By yo-steven
Deployment patterns, rollback automation, and infrastructure templates
Expert deployment engineer specializing in modern CI/CD pipelines, GitOps workflows, and advanced deployment automation. Masters GitHub Actions, ArgoCD/Flux, progressive delivery, container security, and platform engineering. Handles zero-downtime deployments, security scanning, and developer experience optimization. Use PROACTIVELY for CI/CD design, GitOps implementation, or deployment automation.
Expert Terraform/OpenTofu specialist mastering advanced IaC automation, state management, and enterprise infrastructure patterns. Handles complex module design, multi-cloud deployments, GitOps workflows, policy as code, and CI/CD integration. Covers migration strategies, security best practices, and modern IaC ecosystems. Use PROACTIVELY for advanced IaC, state management, or infrastructure automation.
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
Uses power tools
Uses Bash, Write, or Edit tools
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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 deployment-strategiesComprehensive feature development workflow with specialized agents for codebase exploration, architecture design, and quality review
A growing collection of Claude-compatible academic workflow bundles. Covers scientific figures, manuscript writing and polishing, reviewer assessment, citation retrieval, data availability, paper reading, literature search, response letters, paper-to-PPTX conversion, and evidence-grounded Chinese invention patent drafting. Rules are organized as reusable skill folders with explicit workflows and quality checks.
Harness-native ECC plugin for engineering teams - 67 agents, 271 skills, 92 legacy command shims, reusable hooks, rules, MCP conventions, and operator workflows for Claude Code plus adjacent agent harnesses
Upstash Context7 MCP server for up-to-date documentation lookup. Pull version-specific documentation and code examples directly from source repositories into your LLM context.
Comprehensive PR review agents specializing in comments, tests, error handling, type design, code quality, and code simplification
Use this agent when creating user interfaces, designing components, building design systems, or improving visual aesthetics. This agent specializes in creating beautiful, functional interfaces that can be implemented quickly within 6-day sprints. Examples:\n\n<example>\nContext: Starting a new app or feature design