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Found 228 Skills
Monitoring and observability patterns for Prometheus metrics, Grafana dashboards, Langfuse LLM tracing, and drift detection. Use when adding logging, metrics, distributed tracing, LLM cost tracking, or quality drift monitoring.
Set up comprehensive observability for Databricks with metrics, traces, and alerts. Use when implementing monitoring for Databricks jobs, setting up dashboards, or configuring alerting for pipeline health. Trigger with phrases like "databricks monitoring", "databricks metrics", "databricks observability", "monitor databricks", "databricks alerts", "databricks logging".
Dynamic tier system for right-sizing n8n workflow hardening. Use this skill on ANY n8n workflow request to determine appropriate validation, logging, and error handling levels. Adapts to user needs — from quick prototypes to mission-critical production systems.
This skill should be used when the user asks to "generate audit logs", "create HIPAA audit trail", "log healthcare events", "configure audit logging", "track PHI access", "maintain compliance logs", "audit log format", "healthcare event logging", "access control logging", "authentication logging", "HIPAA logging requirements", or mentions HIPAA audit trails, healthcare event logging, compliance logging, PHI access tracking, authentication auditing, or §164.312(b) logging requirements.
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.
World-class application logging - structured logs, correlation IDs, log aggregation, and the battle scars from debugging production without proper logsUse when "log, logging, logger, debug, trace, audit, structured log, correlation id, request id, log level, winston, pino, bunyan, log4j, logging, observability, debugging, monitoring, tracing, structured-logs, correlation, aggregation" mentioned.
Manage agent memory through daily logs, session preservation, and knowledge extraction. Use when (1) logging work at end of day, (2) preserving context before /new or /reset, (3) extracting patterns from daily logs to MEMORY.md, (4) searching past decisions and learnings, (5) organizing knowledge for long-term retention. Essential for continuous improvement and avoiding repeated mistakes.
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".