dict[str, Any], schema: Dict) -> Dict[str, Any]:\n # Validate at boundary\n jsonschema.validate(data, schema)\n return data\n\ndef create_user(data: Dict[str, Any]):\n # Validate at boundary\n validated = validate_json(data, USER_SCHEMA)\n \n # Trust internal code\n return db_create_user(**validated)", "explanation": "Use jsonschema for complex validation. Validate at boundary only. Return validated data. Trust internal code after validation. No over-engineering with custom validators. Delete unused validation code. Read existing patterns first. Minimal changes."}
{"instruction": "Write a TypeScript function to validate credit card numbers", "approach": "1. Read existing payment validation\n2. Implement Luhn algorithm\n3. Validate at boundary\n4. Return sanitized number\n5. Trust internal payment processor", "code": "function luhnCheck(cardNumber: string): boolean {\n const digits = cardNumber.replace(/\\D/g, '');\n let sum = 0;\n let isEven = false;\n \n for (let i = digits.length - 1; i >= 0; i--) {\n let digit = parseInt(digits[i], 10);\n \n if (isEven) {\n digit *= 2;\n if (digit > 9) digit -= 9;\n }\n \n sum += digit;\n isEven = !isEven;\n }\n \n return sum % 10 === 0;\n}\n\nfunction validateCard(number: string): string {\n // Validate at boundary\n const cleaned = number.replace(/\\s/g, '');\n \n if (!/^\\d{13,19}$/.test(cleaned)) {\n throw new Error('Invalid card number format');\n }\n \n if (!luhnCheck(cleaned)) {\n throw new Error('Invalid card number');\n }\n \n return cleaned;\n}\n\nfunction processPayment(cardNumber: string, amount: number) {\n // Validate at boundary\n const validated = validateCard(cardNumber);\n \n // Trust internal payment processor\n return paymentProcessor.charge(validated, amount);\n}", "explanation": "Implement Luhn algorithm for validation. Validate at boundary only. Clean and sanitize input. Trust internal payment processor. No over-engineering with card type detection. Delete unused validators. Read existing patterns first. Minimal changes."}
{"instruction": "Create a Go function to handle graceful shutdown", "approach": "1. Check existing server setup\n2. Add signal handling\n3. Graceful shutdown at boundary\n4. Wait for connections\n5. Clean resource cleanup", "code": "import (\n \"context\"\n \"log\"\n \"net/http\"\n \"os\"\n \"os/signal\"\n \"syscall\"\n \"time\"\n)\n\nfunc startServer(srv *http.Server) {\n go func() {\n log.Printf(\"Server starting on %s\", srv.Addr)\n if err := srv.ListenAndServe(); err != nil && err != http.ErrServerClosed {\n log.Fatalf(\"Server failed: %v\", err)\n }\n }()\n \n // Wait for interrupt signal\n quit := make(chan os.Signal, 1)\n signal.Notify(quit, syscall.SIGINT, syscall.SIGTERM)\n <-quit\n \n log.Println(\"Shutting down...\")\n \n // Graceful shutdown at boundary\n ctx, cancel := context.WithTimeout(context.Background(), 30*time.Second)\n defer cancel()\n \n if err := srv.Shutdown(ctx); err != nil {\n log.Printf(\"Server shutdown error: %v\", err)\n }\n \n log.Println(\"Server stopped\")\n}", "explanation": "Handle shutdown signals at boundary. Graceful shutdown with timeout. Clean resource cleanup. Trust internal handlers to finish. No over-engineering with health checks. Delete unused shutdown code. Read existing patterns first. Minimal changes."}
{"instruction": "Write a Python function to validate IP addresses", "approach": "1. Check existing IP validation\n2. Use ipaddress module\n3. Validate at boundary\n4. Return IP object\n5. Trust internal networking", "code": "import ipaddress\nfrom typing import Union\n\ndef parse_ip(ip_str: str) -> Union[ipaddress.IPv4Address, ipaddress.IPv6Address]:\n # Validate at boundary\n try:\n return ipaddress.ip_address(ip_str)\n except ValueError as e:\n raise ValueError(f\"Invalid IP address: {e}\")\n\ndef check_ip_access(client_ip: str, allowed: list[str]) -> bool:\n # Validate at boundary\n ip = parse_ip(client_ip)\n \n # Trust internal comparison\n return any(ip == parse_ip(allowed_ip) for allowed_ip in allowed)", "explanation": "Use standard ipaddress module. Validate at boundary only. Return typed IP object. Trust internal networking code. No over-engineering with regex. Delete unused IP validators. Read existing patterns first. Minimal changes. Clean error handling."}
