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Found 6,932 Skills
Build comprehensive ARCHITECTURE.md files for any repository following matklad's canonical guidelines. This skill should be used when creating codebase documentation that serves as a map for developers and AI agents, auditing existing repos for architectural understanding, or when users ask to 'document the architecture', 'create an architecture.md', or 'map this codebase'. Produces bird's eye views, ASCII/Mermaid diagrams, codemaps, invariants, and layer boundaries.
Master SQL and database queries across multiple systems. Generate optimized queries, analyze performance, design indexes, and troubleshoot slow queries for PostgreSQL, MySQL, MongoDB, and more.
Authorization system with role-based access control. Must-have for all apps that manage personal or access-restricted data.
Master SQL query optimization, indexing strategies, and EXPLAIN analysis to dramatically improve database performance and eliminate slow queries. Use when debugging slow queries, designing database schemas, or optimizing application performance.
Execute read-only SQL queries against multiple MySQL databases. Use when: (1) querying MySQL databases, (2) exploring database schemas/tables, (3) running SELECT queries for data analysis, (4) checking database contents. Supports multiple database connections with descriptions for intelligent auto-selection. Blocks all write operations (INSERT, UPDATE, DELETE, DROP, etc.) for safety.
Analyze competitor repositories with an evidence-based approach. Use this when tracking competitors, creating competitor profiles, or generating competitive analysis. CRITICAL - all analysis must be based on actual cloned code, never assumptions. Triggers include "analyze competitor", "add competitor", "competitive analysis", or "竞品分析".
Survey any codebase as a senior advisor and produce prioritized, self-contained implementation plans for OTHER models/agents to execute. Strictly read-only on source code — never implements, fixes, or refactors anything itself. Use when asked to audit a codebase, find improvement opportunities (bugs, security, performance, test coverage, tech debt, migrations, DX), suggest features or where to take the project next (roadmap, product direction), or generate handoff plans for another agent to implement.
SQL patterns for database querying and design
Migrates Oracle PL/SQL stored procedures to PostgreSQL PL/pgSQL. Translates Oracle-specific syntax, preserves method signatures and type-anchored parameters, leverages orafce where appropriate, and applies COLLATE "C" for Oracle-compatible text sorting. Use when converting Oracle stored procedures or functions to PostgreSQL equivalents during a database migration.
This skill should be used when the user asks to "connect to Turso", "use libSQL", "set up a Turso database", "query Turso with TypeScript", or needs guidance on Turso Cloud, embedded replicas, or vector search with libSQL.
Use when the user's product is built (or nearly built) and they want to get it live and accessible to customers. Triggers on phrases like "create my launch checklist", "how do I deploy this", "help me launch", "get this live", "put this in production", "ship it to customers", "what do I need to do to go live", or any request for a step-by-step path from working code to a product customers can use. Audits the current codebase — stack, services, environment variables, payments, deploy config — then writes a plain-English, step-by-step launch guide to `docs/launch-checklist.md`. Every step is marked as something the user must do themselves, something their coding agent can do, or both together, and all technical terms are explained for non-technical founders.
Audit and improve SQL quality systematically — catch performance smells in raw SQL, ORM-generated queries, schema/modeling decisions, migrations, or PR diffs, explain the database-level impact, give a corrected version, and make the tradeoff explicit. Generic by design: no project, domain, ORM, or language config — any context it needs (is this table transactional? is the scan intentional? what volume is expected?) is raised during analysis, never assumed. Reach for it whenever someone writes, reviews, or optimizes a query or data-access code — "review this query", "why is this slow", "check my migration", "is this index right", or when you see N+1, SELECT *, a cartesian/row explosion, three-plus joins, a missing date filter on a growing table, OFFSET pagination, LIKE '%term%', NOT IN with nullable columns, an unindexed ORDER BY, an unbounded list, or a long transaction — even when they never say the word "SQL". Use it both to validate new code and designs and to audit existing ones.