By yo-steven
Modern Python development with Python 3.12+, Django, FastAPI, async patterns, and production best practices
Master Django 5.x with async views, DRF, Celery, and Django Channels. Build scalable web applications with proper architecture, testing, and deployment. Use PROACTIVELY for Django development, ORM optimization, or complex Django patterns.
Build high-performance async APIs with FastAPI, SQLAlchemy 2.0, and Pydantic V2. Master microservices, WebSockets, and modern Python async patterns. Use PROACTIVELY for FastAPI development, async optimization, or API architecture.
Master Python 3.12+ with modern features, async programming, performance optimization, and production-ready practices. Expert in the latest Python ecosystem including uv, ruff, pydantic, and FastAPI. Use PROACTIVELY for Python development, optimization, or advanced Python patterns.
Master Python asyncio, concurrent programming, and async/await patterns for high-performance applications. Use when building async APIs, concurrent systems, or I/O-bound applications requiring non-blocking operations.
Use this skill when reviewing Python code for common anti-patterns to avoid. Use as a checklist when reviewing code, before finalizing implementations, or when debugging issues that might stem from known bad practices.
Python background job patterns including task queues, workers, and event-driven architecture. Use when implementing async task processing, job queues, long-running operations, or decoupling work from request/response cycles.
Python code style, linting, formatting, naming conventions, and documentation standards. Use when writing new code, reviewing style, configuring linters, writing docstrings, or establishing project standards.
Python configuration management via environment variables and typed settings. Use when externalizing config, setting up pydantic-settings, managing secrets, or implementing environment-specific behavior.
Uses power tools
Uses Bash, Write, or Edit tools
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Sign in to claimBased on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
This repo is a learning experiment by Steven Li based on wshobson/agents.
It is not affiliated with the original project. It records one day's experiment with the codebase.
tools/validate_agent_unique_names.py (+98 lines). Scans all .md files under plugins/, extracts the name field from YAML frontmatter with a lightweight regex-based parser, and reports any name that appears in more than one file. Exits with code 1 if duplicates exist, otherwise 0.tools/tests/test_validate_agent_unique_names.py (+121 lines). Five unit tests covering:
Total: 2 new files, ~219 lines added, 0 lines removed.
This repo is not maintained. Issues filed here will not be addressed. If you want the maintained version of the project, use the upstream repo.
If something here is useful, port it upstream yourself or open an issue on the upstream repo with a link to this work.
The original project workflow files are stored in UPSTREAM_WORKFLOWS_DISABLED/ for reference. They are not active in this snapshot.
The original LICENSE file is preserved verbatim in this repository.
Original project: wshobson/agents Upstream commit at fork time: cbcde3f1f4309f023095181d3e591f983ec7c95d
Self-contained GEO (Generative Engine Optimization) plugin: 7 slash commands orchestrate the pipeline (/01-intake → /07-reaudit), 7 vendored open-source skills supply commodity capabilities (audit, content writing, schema, internal linking, keyword expansion, quality scoring, frontend design) plus one original skill (geo-review-html) that renders interactive client-review HTML, 8 JSON schemas. Zero external deps, zero API keys for the default flow. Per-client folder convention.
Comprehensive skill pack with 66 specialized skills for full-stack developers: 12 language experts (Python, TypeScript, Go, Rust, C++, Swift, Kotlin, C#, PHP, Java, SQL, JavaScript), 10 backend frameworks, 6 frontend/mobile, plus infrastructure, DevOps, security, and testing. Features progressive disclosure architecture for 50% faster loading.
Lazy senior dev mode. Forces the simplest, shortest solution that actually works: YAGNI, stdlib first, no unrequested abstractions.
LLM application development with LangGraph, RAG systems, vector search, and AI agent architectures for Claude 4.6 and GPT-5.4
Self-improving Claude Code plugin — learns from corrections across sessions via reflexio
npx claudepluginhub yo-steven/agents-exploration-20260523 --plugin python-developmentAccess thousands of AI prompts and skills directly in your AI coding assistant. Search prompts, discover skills, save your own, and improve prompts with AI.
Complete developer toolkit for Claude Code
Intelligent draw.io diagramming plugin with AI-powered diagram generation, multi-platform embedding (GitHub, Confluence, Azure DevOps, Notion, Teams, Harness), conditional formatting, live data binding, and MCP server integration for programmatic diagram creation and management.
Feature development with code-architect/explorer/reviewer agents, CLAUDE.md audit and session learnings, and Agent Skills creation with eval benchmarking from Anthropic.
Orchestrate multi-agent teams for parallel code review, hypothesis-driven debugging, and coordinated feature development using Claude Code's Agent Teams
Production-grade engineering skills for AI coding agents — covering the full software development lifecycle from spec to ship.