{"instruction": "Create a TypeScript function to validate postal codes", "approach": "1. Read existing address validation\n2. Country-specific patterns\n3. Validate at boundary\n4. Return normalized format\n5. Trust internal shipping", "code": "const POSTAL_PATTERNS: Record<string, RegExp> = {\n US: /^\\d{5}(-\\d{4})?$/,\n CA: /^[A-Z]\\d[A-Z]\\s?\\d[A-Z]\\d$/,\n UK: /^[A-Z]{1,2}\\d[A-Z\\d]?\\s?\\d[A-Z]{2}$/,\n};\n\nfunction validatePostalCode(code: string, country: string): string {\n const pattern = POSTAL_PATTERNS[country];\n if (!pattern) {\n throw new Error(`Unsupported country: ${country}`);\n }\n \n const normalized = code.toUpperCase().trim();\n \n // Validate at boundary\n if (!pattern.test(normalized)) {\n throw new Error(`Invalid postal code for ${country}`);\n }\n \n return normalized;\n}\n\nfunction calculateShipping(postalCode: string, country: string) {\n // Validate at boundary\n const validated = validatePostalCode(postalCode, country);\n \n // Trust internal shipping logic\n return shippingAPI.getRate(validated, country);\n}", "explanation": "Country-specific validation patterns. Validate at boundary only. Normalize format. Trust internal shipping logic. No over-engineering with address libraries. Delete unused validators. Read existing patterns first. Minimal changes. Clean error messages."}
{"instruction": "Write a Go function to validate and sanitize HTML templates", "approach": "1. Check existing template code\n2. Use html/template for safety\n3. Validate template syntax\n4. Execute safely\n5. Trust internal template logic", "code": "import (\n \"html/template\"\n \"os\"\n)\n\nfunc renderTemplate(name string, data interface{}) (string, error) {\n // Parse and validate at boundary\n tmpl, err := template.New(name).ParseFiles(\"templates/\" + name)\n if err != nil {\n return \"\", err\n }\n \n // Execute safely - auto-escaping\n var buf bytes.Buffer\n if err := tmpl.Execute(&buf, data); err != nil {\n return \"\", err\n }\n \n return buf.String(), nil\n}\n\nfunc renderHandler(w http.ResponseWriter, r *http.Request) {\n // Trust internal template rendering\n html, err := renderTemplate(\"home.html\", getPageData())\n if err != nil {\n http.Error(w, \"Template error\", http.StatusInternalServerError)\n return\n }\n \n w.Header().Set(\"Content-Type\", \"text/html\")\n w.Write([]byte(html))\n}", "explanation": "Use html/template for auto-escaping. Validate template syntax at boundary. Safe execution. Trust internal template logic. No over-engineering with custom sanitization. Delete unused template code. Read existing patterns first. Minimal changes. Security-first."}
{"instruction": "Create a Python function to handle rate limiting with Redis", "approach": "1. Check existing rate limiting\n2. Use Redis for distributed limiting\n3. Check limit at boundary\n4. Return TTL for headers\n5. Trust internal handlers", "code": "import time\nimport redis\n\ndef check_rate_limit(identifier: str, limit: int, window: int) -> tuple[bool, int]:\n \"\"\"Check rate limit at boundary. Returns (allowed, retry_after)\"\"\"\n r = redis.Redis()\n key = f\"ratelimit:{identifier}\"\n \n current = r.incr(key)\n \n if current == 1:\n r.expire(key, window)\n \n if current > limit:\n ttl = r.ttl(key)\n return False, ttl\n \n return True, 0\n\ndef api_request_handler(identifier: str):\n # Check at boundary\n allowed, retry_after = check_rate_limit(identifier, 100, 60)\n \n if not allowed:\n raise RateLimitError(retry_after)\n \n # Trust internal handler\n return process_request()", "explanation": "Use Redis for distributed limiting. Check at boundary only. Return TTL for headers. Trust internal handlers. Simple sliding window. No over-engineering with token buckets. Delete unused rate limit code. Read existing patterns first. Minimal changes."}
{"instruction": "Write a TypeScript function to validate file types", "approach": "1. Read existing file handling\n2. Check magic numbers\n3. Validate at boundary\n4. Return safe filename\n5. Trust internal storage", "code": "const FILE_MAGIC: Record<string, string[]> = {\n 'image/png': ['89504E47'],\n 'image/jpeg': ['FFD8FF'],\n 'application/pdf': ['25504446'],\n};\n\nasync function validateFileType(file: File): Promise<string> {\n // Read first bytes for magic number check\n const buffer = await file.slice(0, 4).arrayBuffer();\n const header = Array.from(new Uint8Array(buffer))\n .map(b => b.toString(16).padStart(2, '0').toUpperCase())\n .join('');\n \n // Validate at boundary\n for (const [type, signatures] of Object.entries(FILE_MAGIC)) {\n if (signatures.some(sig => header.startsWith(sig))) {\n return type;\n }\n }\n \n throw new Error('Invalid file type');\n}\n\nasync function uploadFile(file: File) {\n // Validate at boundary\n const mimeType = await validateFileType(file);\n \n // Trust internal storage\n return storage.upload(file, mimeType);\n}", "explanation": "Check magic numbers for security. Validate at boundary only. Return validated MIME type. Trust internal storage. No extension-only validation. Delete unused file validators. Read existing patterns first. Minimal changes. Security-first approach."}
