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Build CI/CD pipelines for GitHub Actions, GitLab CI, Jenkins, and more

Build classification models

5 Claude Code skills for context management. Save, load, update, share, and audit session memory across resets.

Persistent memory across sessions. Learns preferences, conventions, and corrections automatically.

Self-learning system for Claude Code that captures corrections and updates CLAUDE.md automatically

Common workflow skills for Claude Code sessions: promote changes through the full release cycle, audit Claude Code plugins/skills/agents, audit project standards compliance, analyse projects for improvements, triage open GitHub issues, and review pull requests

Back up and restore your entire Claude Code environment to a private GitHub repo

Optimize cloud costs and generate cost reports

Run clustering algorithms on datasets

Check infrastructure compliance (SOC2, HIPAA, PCI-DSS)

Computer vision image processing and analysis

Manage container registries (ECR, GCR, Harbor)

Scan containers for vulnerabilities using Trivy, Snyk, and other security tools

Turn one idea, post, or transcript into a week of on-brand content across every channel and language — no accounts, no API keys, no setup.

Local-only OSS contribution command center with 41 deterministic gates against AI-slop failure modes

Debug REST API failures using OpenAPI specs and HTTP logs. Analyzes errors, suggests fixes, and generates test commands.

Evaluate model performance — check for accuracy drops, data drift, and error patterns. Use when asked about "model accuracy dropped", "evaluate the model", "check for drift", or "model performance".

Design and implement an AI feature integration — model selection, architecture pattern, system prompt, data flow, error handling, cost estimate. Use when asked to "add AI to this", "LLM integration", "add Claude/GPT", or "AI-powered feature".

Build an ML pipeline — from data to trained model to serving endpoint. Use when asked to "build ML model", "train a model", "prediction pipeline", "classification", or "regression".

Build a production-ready prompt package — system prompt, few-shot examples, output format, edge case handling, eval criteria. Use when asked to "prompt engineering", "build a prompt", "write a system prompt", or "improve this prompt".

ML reconnaissance — inventory all models, pipelines, data sources, and monitoring. Use when asked "what ML do we have", "model inventory", or "ML assessment".

Monitor and analyze CPU usage patterns in applications

Complete plugin suite for builder-filmmakers: Build products AND create viral videos explaining them. 20 plugins covering documentation, video production, content strategy, and workflow optimization.

Competitive analysis ending in a clear positioning call — where to play, how to win. Use when asked to "analyze competitors", "competitive landscape", "how do we compare to X", "competitive positioning", "where should we play", "find our white space", or "who else does this".