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Found 1,352 Skills
Analiza cambios staged en git para detectar bugs, vulnerabilidades de seguridad, malas prácticas, y genera descripciones detalladas de commits con mensaje en formato Conventional Commits. Usa este skill siempre que el usuario quiera revisar cambios antes de commitear o pushear, analizar un diff staged, detectar bugs o malas prácticas en código que está por commitear, generar un mensaje o descripción de commit, o hacer code review previo al commit. Se activa con frases como "revisá mis cambios staged", "analiza mi commit", "qué bugs tiene lo que cambié", "generame el mensaje de commit", "review antes de push", "detecta errores en mis cambios", "haceme un análisis antes de commitear", o "necesito una descripción para mi commit". NO usar para: code review de archivos sueltos sin contexto de commit, configurar linters, escribir tests, debugging de producción, o crear código nuevo. Este skill es específicamente para el momento previo al commit.
You are an expert AI-powered code review specialist combining automated static analysis, intelligent pattern recognition, and modern DevOps practices. Leverage AI tools (GitHub Copilot, Qodo, GPT-5, C
Build or refresh engineering culture and produce an Engineering Culture Operating System Pack (capability map, culture code, org↔architecture alignment, clock-speed/DevEx backlog, workflow contract, rollout + measurement). Use for engineering culture, DevOps capabilities, DevEx, clock speed, Conway's Law, and engineering principles. Category: Engineering.
Designing Go libraries and packages for long-term evolution. Covers API surface management, dependency direction, backwards compatibility, trade-offs between parameter objects and functional options, and testability via deterministic simulation.
[DevOps & Infra] Run linters and fix issues for backend or frontend
Use when managing project uncertainty through structured risk tracking, identifying and assessing risks with probability×impact scoring (risk matrix), assigning risk owners and mitigation plans, tracking contingencies and triggers, monitoring risk evolution over project lifecycle, or when user mentions risk register, risk assessment, risk management, risk mitigation, probability-impact matrix, or asks "what could go wrong with this project?".
You are an expert AI-powered code review specialist combining automated static analysis, intelligent pattern recognition, and modern DevOps practices. Leverage AI tools (GitHub Copilot, Qodo, GPT-5, C
Use when defending constitutional order and peaceful institutions against deliberate destabilization or revolutionary disruption tactics. Applies when identifying, analyzing, or responding to chaos exploitation strategies documented in the chaos-seize skill.
Complete ClickHouse operations guide for DevOps and SRE teams managing production deployments. Provides practical guidance on monitoring essential metrics (query latency, throughput, memory, disk), introspecting system tables, performance analysis, scaling strategies (vertical and horizontal), backup/disaster recovery, tuning at query/server/table levels, and troubleshooting common issues. Use when diagnosing ClickHouse problems, optimizing performance, planning capacity, setting up monitoring, implementing backups, or managing production clusters. Includes resource management strategies for disk space, connections, and background operations plus production checklists.
Automatically discover and recommend relevant Claude skills when users encounter tasks that could benefit from specialized capabilities. Use this skill proactively when detecting any of these patterns: (1) User mentions working with specific file formats (PDF, DOCX, Excel, images, etc.), (2) User describes repetitive or specialized tasks (data analysis, code review, deployment, testing, document processing), (3) User asks if there's a tool or capability for something, (4) User struggles with domain-specific work (React development, SQL queries, DevOps, content writing), (5) User mentions needing best practices or patterns for a technology, (6) Any situation where a specialized skill could save time or improve quality. Search using SkillsMP API (if configured), skills.sh leaderboard, or GitHub as fallback. Recommend 1-3 most relevant skills and offer to install via npx skills add.
Intelligent multi-store memory system with human-like encoding, consolidation, decay, and recall. Use when setting up agent memory, configuring remember/forget triggers, enabling sleep-time reflection, building knowledge graphs, or adding audit trails. Replaces basic flat-file memory with a cognitive architecture featuring episodic, semantic, procedural, and core memory stores. Supports multi-agent systems with shared read, gated write access model. Includes philosophical meta-reflection that deepens understanding over time. Covers MEMORY.md, episode logging, entity graphs, decay scoring, reflection cycles, evolution tracking, and system-wide audit.
Execute authoring T-SQL (DDL, DML, data ingestion, transactions, schema changes) against Microsoft Fabric Data Warehouse and SQL endpoints from agentic CLI environments. Use when the user wants to: (1) create/alter/drop tables from terminal, (2) insert/update/delete/merge data via CLI, (3) run COPY INTO or OPENROWSET ingestion, (4) manage transactions or stored procedures, (5) perform schema evolution, (6) use time travel or snapshots, (7) generate ETL/ELT shell scripts, (8) create views/functions/procedures on Lakehouse SQLEP. Triggers: "create table in warehouse", "insert data via T-SQL", "load from ADLS", "COPY INTO", "run ETL with T-SQL", "alter warehouse table", "upsert with T-SQL", "merge into warehouse", "create T-SQL procedure", "warehouse time travel", "recover deleted warehouse data", "create warehouse schema", "deploy warehouse", "transaction conflict", "snapshot isolation error".