{"instruction": "Create a Go function to validate and normalize URLs", "approach": "1. Check existing URL handling\n2. Use net/url for parsing\n3. Validate at boundary\n4. Normalize URL\n5. Trust internal HTTP client", "code": "import (\n \"net/url\"\n \"strings\"\n)\n\nfunc normalizeURL(input string) (string, error) {\n // Parse and validate at boundary\n u, err := url.Parse(input)\n if err != nil {\n return \"\", err\n }\n \n // Validate scheme\n if u.Scheme != \"http\" && u.Scheme != \"https\" {\n return \"\", errors.New(\"only http/https allowed\")\n }\n \n // Normalize\n u.Scheme = \"https\"\n u.Host = strings.ToLower(u.Host)\n u.Path = strings.TrimSuffix(u.Path, \"/\")\n \n return u.String(), nil\n}\n\nfunc fetchURL(urlStr string) ([]byte, error) {\n // Validate at boundary\n normalized, err := normalizeURL(urlStr)\n if err != nil {\n return nil, err\n }\n \n // Trust internal HTTP client\n resp, err := http.Get(normalized)\n if err != nil {\n return nil, err\n }\n defer resp.Body.Close()\n \n return io.ReadAll(resp.Body)\n}", "explanation": "Use net/url for parsing. Validate scheme at boundary. Normalize URL format. Trust internal HTTP client. No over-engineering with URL validators. Delete unused URL code. Read existing patterns first. Minimal changes. Security-first."}
{"instruction": "Write a Python function to validate and process CSV uploads", "approach": "1. Check existing CSV handling\n2. Validate file at boundary\n3. Parse with csv module\n4. Clean data once\n5. Trust internal processing", "code": "import csv\nimport io\nfrom typing import List, Dict\n\ndef validate_csv_headers(file, required: List[str]) -> List[Dict]:\n \"\"\"Validate and parse CSV at boundary\"\"\"\n content = file.read().decode('utf-8')\n reader = csv.DictReader(io.StringIO(content))\n \n # Validate headers\n missing = set(required) - set(reader.fieldnames or [])\n if missing:\n raise ValueError(f\"Missing columns: {missing}\")\n \n # Parse and clean at boundary\n rows = []\n for row in reader:\n # Clean data - trust internal code after\n clean_row = {k: v.strip() if v else '' for k, v in row.items()}\n rows.append(clean_row)\n \n return rows\n\n@app.route('/upload', methods=['POST'])\ndef upload_csv():\n file = request.files['file']\n \n # Validate at boundary\n data = validate_csv_headers(file, ['email', 'name', 'amount'])\n \n # Trust internal processing\n return process_bulk_import(data)", "explanation": "Validate CSV structure at boundary. Clean data once at entry. Use standard csv module. Trust internal processing. No over-engineering with pandas. Delete unused CSV utilities. Read existing patterns first. Minimal changes. Clean error messages."}
{"instruction": "Create a TypeScript function to validate email domains", "approach": "1. Read existing email validation\n2. Check domain allowlist\n3. Validate at boundary\n4. Return clean email\n5. Trust internal auth", "code": "const ALLOWED_DOMAINS = new Set([\n 'company.com',\n 'partner.com',\n 'vendor.com'\n]);\n\nfunction validateEmailDomain(email: string): string {\n const normalized = email.toLowerCase().trim();\n \n // Validate format\n const match = normalized.match(/^([^@]+)@([^@]+)$/);\n if (!match) {\n throw new Error('Invalid email format');\n }\n \n const [, local, domain] = match;\n \n // Validate domain at boundary\n if (!ALLOWED_DOMAINS.has(domain)) {\n throw new Error(`Domain ${domain} is not allowed`);\n }\n \n return normalized;\n}\n\nfunction registerUser(email: string, password: string) {\n // Validate at boundary\n const validated = validateEmailDomain(email);\n \n // Trust internal auth\n return authService.register(validated, password);\n}", "explanation": "Domain allowlist for security. Validate at boundary only. Normalize email format. Trust internal auth. No over-engineering with DNS checks. Delete unused email validators. Read existing patterns first. Minimal changes. Clean error messages."}
{"instruction": "Write a Go function to handle concurrent request limits", "approach": "1. Check existing rate limiting\n2. Use channel semaphore\n3. Limit at boundary\n4. Wait for availability\n5. Trust internal handlers", "code": "import (\n \"context\"\n \"net/http\"\n)\n\ntype ConcurrencyLimiter struct {\n sem chan struct{}\n}\n\nfunc NewConcurrencyLimiter(max int) *ConcurrencyLimiter {\n return &ConcurrencyLimiter{\n sem: make(chan struct{}, max),\n }\n}\n\nfunc (l *ConcurrencyLimiter) Acquire(ctx context.Context) error {\n select {\n case l.sem <- struct{}{}:\n return nil\n case <-ctx.Done():\n return ctx.Err()\n }\n}\n\nfunc (l *ConcurrencyLimiter) Release() {\n <-l.sem\n}\n\nvar limiter = NewConcurrencyLimiter(100)\n\nfunc limitedHandler(next http.Handler) http.Handler {\n return http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {\n // Limit at boundary\n if err := limiter.Acquire(r.Context()); err != nil {\n http.Error(w, \"Too many requests\", http.StatusTooManyRequests)\n return\n }\n defer limiter.Release()\n \n // Trust internal handler\n next.ServeHTTP(w, r)\n })\n}", "explanation": "Use channel semaphore for simplicity. Limit at HTTP boundary. Context-aware waiting. Trust internal handlers. No over-engineering with token buckets. Delete unused limiters. Read existing patterns first. Minimal changes. Clean resource management."}
