By discopops
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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Verify ownership to unlock analytics, metadata editing, and a verified badge. GitHub access is read-only (username + org membership).
Sign in to claimBased on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
Production-ready agentic workflow building blocks: 83 plugins, 191 agents, 155 skills, 102 commands — built for Claude Code and consumed natively by OpenAI Codex CLI, Cursor, OpenCode, and Gemini CLI from a single Markdown source.
[!NOTE] One source-of-truth (
plugins/), five harnesses. Each harness gets idiomatic, harness-native artifacts — not lowest-common-denominator translations. See docs/harnesses.md for the capability matrix.
Pick your harness:
/plugin marketplace add wshobson/agents
/plugin install python-development # or any of 83 plugins
→ Full Claude Code setup, troubleshooting, and plugin catalog
gh repo clone wshobson/agents ~/agents
cd ~/agents
make generate HARNESS=<codex|cursor|opencode|gemini>
Setup details and per-harness gotchas: docs/harnesses.md. Gemini-specific setup: GEMINI.md (also auto-loaded by Gemini CLI).
| Count | What it is | |
|---|---|---|
| Plugins | 83 | Granular, single-purpose installable units (81 local + 2 external via git-subdir) |
| Agents | 191 | Domain experts (architecture, languages, infra, security, data, ML, docs, business, SEO) |
| Skills | 155 | Modular knowledge packages with progressive disclosure (load when activated) |
| Commands | 102 | Slash commands: scaffolding, security scans, test gen, infrastructure setup |
| Orchestrators | 16 | Multi-agent coordination workflows (full-stack, security, ML, incident response) |
Browse the catalog: docs/plugins.md · docs/agents.md · docs/agent-skills.md
Each plugin is isolated and composable: agents, commands, and skills are auto-discovered from directory structure. Installing a plugin loads only its components into context — not the whole marketplace.
plugins/python-development/
├── .claude-plugin/plugin.json
├── agents/ # 3 Python agents (python-pro, django-pro, fastapi-pro)
├── commands/ # 1 scaffolding command
└── skills/ # 16 specialized skills (async, testing, packaging, …)
Three-tier model strategy:
| Tier | Model | Use |
|---|---|---|
| 1 | Opus 4.7 | Architecture, security, code review, production-critical |
| 2 | inherit | User-chosen — backend, frontend, AI/ML, specialized |
| 3 | Sonnet | Docs, testing, debugging, API references |
| 4 | Haiku | Fast operational tasks, SEO, deployment, content |
This marketplace ships to five agentic harnesses from one Markdown source. Each adapter emits harness-native artifacts (not lowest-common-denominator translations):
| Harness | Generates | Notes |
|---|---|---|
| Claude Code | (source-of-truth) | Native marketplace.json + plugins/ |
| Codex CLI | .codex/skills/, .codex/agents/, AGENTS.md | 8 KB skill cap respected; commands → skills |
| Cursor | .cursor-plugin/, .cursor/rules/ | Thin marketplace + curated rules; reuses .claude/ |
| OpenCode | .opencode/agents/, .opencode/commands/ | permission: block from tools: allowlist |
| Gemini CLI | skills/, agents/, commands/ (TOML) | Native skills + subagents (April 2026 spec) |
make generate-all # all four
make validate # structural checks
make garden # drift / dead-link / cap detection
→ Full capability matrix and per-harness deep-dives
plugin-eval is a three-layer evaluation framework for measuring
and certifying plugin/skill quality:
uv run plugin-eval score path/to/skill --depth quick
uv run plugin-eval certify path/to/skill
→ PluginEval framework documentation
Detail lives in docs/. Read in this order:
npx claudepluginhub discopops/agents --plugin incident-responseMulti-perspective code analysis covering architecture, security, and best practices
Pre-deployment checks, configuration validation, and deployment readiness assessment
Database architecture, schema design, and SQL optimization for production systems
Deployment patterns, rollback automation, and infrastructure templates
Distributed system tracing and debugging across microservices
Harness-native ECC plugin for engineering teams - 67 agents, 278 skills, 94 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.
Consult multiple AI coding agents (Gemini, OpenAI, Grok, Perplexity, plus codex, antigravity, and grok CLIs when installed) to get diverse perspectives on coding problems
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.