By discopops
Orchestrate multi-agent teams for parallel code review, hypothesis-driven debugging, and coordinated feature development using Claude Code's Agent Teams
Develop features in parallel with multiple agents using file ownership boundaries and dependency management
Debug issues using competing hypotheses with parallel investigation by multiple agents
Task delegation dashboard for managing team workload, assignments, and rebalancing
Launch a multi-reviewer parallel code review with specialized review dimensions
Gracefully shut down an agent team, collect final results, and clean up resources
Hypothesis-driven debugging investigator that investigates one assigned hypothesis, gathering evidence to confirm or falsify it with file:line citations and confidence levels. Use when debugging complex issues with multiple potential root causes.
Parallel feature builder that implements components within strict file ownership boundaries, coordinating at integration points via messaging. Use when building features in parallel across multiple agents with file ownership coordination.
Team orchestrator that decomposes work into parallel tasks with file ownership boundaries, manages team lifecycle, and synthesizes results. Use when coordinating multi-agent teams, decomposing complex tasks, or managing parallel workstreams.
Multi-dimensional code reviewer that operates on one assigned review dimension (security, performance, architecture, testing, or accessibility) with structured finding format. Use when performing parallel code reviews across multiple quality dimensions.
Coordinate parallel code reviews across multiple quality dimensions with finding deduplication, severity calibration, and consolidated reporting. Use this skill when organizing multi-reviewer code reviews, calibrating finding severity, or consolidating review results.
Debug complex issues using competing hypotheses with parallel investigation, evidence collection, and root cause arbitration. Use this skill when debugging bugs with multiple potential causes, performing root cause analysis, or organizing parallel investigation workflows.
Coordinate parallel feature development with file ownership strategies, conflict avoidance rules, and integration patterns for multi-agent implementation. Use this skill when decomposing a large feature into independent work streams, when two or more agents need to implement different layers of the same system simultaneously, when establishing file ownership to prevent merge conflicts in a shared codebase, when designing interface contracts so parallel implementers can build against each other's APIs before they are ready, or when deciding whether to use vertical slices versus horizontal layers for a full-stack feature.
Decompose complex tasks, design dependency graphs, and coordinate multi-agent work with proper task descriptions and workload balancing. Use this skill when breaking down work for agent teams, managing task dependencies, or monitoring team progress.
Structured messaging protocols for agent team communication including message type selection, plan approval, shutdown procedures, and anti-patterns to avoid. Use this skill when establishing communication norms for a newly spawned team, when deciding whether to send a direct message or a broadcast, when a team-lead needs to review and approve an implementer's plan before work begins, when orchestrating a graceful team shutdown after all tasks are complete, or when debugging why teammates are not coordinating correctly at integration points.
Uses power tools
Uses Bash, Write, or Edit tools
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Production-ready agentic workflow building blocks: 82 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 82 plugins
→ Full Claude Code setup, troubleshooting, and plugin catalog
gh repo clone wshobson/agents ~/agents
cd ~/agents
make generate HARNESS=<codex|cursor|opencode|gemini>
Per-harness setup guides: CODEX.md · CURSOR.md · OPENCODE.md · GEMINI.md
| Count | What it is | |
|---|---|---|
| Plugins | 82 | Granular, single-purpose installable units (81 local + 1 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:
Multi-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
npx claudepluginhub discopops/agents --plugin agent-teamsAccess thousands of AI prompts and skills directly in your AI coding assistant. Search prompts, discover skills, save your own, and improve prompts with AI.
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Feature development with code-architect/explorer/reviewer agents, CLAUDE.md audit and session learnings, and Agent Skills creation with eval benchmarking from Anthropic.