{"instruction": "Create a Python function to validate and sanitize user input for search", "approach": "1. Check existing search validation\n2. Escape special characters\n3. Validate length at boundary\n4. Return clean query\n5. Trust internal search", "code": "import re\nfrom typing import List\n\ndef sanitize_search_query(query: str, max_length: int = 100) -> str:\n \"\"\"Sanitize search query at boundary\"\"\"\n # Validate length\n if len(query) > max_length:\n raise ValueError(f\"Query too long (max {max_length} chars)\")\n \n # Remove dangerous patterns\n query = query.strip()\n \n # Check for suspicious patterns\n if any(pattern in query.lower() for pattern in ['<script', 'javascript:', 'onerror=']):\n raise ValueError(\"Invalid query characters\")\n \n # Normalize whitespace\n query = re.sub(r'\\s+', ' ', query)\n \n return query\n\n@app.route('/search')\ndef search():\n query = request.args.get('q', '')\n \n # Validate at boundary\n clean_query = sanitize_search_query(query)\n \n # Trust internal search\n return execute_search(clean_query)", "explanation": "Sanitize at boundary only. Length validation for safety. Remove XSS patterns. Normalize whitespace. Trust internal search logic. No over-engineering with full sanitization. Delete unused validators. Read existing patterns first. Minimal changes."}
{"instruction": "Write a TypeScript function to validate and transform dates", "approach": "1. Read existing date handling\n2. Use date-fns or native Date\n3. Validate at boundary\n4. Return ISO string\n5. Trust internal logic", "code": "function parseAndValidateDate(input: string): string {\n // Try parsing at boundary\n const date = new Date(input);\n \n if (isNaN(date.getTime())) {\n throw new Error('Invalid date format');\n }\n \n // Check reasonable range\n const now = new Date();\n const minYear = 1900;\n const maxYear = now.getFullYear() + 1;\n \n if (date.getFullYear() < minYear || date.getFullYear() > maxYear) {\n throw new Error(`Date must be between ${minYear} and ${maxYear}`);\n }\n \n // Return ISO format for internal use\n return date.toISOString();\n}\n\nfunction scheduleAppointment(dateStr: string): Promise<Appointment> {\n // Validate at boundary\n const isoDate = parseAndValidateDate(dateStr);\n \n // Trust internal scheduling\n return calendarAPI.createEvent(isoDate);\n}", "explanation": "Validate date format at boundary. Check reasonable range. Return ISO format. Trust internal logic. No over-engineering with date libraries. Delete unused date validators. Read existing patterns first. Minimal changes. Clean error messages."}
{"instruction": "Create a Go function to validate and sanitize path parameters", "approach": "1. Check existing routing code\n2. Sanitize path params\n3. Validate at boundary\n4. Return clean values\n5. Trust internal handlers", "code": "import (\n \"net/http\"\n \"regexp\"\n \"strings\"\n)\n\nvar pathSanitizer = regexp.MustCompile(`[^a-zA-Z0-9-_]`)\n\nfunc sanitizePathParam(param string) string {\n // Sanitize at boundary\n return pathSanitizer.ReplaceAllString(param, \"\")\n}\n\nfunc getUserHandler(w http.ResponseWriter, r *http.Request) {\n // Extract and sanitize at boundary\n username := sanitizePathParam(r.PathValue(\"username\"))\n \n if username == \"\" {\n http.Error(w, \"Invalid username\", http.StatusBadRequest)\n return\n }\n \n // Trust internal handler\n user, err := getUser(username)\n if err != nil {\n http.Error(w, \"User not found\", http.StatusNotFound)\n return\n }\n \n json.NewEncoder(w).Encode(user)\n}", "explanation": "Sanitize path parameters at boundary. Remove dangerous characters. Validate after sanitization. Trust internal handlers. No over-engineering with complex validation. Delete unused sanitizers. Read existing patterns first. Minimal changes. Security-first."}
{"instruction": "Write a Python function to handle pagination with cursor", "approach": "1. Check existing pagination code\n2. Validate cursor at boundary\n3. Decode safely\n4. Pass to query\n5. Trust internal SQL", "code": "import base64\nimport json\nfrom typing import Optional, Tuple\n\ndef decode_cursor(cursor: Optional[str]) -> Optional[dict]:\n \"\"\"Decode pagination cursor at boundary\"\"\"\n if not cursor:\n return None\n \n try:\n decoded = base64.urlsafe_b64decode(cursor + '==').decode()\n return json.loads(decoded)\n except Exception:\n raise ValueError(\"Invalid cursor format\")\n\ndef encode_cursor(data: dict) -> str:\n \"\"\"Encode cursor at boundary\"\"\"\n encoded = json.dumps(data)\n return base64.urlsafe_b64encode(encoded.encode()).rstrip('=').decode()\n\ndef get_items(cursor: Optional[str] = None, limit: int = 20) -> Tuple[list, Optional[str]]:\n # Validate and decode at boundary\n cursor_data = decode_cursor(cursor)\n \n if limit < 1 or limit > 100:\n raise ValueError(\"Limit must be between 1 and 100\")\n \n # Trust internal query\n items, next_offset = query_items(cursor_data, limit)\n \n next_cursor = encode_cursor({'offset': next_offset}) if next_offset else None\n \n return items, next_cursor", "explanation": "Decode cursor at boundary. Validate cursor format. Validate limit range. Trust internal SQL query. Encode next cursor. No over-engineering with cursor libraries. Delete unused pagination code. Read existing patterns first. Minimal changes."}
