By yo-steven
Production incident management, triage workflows, and automated incident resolution
Orchestrate multi-agent incident response with modern SRE practices for rapid resolution and learning
Intelligent issue resolution with multi-agent debugging, root cause analysis, and verified fix implementation
Reviews code for logic flaws, type safety gaps, error handling issues, architectural concerns, and similar vulnerability patterns. Provides fix design recommendations.
Performs deep root cause analysis through code path tracing, git bisect automation, dependency analysis, and systematic hypothesis testing for production bugs.
Expert DevOps troubleshooter specializing in rapid incident response, advanced debugging, and modern observability. Masters log analysis, distributed tracing, Kubernetes debugging, performance optimization, and root cause analysis. Handles production outages, system reliability, and preventive monitoring. Use PROACTIVELY for debugging, incident response, or system troubleshooting.
Analyzes error traces, logs, and observability data to identify error signatures, reproduction steps, user impact, and timeline context for production issues.
Expert SRE incident responder specializing in rapid problem resolution, modern observability, and comprehensive incident management. Masters incident command, blameless post-mortems, error budget management, and system reliability patterns. Handles critical outages, communication strategies, and continuous improvement. Use IMMEDIATELY for production incidents or SRE practices.
Create structured incident response runbooks with step-by-step procedures, escalation paths, and recovery actions. Use this skill when building a service outage runbook for a payment processing system; creating database incident procedures covering connection pool exhaustion, replication lag, and disk space alerts; onboarding new on-call engineers who need step-by-step recovery guides written for a 3 AM brain; or standardizing escalation matrices across multiple engineering teams.
Master on-call shift handoffs with context transfer, escalation procedures, and documentation. Use this skill when transitioning on-call responsibilities between engineers and ensuring the incoming responder has full situational awareness, when writing a shift summary that captures active incidents, ongoing investigations, and recent changes, when handing off mid-incident so a fresh engineer can take over the incident commander role without losing context, when onboarding a new engineer to the on-call rotation for the first time, or when auditing and improving the quality of existing handoff processes across teams.
Write effective blameless postmortems with root cause analysis, timelines, and action items. Use when conducting incident reviews, writing postmortem documents, or improving incident response processes.
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 incident-responseComprehensive feature development workflow with specialized agents for codebase exploration, architecture design, and quality review
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.
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.
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.
Tools to maintain and improve CLAUDE.md files - audit quality, capture session learnings, and keep project memory current.