Skill UI

Scans Solana and Anchor programs for six critical security vulnerabilities—arbitrary CPI, improper PDA validation, missing signer/ownership checks, sysvar spoofing, and instruction introspection issues—to support audits and pre-launch reviews.

This skill guides the mastery of smart contract security best practices for Solidity. It is essential for writing robust, secure, and efficient contracts, auditing existing code for common vulnerabilities (such as reentrancy, overflow, and access control issues), and implementing secure DeFi protocols. It focuses on preventing common attack vectors while optimizing gas usage.

This guide helps developers diagnose and fix common issues encountered when integrating the Speak API. It covers critical errors such as authentication failures, incorrect audio formats, rate limiting (429), and session expiration. The resource includes comprehensive HTTP error code reference tables, diagnostic commands (cURL, ffprobe), and resilient code patterns for implementing robust, production-ready error recovery mechanisms.

A comprehensive diagnostic bundle designed for developers integrating with the Speak API. It systematically collects critical information, including authentication status, audio format validation (checking codecs, sample rates, and file size using ffprobe), and network connectivity tests for both Speak and OpenAI endpoints. Use this tool when troubleshooting complex language learning integration issues or verifying API setup.

Structured pre-PR verification loop for Spring Boot projects that runs fast-build checks, static analysis, tests with coverage, security scans, formatting gates, and diff reviews to catch issues before deployment.

This skill provides systematic patterns and best practices for transforming slow database queries into high-performance operations. It covers techniques like proper indexing, query plan analysis (e.g., using EXPLAIN), schema design improvements, and resolving common issues like N+1 query problems. Use it to debug performance bottlenecks, reduce database load, and ensure scalable application backends.

Scans Substrate/Polkadot FRAME pallets for seven critical vulnerabilities such as arithmetic overflow, panic DoS, incorrect weights, unsigned validation issues, bad randomness, and origin flaws, making it ideal for runtime audits and pre-launch security assessments.

A comprehensive guide for deep PostgreSQL diagnostics, designed for advanced troubleshooting when standard methods fail. Covers using pg_stat_statements for identifying slow queries, analyzing lock contention with pg_locks, detecting connection leaks, debugging RLS policy conflicts, and profiling Edge Function cold starts. Essential for performance regression investigation and escalating issues to support.

This tool collects a comprehensive, redacted diagnostic bundle from a Supabase project. It systematically tests connectivity, authentication (Auth), Realtime capabilities, Storage buckets, and Row-Level Security (RLS) policies. The resulting archive is designed for sharing with support teams to accelerate troubleshooting of complex issues like connection failures or misconfigurations.

A comprehensive guide for structured incident response when a Supabase-backed application fails. This runbook guides users through triaging issues, verifying platform status, inspecting connection pools, debugging stuck queries using pg_stat_activity, and analyzing Edge Function logs. Essential for root cause analysis and escalating issues to support.

A comprehensive guide detailing the most common and critical mistakes when developing with Supabase. Covers severe security issues (like exposing service role keys or missing RLS), data integrity failures, and performance bottlenecks (connection pooling, N+1 queries). Essential for code review, onboarding new developers, or auditing existing Supabase projects to ensure secure and robust applications.

A disciplined debugging ritual that forces you to investigate errors, reproduce issues, and analyze patterns before proposing fixes, ensuring root causes are understood across multi-component systems and minimizing risky guesswork under pressure.