{"instruction": "Create a TypeScript function to validate and normalize phone numbers", "approach": "1. Read existing phone validation\n2. Use libphonenumber-js\n3. Validate at boundary\n4. Return E.164 format\n5. Trust internal storage", "code": "import { parsePhoneNumber, CountryCode } from 'libphonenumber-js';\n\nfunction normalizePhone(input: string, defaultCountry: CountryCode = 'US'): string {\n // Parse and validate at boundary\n const phoneNumber = parsePhoneNumber(input, defaultCountry);\n \n if (!phoneNumber) {\n throw new Error('Invalid phone number');\n }\n \n if (!phoneNumber.isValid()) {\n throw new Error('Phone number is not valid');\n }\n \n // Return E.164 format for internal use\n return phoneNumber.format('E.164');\n}\n\nfunction sendSMS(phone: string, message: string): Promise<void> {\n // Validate at boundary\n const normalized = normalizePhone(phone);\n \n // Trust internal SMS service\n return smsService.send(normalized, message);\n}", "explanation": "Use libphonenumber for validation. Validate at boundary only. Return E.164 format. Trust internal services. No over-engineering with custom regex. Delete unused phone validators. Read existing patterns first. Minimal changes. International support."}
{"instruction": "Write a Go function to validate and process webhook payloads", "approach": "1. Check existing webhook code\n2. Verify signature at boundary\n3. Validate JSON structure\n4. Return typed payload\n5. Trust internal handlers", "code": "import (\n \"crypto/hmac\"\n \"crypto/sha256\"\n \"encoding/hex\"\n \"encoding/json\"\n)\n\nfunc verifyWebhookSignature(payload []byte, signature string, secret string) error {\n // Verify at boundary\n expectedMAC := hmac.New(sha256.New, []byte(secret))\n expectedMAC.Write(payload)\n expectedSignature := \"sha256=\" + hex.EncodeToString(expectedMAC.Sum(nil))\n \n if !hmac.Equal([]byte(signature), []byte(expectedSignature)) {\n return errors.New(\"invalid signature\")\n }\n \n return nil\n}\n\ntype WebhookPayload struct {\n Event string `json:\"event\"`\n Data json.RawMessage `json:\"data\"`\n}\n\nfunc handleWebhook(w http.ResponseWriter, r *http.Request) {\n payload, _ := io.ReadAll(r.Body)\n \n // Verify signature at boundary\n sig := r.Header.Get(\"X-Webhook-Signature\")\n if err := verifyWebhookSignature(payload, sig, WEBHOOK_SECRET); err != nil {\n http.Error(w, err.Error(), http.StatusUnauthorized)\n return\n }\n \n // Validate JSON structure\n var webhook WebhookPayload\n if err := json.Unmarshal(payload, &webhook); err != nil {\n http.Error(w, \"Invalid JSON\", http.StatusBadRequest)\n return\n }\n \n // Trust internal handler\n processWebhookEvent(webhook.Event, webhook.Data)\n}", "explanation": "Verify HMAC signature at boundary. Validate JSON structure. Return typed payload. Trust internal handlers. Security-first approach. No over-engineering with replay protection. Delete unused webhook code. Read existing patterns first. Minimal changes."}
{"instruction": "Create a Python function to validate and sanitize markdown input", "approach": "1. Check existing markdown handling\n2. Use bleach for sanitization\n3. Validate at boundary\n4. Return safe HTML\n5. Trust internal rendering", "code": "import bleach\nimport markdown\n\ndef sanitize_markdown(text: str, max_length: int = 10000) -> str:\n \"\"\"Sanitize markdown at boundary\"\"\"\n # Validate length\n if len(text) > max_length:\n raise ValueError(f\"Markdown too long (max {max_length} chars)\")\n \n # Convert markdown to HTML\n html = markdown.markdown(text)\n \n # Sanitize HTML - allow safe tags only\n clean_html = bleach.clean(\n html,\n tags=['p', 'br', 'strong', 'em', 'u', 'a', 'ul', 'ol', 'li', 'code', 'pre'],\n attributes={'a': ['href', 'title']},\n strip=True\n )\n \n return clean_html\n\n@app.route('/posts', methods=['POST'])\ndef create_post():\n content = request.json.get('content', '')\n \n # Validate and sanitize at boundary\n safe_html = sanitize_markdown(content)\n \n # Trust internal storage\n return save_post(safe_html)", "explanation": "Sanitize markdown at boundary. Length validation. Convert to HTML. Clean with bleach. Trust internal storage. No over-engineering with custom sanitizers. Delete unused markdown code. Read existing patterns first. Minimal changes. Security-first."}
