productivity▌

OCI monitoring setup, alarm configuration, and troubleshooting for metrics, logs, and observability gaps. \n \n Covers metric namespace patterns, alarm threshold gotchas (sparse data handling, trigger delays), and missing data strategies across OCI services \n Provides decision trees for log collection troubleshooting, Service Connector setup, and IAM policy requirements \n Highlights critical anti-patterns: metric lag (10-15 minutes), dimension requirements, notification channel setup, and Clou

Screen job applications against role requirements to identify top candidates efficiently.

Thread-safe data persistence in Swift using actors with in-memory cache and file-backed storage. \n \n Implements an actor-based repository pattern that eliminates data races at compile time, replacing manual synchronization with Swift's actor model \n Combines fast O(1) in-memory lookups with atomic file persistence, supporting any Codable & Identifiable model type \n Provides synchronous initialization to avoid async complexity, with automatic await enforcement on all public API calls \n

Free distributed continuous fuzzing infrastructure for open-source projects with integrated coverage and bug tracking. \n \n Provides CLI helper script for building Docker images, compiling fuzzers with sanitizers (AddressSanitizer, UndefinedBehaviorSanitizer), and running harnesses locally \n Supports multiple fuzzing engines (libFuzzer, AFL++) and languages (C/C++, Python via Atheris, Rust, Go) with language-specific base images \n Includes public bug tracker, build status dashboard, and Fuzz

Discover and execute standardized development workflows using Task automation instead of direct shell commands. \n \n Provides command discovery via task --list and built-in help, showing all available project tasks with descriptions \n Covers common patterns: task dev for fast iteration, task test for testing, task docs for documentation, and task ci for full CI simulation \n Wraps language-specific commands (Julia, R, Python, etc.) with consistent naming conventions and multi-step workflows \n

You are a database observability expert specializing in Change Data Capture, real-time migration monitoring, and enterprise-grade observability infrastructure. Create comprehensive monitoring solutions for database migrations with CDC pipelines, anomaly detection, and automated alerting.

Complete Clerk setup for Next.js 14/15 App Router.

Port existing Semgrep rules to new target languages with applicability analysis and test-driven validation. \n \n Takes an existing Semgrep rule and target languages as input; produces independent rule and test directories for each applicable language \n Requires mandatory applicability analysis per language before porting, rejecting shortcuts like assuming identical patterns across different ASTs \n Enforces test-first methodology: write minimum 2 vulnerable and 2 safe test cases before creatin

Help teams write focused, actionable product requirements documents using frameworks from 11 product leaders. \n \n Start with problem and context before solutions; include \"why now\" to justify timing and urgency against competing priorities \n Choose the right format for your product type: traditional PRDs for feature specs, prototypes or prompt sets for AI features, executable evals as living requirements \n Define success upfront with clear metrics and outcomes; keep documents lightweight a

Multi-core fuzzer for C/C++ projects with advanced instrumentation and mutation strategies. \n \n Supports three compilation modes (LTO, LLVM, GCC plugin) with libFuzzer-style harnesses for persistent fuzzing at 10-20x faster speeds than fork server mode \n Excels at parallel fuzzing across multiple cores with asymmetrical job configurations (e.g., one ASan instance plus non-instrumented workers) \n Includes CMPLOG/RedQueen path constraint solving, integrated sanitizer support (ASan, UBSan), and