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Found 1,812 Skills
Implements OpenTelemetry (OTEL) logging with trace context correlation and structured logging. Use when setting up production logging with OTEL exporters, structlog/loguru integration, trace context propagation, and comprehensive test patterns. Covers Python implementations for FastAPI, Kafka consumers, and background jobs. Includes OTLP, Jaeger, and console exporters.
Configure notification channels and settings for account alerts and events. This skill provides Python SDK examples.
12 production-ready regulatory affairs and quality management skills for HealthTech/MedTech: ISO 13485 QMS, MDR 2017/745, FDA 510(k)/PMA, ISO 27001 ISMS, GDPR/DSGVO compliance, risk management (ISO 14971), CAPA, document control, and internal auditing. Python tools included (all stdlib-only). Works with Claude Code, Codex CLI, and OpenClaw.
Expert guidance for LangChain and LangGraph development with Python, covering chain composition, agents, memory, and RAG implementations.
This skill should be used when the user asks to "connect to MySQL with PyMySQL", "use PyMySQL in Python", "query a MySQL database with Python", "set up PyMySQL", or needs guidance on PyMySQL best practices, transactions, parameterized queries, or cursor types.
Comprehensive software development planning and implementation skill. Triggers when: Creating new Python software with CLI/GUI/Web interfaces, planning software architecture and modules, designing scientific or engineering applications, setting up bilingual documentation and PyPI publishing, or needing academic research-based feature design. Capabilities: Pre-development planning and research, multi-interface design (CLI + PySide6 GUI + Flask Web), scientific visualization with pyqtgraph, academic literature-based feature design, sample data and test documentation generation, bilingual README with structured sections, GPLv3 licensing and PyPI publishing setup.
Python video composition with moviepy 2.x — overlaying deterministic text on AI-generated video (LTX-2, SadTalker), compositing clips, single-file build.py video projects. Use when adding labels/captions/lower-thirds to LTX-2 or SadTalker outputs, building short ad-style spots in pure Python without Remotion, or doing programmatic video composition. Triggers include text overlay on video, label LTX-2 clip, caption SadTalker output, lower third, build.py video, moviepy, Python video composition, sub-30s ad spot.
Use the unified Opper SDKs (`opperai` package for both Python and TypeScript, with built-in agent support) for AI task completion, structured output with Pydantic / Zod / JSON Schema, knowledge base semantic search, streaming, tracing, tool use, and multi-agent composition. Use this skill whenever the user is writing Python or TypeScript code that imports `opperai`, builds an Opper agent, or asks how to do anything Opper-related in code — even if they don't explicitly name the SDK. Both languages live in one repo with parallel numbered examples; agents are part of the SDK, not a separate package.
Initialize Python Project (New or Fork). Use when the user wants to create a new production-ready Python/ML project structure, or fork and enhance an existing project. Uses uv for environment management.
[Hyper] Run deploy-readiness validation and fix reproduced lint/typecheck/build blockers for Node.js, Rust, and Python repos. Use for pre-deploy checks, deploy-ready requests, or final quality/build gates before deployment.
End-to-end epidemiological data analysis — from research question to statistical report. Covers study design assessment, dataset discovery and download, data wrangling, confounder adjustment, regression modeling, sensitivity analysis, visualization, and biological interpretation. Integrates ToolUniverse tools for dataset discovery, literature search, and biological context with Python code execution for data analysis. Use whenever users ask to analyze health data, study disease risk factors, assess exposure-outcome relationships, or conduct observational epidemiology. Also use when users want to run regression on clinical/survey data, calculate odds ratios or hazard ratios from a dataset, adjust for confounders, or produce a Table 1. If the task involves downloading a health dataset and running statistical analysis on it, this is the right skill.
Use when adding, retiring, or auditing feature flags. Triggers on "add a flag", "ship behind a flag", "rollout plan", "kill switch", "stale flags", "flag debt", "LaunchDarkly", "GrowthBook", "Statsig", "Unleash", "Flipt", or any progressive-delivery question. Ships flag debt scanner, rollout planner, and kill-switch auditor (all stdlib Python), 4 references on flag taxonomy + provider trade-offs + rollout strategies + lifecycle, plus a /flag-cleanup slash command.