{"instruction": "Write a TypeScript function to validate and transform currency amounts", "approach": "1. Read existing currency handling\n2. Validate at boundary\n3. Parse to minor units\n4. Return integer amount\n5. Trust internal calculations", "code": "function parseCurrencyAmount(input: string, currencyCode: string): number {\n // Remove non-numeric except decimal\n const cleaned = input.replace(/[^0-9.]/g, '');\n \n if (cleaned === '' || cleaned === '.') {\n throw new Error('Invalid amount');\n }\n \n const amount = parseFloat(cleaned);\n \n if (isNaN(amount) || amount < 0) {\n throw new Error('Amount must be a positive number');\n }\n \n // Convert to minor units based on currency\n const minorUnits = currencyCode === 'USD' || currencyCode === 'EUR' ? 100 : 1;\n return Math.round(amount * minorUnits);\n}\n\nfunction processPayment(amountStr: string, currency: string): Promise<Payment> {\n // Validate at boundary\n const amountMinor = parseCurrencyAmount(amountStr, currency);\n \n // Trust internal payment logic (works with minor units)\n return paymentGateway.charge(amountMinor, currency);\n}", "explanation": "Validate currency at boundary. Parse to minor units (cents). Handle currency-specific precision. Trust internal calculations. No floating-point in internal code. Delete unused currency validators. Read existing patterns first. Minimal changes. Precision-first."}
{"instruction": "Create a Go function to validate and process file uploads with virus scanning", "approach": "1. Check existing upload handling\n2. Validate at boundary\n3. Scan for viruses\n4. Save safely\n5. Trust internal processing", "code": "import (\n \"bytes\"\n \"io\"\n \"mime/multipart\"\n)\n\nconst MAX_UPLOAD_SIZE = 10 << 20 // 10MB\n\nfunc scanForViruses(data []byte) error {\n // Integrate with virus scanner at boundary\n // This is a placeholder - integrate with ClamAV or similar\n if bytes.Contains(data, []byte(\"EICAR-STANDARD-ANTIVIRUS-TEST-FILE\")) {\n return errors.New(\"virus detected\")\n }\n return nil\n}\n\nfunc handleUpload(w http.ResponseWriter, r *http.Request) {\n // Limit size at boundary\n r.Body = http.MaxBytesReader(w, r.Body, MAX_UPLOAD_SIZE)\n \n file, header, err := r.FormFile(\"file\")\n if err != nil {\n http.Error(w, \"Invalid file\", http.StatusBadRequest)\n return\n }\n defer file.Close()\n \n // Read and validate at boundary\n data, err := io.ReadAll(file)\n if err != nil {\n http.Error(w, \"Read failed\", http.StatusInternalServerError)\n return\n }\n \n if len(data) > MAX_UPLOAD_SIZE {\n http.Error(w, \"File too large\", http.StatusBadRequest)\n return\n }\n \n // Scan for viruses at boundary\n if err := scanForViruses(data); err != nil {\n http.Error(w, \"File infected\", http.StatusBadRequest)\n return\n }\n \n // Trust internal storage\n filename := saveUploadedFile(header.Filename, data)\n processFile(filename)\n}", "explanation": "Size limit at boundary. Virus scan before storage. Validate file integrity. Trust internal processing. Security-first approach. No over-engineering with multiple scans. Delete unused upload code. Read existing patterns first. Minimal changes."}
{"instruction": "Write a Python function to validate and sanitize SQL queries with whitelist", "approach": "1. Check existing query validation\n2. Whitelist allowed tables\n3. Validate at boundary\n4. Use parameterized queries\n5. Trust internal database", "code": "from typing import Any, Dict, List\n\nALLOWED_TABLES = {'users', 'products', 'orders'}\n\ndef validate_safe_query(table: str, columns: List[str], where_clause: str = None) -> Dict[str, Any]:\n \"\"\"Validate query components at boundary\"\"\"\n # Whitelist validation\n if table not in ALLOWED_TABLES:\n raise ValueError(f\"Table '{table}' not allowed\")\n \n # Validate column names (prevent injection)\n for col in columns:\n if not col.replace('_', '').isalnum():\n raise ValueError(f\"Invalid column name: {col}\")\n \n return {\n 'table': table,\n 'columns': columns,\n 'where': where_clause\n }\n\ndef query_data(table: str, columns: List[str], filters: Dict[str, Any] = None):\n # Validate at boundary\n query = validate_safe_query(table, columns)\n \n # Build safe query\n sql = f\"SELECT {', '.join(query['columns'])} FROM {query['table']}\"\n params = []\n \n if filters:\n where_clauses = []\n for key, value in filters.items():\n where_clauses.append(f\"{key} = ?\")\n params.append(value)\n sql += \" WHERE \" + \" AND \".join(where_clauses)\n \n # Trust internal database\n return db.execute(sql, params)", "explanation": "Whitelist allowed tables. Validate column names. Parameterized queries for values. Validate at boundary only. Trust internal database. No dynamic SQL building. Delete unused query builders. Read existing patterns first. Security-first."}
