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Found 365 Skills
Implement centralized logging with ELK Stack, Loki, or Splunk for log collection, parsing, storage, and analysis across infrastructure.
Generates Tzatziki-based Cucumber BDD tests (.feature files) from a functional specification. Use this skill whenever a user wants to write Cucumber tests, add BDD scenarios, create feature files, generate tests, or test application behaviors with Gherkin — especially in Java/Spring projects using Tzatziki step definitions for HTTP, JPA, Kafka, MongoDB, OpenSearch, logging, or MCP. Also use when the user mentions writing integration tests, acceptance tests, or end-to-end tests in a project that already has Tzatziki/Cucumber dependencies, including TestNG-based setups.
Scaffold and architect custom Frappe apps including app structure, hooks, background jobs, service layers, and production hardening. Use when creating new apps, setting up app architecture, or implementing cross-cutting patterns like caching, logging, and error handling.
Master Taubyte workflow skill. Enforces strict order with Dream-by-default routing, scope routing, context logging, and verification.
Implement structured logging with JSON formats, log levels (DEBUG, INFO, WARN, ERROR), contextual logging, PII handling, and centralized logging. Use for logging, observability, log levels, structured logs, or debugging.
Review code for logging patterns and suggest evlog adoption. Detects console.log spam, unstructured errors, and missing context. Guides wide event design, structured error handling, request-scoped logging, and log draining with adapters (Axiom, OTLP).
When you have a decision to make and want a structured workflow that picks the load-bearing questions, walks through them, reaches a call (or "wait"), and archives the rationale for future reference. Based on the 37signals Guide to Making Decisions (38 questions). Triages to 6–8 relevant questions per decision instead of forcing all 38. Archives every decision to references/decisions-archive/ with a revisit date so you can check later whether the call was right. Triggers on "/decide," "help me decide," "should I [X]," "I need to make a decision about," "stuck on a decision," "deciding between," "go/no-go on," "what should I do about." This is both the decision-making workflow AND the decision log — making the decision is the act of logging it.
Help a CS or AI PhD student design hypothesis-driven experiments with baselines, variables, metrics, controls, logging, and stop conditions. Use this skill whenever the user is about to run experiments, compare models, plan an ablation, debug inconclusive results, prepare an experiment section, or wants to avoid changing too many things at once.
Backend architecture principles, layering, error handling, logging patterns for NestJS. Use when designing NestJS modules, writing service logic, structuring error handling, or setting up structured logging.
Consult this skill when implementing usage logging and audit trails. Use when implementing audit trails, tracking costs, collecting usage analytics, managing session logging. Do not use when simple operations without logging needs.
Instrumenting Go applications with OpenTelemetry for distributed tracing, Prometheus for metrics, and structured logging with slog
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".