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Found 316 Skills
Two-layer memory architecture for board meeting decisions. Manages raw transcripts (Layer 1) and approved decisions (Layer 2). Use when logging decisions after a board meeting, reviewing past decisions with /cs:decisions, or checking overdue action items with /cs:review. Invoked automatically by the board-meeting skill after Phase 5 founder approval.
Debug Laravel applications systematically with this comprehensive troubleshooting skill. Covers class/namespace errors, database SQLSTATE issues, route problems (404/405), Blade template errors, middleware issues (CSRF/auth), queue job failures, and cache/session problems. Provides structured four-phase debugging methodology with Laravel Telescope, Debugbar, Artisan tinker, and logging best practices for development and production environments.
Debug Django web applications with systematic diagnostic approaches. This skill covers troubleshooting Django-specific errors including TemplateDoesNotExist, ImproperlyConfigured, IntegrityError, migration conflicts, CSRF failures, N+1 query problems, and circular imports. Includes Django Debug Toolbar setup, ORM query logging, pdb/ipdb usage, shell_plus debugging, and comprehensive logging configuration. Provides four-phase methodology for root cause analysis and regression prevention.
Debug Express.js and Node.js applications with systematic diagnostic techniques. This skill provides comprehensive guidance for troubleshooting middleware execution issues, routing problems, CORS errors, async error handling, memory leaks, and unhandled promise rejections. Covers DEBUG environment variable usage, Node Inspector with Chrome DevTools, VS Code debugging, Morgan request logging, and diagnostic middleware patterns. Includes four-phase debugging methodology and common error message reference.
Access and interact with Large Language Models from the command line using Simon Willison's llm CLI tool. Supports OpenAI, Anthropic, Gemini, Llama, and dozens of other models via plugins. Features include chat sessions, embeddings, structured data extraction with schemas, prompt templates, conversation logging, and tool use. This skill is triggered when the user says things like "run a prompt with llm", "use the llm command", "call an LLM from the command line", "set up llm API keys", "install llm plugins", "create embeddings", or "extract structured data from text".
Explain how to do logging
Structured logging for Python applications with context support and powerful processors
OWASP Top 10 CI/CD Security Risks - prevention, detection, and remediation for pipeline security. Use when securing or reviewing CI/CD - flow control, IAM, dependency chain, poisoned pipeline execution, PBAC, credential hygiene, system config, third-party services, artifact integrity, logging and visibility.
nginx C module performance optimization and reliability guidelines based on the official nginx development guide. This skill should be used when optimizing nginx C modules for throughput, latency, memory efficiency, and operational resilience. Triggers on tasks involving buffer optimization, connection tuning, shared memory contention, error recovery, timeout strategy, caching implementation, worker process tuning, or logging performance in nginx C modules.
Implement machine learning experiment tracking using MLflow or Weights & Biases. Configures environment and provides code for logging parameters, metrics, and artifacts. Use when asked to "setup experiment tracking" or "initialize MLflow". Trigger with relevant phrases based on skill purpose.
Automatically generate complete Python project deliverables from natural language requirements through collaboration among four virtual roles: autonomous learning, PM, architect, and senior programmer. Supports feature expansion, project refactoring, and skill invocation. Also supports web search, knowledge integration, version control, Python 3.11+ features, UV package management, loguru logging, and project size adaptation (folder/single file). It provides support for database design and implementation (SQLite, PostgreSQL, MongoDB, vector databases, graph databases), data layer abstraction (Repository pattern), and database switching. Suitable for scenarios such as software requirement clarification, rapid prototyping, project initialization, feature expansion, and code refactoring.
Complete command-line reference for managing the Temps deployment platform. Covers all 54+ CLI commands including projects, deployments, environments, services, domains, monitoring, backups, security scanning, error tracking, and platform administration. Use when the user wants to: (1) Find CLI command syntax, (2) Manage projects and deployments via CLI, (3) Configure services and infrastructure, (4) Set up monitoring and logging, (5) Automate deployments with CI/CD, (6) Manage domains and DNS, (7) Configure notifications and webhooks. Triggers: "temps cli", "temps command", "how to use temps", "@temps-sdk/cli", "bunx temps", "npx temps", "temps deploy", "temps projects", "temps services".