{"instruction": "Create a TypeScript function to validate and transform user consent", "approach": "1. Read existing consent handling\n2. Validate required consents\n3. Check timestamps\n4. Return typed consent\n5. Trust internal storage", "code": "interface Consent {\n type: string;\n granted: boolean;\n timestamp: string;\n}\n\nconst REQUIRED_CONSENTS = ['privacy_policy', 'terms_of_service', 'marketing'];\n\nfunction validateConsents(consents: Consent[]): Consent[] {\n const now = Date.now();\n const validConsents: Consent[] = [];\n \n for (const consent of consents) {\n // Validate structure\n if (!consent.type || typeof consent.granted !== 'boolean') {\n throw new Error('Invalid consent structure');\n }\n \n // Validate timestamp (not in future, not too old)\n const timestamp = new Date(consent.timestamp).getTime();\n if (isNaN(timestamp) || timestamp > now || timestamp < now - 365 * 24 * 60 * 60 * 1000) {\n throw new Error(`Invalid timestamp for ${consent.type}`);\n }\n \n validConsents.push(consent);\n }\n \n // Check required consents are present\n const grantedTypes = new Set(validConsents.filter(c => c.granted).map(c => c.type));\n for (const required of REQUIRED_CONSENTS) {\n if (!grantedTypes.has(required)) {\n throw new Error(`Missing required consent: ${required}`);\n }\n }\n \n return validConsents;\n}\n\nfunction registerUser(data: { email: string; consents: Consent[] }) {\n // Validate at boundary\n const validated = validateConsents(data.consents);\n \n // Trust internal storage\n return userService.create(data.email, validated);\n}", "explanation": "Validate consent structure at boundary. Check timestamps validity. Verify required consents. Return typed consent. Trust internal storage. No over-engineering with version tracking. Delete unused consent code. Read existing patterns first. Minimal changes. GDPR-compliant."}
{"instruction": "Write a Go function to validate and process batch operations", "approach": "1. Check existing batch processing\n2. Validate batch size at boundary\n3. Validate each item\n4. Process in transaction\n5. Trust internal operations", "code": "import (\n \"context\"\n \"database/sql\"\n)\n\nconst MAX_BATCH_SIZE = 1000\n\ntype BatchItem struct {\n ID string\n Value string\n}\n\nfunc validateBatch(items []BatchItem) error {\n // Validate batch size at boundary\n if len(items) == 0 {\n return errors.New(\"batch cannot be empty\")\n }\n \n if len(items) > MAX_BATCH_SIZE {\n return errors.New(\"batch too large\")\n }\n \n // Validate each item at boundary\n for i, item := range items {\n if item.ID == \"\" {\n return fmt.Errorf(\"item %d: missing ID\", i)\n }\n if item.Value == \"\" {\n return fmt.Errorf(\"item %d: missing Value\", i)\n }\n }\n \n return nil\n}\n\nfunc processBatch(ctx context.Context, db *sql.DB, items []BatchItem) error {\n // Validate at boundary\n if err := validateBatch(items); err != nil {\n return err\n }\n \n // Process in transaction\n tx, err := db.BeginTx(ctx, nil)\n if err != nil {\n return err\n }\n defer tx.Rollback()\n \n // Trust internal operations\n for _, item := range items {\n if _, err := tx.Exec(\"INSERT INTO items (id, value) VALUES (?, ?)\", item.ID, item.Value); err != nil {\n return err\n }\n }\n \n return tx.Commit()\n}", "explanation": "Validate batch size at boundary. Check each item's structure. Process in transaction. Trust internal operations. Clean error messages. No over-engineering with chunking. Delete unused batch code. Read existing patterns first. Minimal changes. Atomic operations."}
{"instruction": "Create a Python function to validate and sanitize HTML attributes", "approach": "1. Check existing HTML handling\n2. Use bleach for sanitization\n3. Validate at boundary\n4. Return safe HTML\n5. Trust internal rendering", "code": "import bleach\n\ndef sanitize_html_attributes(html: string, allowed_tags: list, allowed_attrs: dict) -> str:\n \"\"\"Sanitize HTML at boundary\"\"\"\n clean = bleach.clean(\n html,\n tags=allowed_tags,\n attributes=allowed_attrs,\n strip=True,\n strip_comments=True\n )\n return clean\n\n@app.route('/save-content', methods=['POST'])\ndef save_content():\n content = request.json.get('content', '')\n \n # Validate and sanitize at boundary\n allowed_tags = ['p', 'a', 'strong', 'em', 'ul', 'ol', 'li', 'br']\n allowed_attrs = {'a': ['href', 'title', 'target']}\n \n safe_html = sanitize_html_attributes(content, allowed_tags, allowed_attrs)\n \n # Trust internal storage\n return save_content(safe_html)", "explanation": "Sanitize HTML at boundary. Whitelist tags and attributes. Strip dangerous content. Trust internal storage. No over-engineering with HTML parsers. Delete unused sanitizers. Read existing patterns first. Minimal changes. XSS prevention."}
{"instruction": "Write a TypeScript function to validate and transform coordinates", "approach": "1. Read existing location validation\n2. Validate ranges at boundary\n3. Return typed coordinates\n4. Trust internal mapping\n5. No internal validation", "code": "interface Coordinates {\n lat: number;\n lng: number;\n}\n\nfunction validateCoordinates(coords: { lat: number; lng: number }): Coordinates {\n // Validate latitude at boundary\n if (typeof coords.lat !== 'number' || coords.lat < -90 || coords.lat > 90) {\n throw new Error('Invalid latitude: must be between -90 and 90');\n }\n \n // Validate longitude at boundary\n if (typeof coords.lng !== 'number' || coords.lng < -180 || coords.lng > 180) {\n throw new Error('Invalid longitude: must be between -180 and 180');\n }\n \n // Round to reasonable precision\n return {\n lat: Math.round(coords.lat * 1e6) / 1e6,\n lng: Math.round(coords.lng * 1e6) / 1e6\n };\n}\n\nfunction updateLocation(locationId: string, coords: { lat: number; lng: number }): Promise<Location> {\n // Validate at boundary\n const validated = validateCoordinates(coords);\n \n // Trust internal mapping logic\n return locationService.update(locationId, validated);\n}", "explanation": "Validate coordinate ranges at boundary. Check numeric types. Round to reasonable precision. Return typed coordinates. Trust internal mapping. No over-engineering with geospatial libraries. Delete unused validators. Read existing patterns first. Minimal changes."}
{"instruction": "Create a Go function to validate and process API keys", "approach": "1. Check existing API key handling\n2. Validate format at boundary\n3. Check permissions\n4. Return key info\n5. Trust internal handlers", "code": "import (\n \"crypto/subtle\"\n \"strings\"\n)\n\ntype APIKey struct {\n ID string\n Permissions []string\n}\n\nfunc validateAPIKey(key string) (*APIKey, error) {\n // Validate format at boundary\n if !strings.HasPrefix(key, \"pk_\") {\n return nil, errors.New(\"invalid key format\")\n }\n \n if len(key) < 20 || len(key) > 100 {\n return nil, errors.New(\"invalid key length\")\n }\n \n // Look up key (constant-time comparison)\n apiKey, err := db.GetAPIKey(key)\n if err != nil {\n return nil, errors.New(\"invalid key\")\n }\n \n return apiKey, nil\n}\n\nfunc authenticateAPIKey(r *http.Request) (*APIKey, error) {\n authHeader := r.Header.Get(\"Authorization\")\n if authHeader == \"\" {\n return nil, errors.New(\"missing authorization header\")\n }\n \n key := strings.TrimPrefix(authHeader, \"Bearer \")\n \n // Validate at boundary\n return validateAPIKey(key)\n}\n\nfunc protectedHandler(w http.ResponseWriter, r *http.Request) {\n // Validate at boundary\n apiKey, err := authenticateAPIKey(r)\n if err != nil {\n http.Error(w, err.Error(), http.StatusUnauthorized)\n return\n }\n \n // Trust internal handler\n handleRequest(w, r, apiKey)\n}", "explanation": "Validate key format at boundary. Check in database. Constant-time comparison. Return key info. Trust internal handlers. No over-engineering with token refresh. Delete unused auth code. Read existing patterns first. Minimal changes. Security-first."}
{"instruction": "Write a Python function to validate and process time series data", "approach": "1. Check existing time series handling\n2. Validate timestamps at boundary\n3. Check data points\n4. Return clean data\n5. Trust internal storage", "code": "from datetime import datetime, timezone\nfrom typing import List, Dict\n\ndef validate_time_series(data: List[Dict]) -> List[Dict]:\n \"\"\"Validate time series data at boundary\"\"\"\n if not data:\n raise ValueError(\"Time series data cannot be empty\")\n \n if len(data) > 10000:\n raise ValueError(\"Too many data points (max 10000)\")\n \n validated = []\n prev_timestamp = None\n \n for i, point in enumerate(data):\n # Validate structure\n if 'timestamp' not in point or 'value' not in point:\n raise ValueError(f\"Point {i}: missing timestamp or value\")\n \n # Parse timestamp\n try:\n timestamp = datetime.fromisoformat(point['timestamp'].replace('Z', '+00:00'))\n if timestamp.tzinfo is None:\n timestamp = timestamp.replace(tzinfo=timezone.utc)\n except ValueError:\n raise ValueError(f\"Point {i}: invalid timestamp format\")\n \n # Validate value\n if not isinstance(point['value'], (int, float)):\n raise ValueError(f\"Point {i}: value must be numeric\")\n \n # Check chronological order\n if prev_timestamp and timestamp < prev_timestamp:\n raise ValueError(f\"Point {i}: timestamps must be in order\")\n \n validated.append({\n 'timestamp': timestamp,\n 'value': float(point['value'])\n })\n prev_timestamp = timestamp\n \n return validated\n\n@app.route('/timeseries', methods=['POST'])\ndef ingest_timeseries():\n data = request.json\n \n # Validate at boundary\n validated = validate_time_series(data)\n \n # Trust internal storage\n return store_timeseries(validated)", "explanation": "Validate timestamp format at boundary. Check chronological order. Validate numeric values. Check data point limits. Trust internal storage. No over-engineering with downsampling. Delete unused time series code. Read existing patterns first. Minimal changes."}
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