An OpenCode and Codex CLI plugin that bundles agent skills, MCP servers, parallel execution, and superpowers into a single install.
Обзор
An OpenCode and Codex CLI plugin that bundles agent skills, MCP servers, parallel execution, and superpowers into a single install.
README
OmAgents
An OpenCode and Codex CLI plugin that bundles agent skills, MCP servers, parallel execution, and superpowers into a single install.
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Read this and install omagents: https://raw.githubusercontent.com/omagents/omagents/main/README.md
Installation
TL;DR
| You want | Do this | What happens |
|---|---|---|
| Stable (npm) | Add "@omagents/omagents" to opencode.json plugin array |
Plugin auto-installs from npm, superpowers bundled |
| Pinned | Add "@omagents/omagents@^0.1.0" |
Same, but locked to a version range |
| Bleeding edge (git) | Add "@omagents/omagents@git+https://github.com/omagents/omagents.git" |
Latest source from main branch |
For Humans
Prerequisites:
- OpenCode installed and running
- Python 3.11+ installed and on PATH (required for deep-research, markitdown-converter, playwright-web-scraping, and loop engine)
- Open your OpenCode config:
open -e ~/.config/opencode/opencode.json
- Add
@omagents/omagentsto thepluginarray:
{
"plugin": [
"@omagents/omagents"
]
}
- Restart OpenCode.
Or, use the CLI setup command:
npx @omagents/omagents opencode
That’s it. At session start OmAgents will automatically:
- Install superpowers (bundled, no separate install needed)
- Register all skills (OmAgents + Superpowers)
- Register all MCP servers (agentmemory, codegraph, context7, websearch, github/grep_app)
- Enable parallel execution (background agents with
/psandcancel_task) - Set up Python venv at
~/.venvs/omagents(installsjinja2for report templates) - Check Python prerequisite (warns with install instructions if Python is missing)
For LLM Agents
If you’re an AI agent helping a user install OmAgents, follow these steps:
# 1. Read the user's current OpenCode config
cat ~/.config/opencode/opencode.json
# 2. Add "@omagents/omagents" to the plugin array
# Use jq if available, otherwise edit manually
# 3. Verify the config is valid JSON after editing
# 4. Tell the user to restart OpenCode
The plugin handles everything else automatically - no manual MCP configuration, no skill installation, no venv setup.
Optional: API Keys
Some remote MCP servers accept optional API keys for higher rate limits:
# ~/.zshrc or ~/.bashrc
export EXA_API_KEY="your-exa-key"
export CONTEXT7_API_KEY="your-context7-key"
export GITHUB_TOKEN="your-github-token"
Setting GITHUB_TOKEN enables the full GitHub Copilot MCP (issues, PRs, repos, code search). Without it, OmAgents falls back to Vercel’s mcp.grep.app for public code search only.
Combine with Other Plugins
OmAgents’ hook merging mechanism ensures no conflicts with additional plugins:
{
"plugin": [
"@omagents/omagents",
"@devcxl/opencode-spec"
]
}
Codex CLI
Prerequisite: Python 3.11+ installed and on PATH.
npx @omagents/omagents codex
This installs the OmAgents plugin into ~/.codex/plugins/cache/omagents/omagents/local/ and enables it in ~/.codex/config.toml. At session start, the plugin auto-discovers bundled skills, MCP servers, and sets up the Python venv via SessionStart hooks.
The OpenCode-only parallel execution engine is not available; use Codex’s native subagent tools for parallel dispatch.
Highlights
| Feature | What it does | |
|---|---|---|
| 🔁 | Loop Engineering | Durable task queues for iterative skills. Survives context clearing, retry logic, unified summary. Used by 8 skills |
| 🧠 | Superpowers (14 skills) | Brainstorming before implementation, TDD, systematic debugging, plan writing, code review, git worktrees |
| 🔍 | Deep Research | Multi-source iterative research with items × fields matrix, gap detection loop, Jinja2 reports |
| ⚡ | Parallel Execution | Background task dispatch via task(background: true), Job Board with persistence + session isolation, /ps command |
| 📚 | Built-in MCPs | agentmemory, codegraph, context7, websearch, github/grep_app - all auto-registered |
| 🐍 | Python Tooling | Dedicated venv at ~/.venvs/omagents, auto-installs jinja2 and skill dependencies |
| 📄 | MarkItDown | Convert PDF, DOCX, XLSX, PPTX, HTML to Markdown |
| 📊 | OfficeCLI | Create, analyze, proofread, and modify .docx/.xlsx/.pptx via officecli |
| 🌐 | Web Scraping | Playwright-based page fetching and scraping |
| 🔗 | GitHub | Full GitHub API when GITHUB_TOKEN is set; falls back to mcp.grep.app without token |
| 🏗️ | Refactor | Systematic code refactoring with loop engine verification |
| 🛡️ | Hyperplan | Adversarial plan review with 3 parallel critics (security, architecture, edge cases) |
| 🔧 | Code Intelligence | LSP guide + AST-grep for structural code search and rewrite |
Loop Engineering
OmAgents pioneers loop engineering for AI agent skills. Instead of one-shot prompts that say “scan everything and fix it,” loop-based skills use a durable task queue that processes items one at a time with verification.
How It Works
Phase 1: Build Task Queue Phase 2: Execute Loop Phase 3: Report
┌─────────────────────┐ ┌──────────────────────────┐ ┌─────────────────┐
│ Scan codebase │ │ loop_engine.py next │ │ loop_engine.py │
│ Build task list │───>│ -> get next task │───>│ summary │
│ loop_engine.py init │ │ -> execute + verify │ │ Show results │
└─────────────────────┘ │ -> complete or fail │ └─────────────────┘
│ -> repeat until null │
└──────────────────────────┘
State persists in .omagents/loops//tasks.json – if the agent’s context is cleared mid-task, it can resume exactly where it left off.
Retry logic: Failed tasks retry up to 3 times before being marked blocked.
Compaction safe: The experimental.session.compacting hook injects loop engine state into the compaction prompt, so the agent knows to resume after context clearing.
Skills Using Loop Engineering
| Skill | What it loops over | Verification |
|---|---|---|
deep-research |
Research tasks -> gap detection -> new tasks | Findings validation + coverage matrix |
remove-ai-slops |
Source files (one per task) | Lint / test pass |
remove-deadcode |
Dead code candidates (one per task) | Test pass after removal |
github-triage |
Open issues (one per task) | Labels applied successfully |
tech-debt-audit |
Audit categories (one per task) | Findings collected |
pre-publish-review |
Release checklist items (one per task) | Each check passes |
hyperplan |
3 parallel critics (tracked, not sequential) | Critic produces findings |
refactor |
Refactoring targets (one file per task) | Tests pass after refactor |
Loop Engine API
loop_engine.py init '' # Initialize task queue
loop_engine.py next # Get next pending task
loop_engine.py complete [result] # Mark task complete
loop_engine.py fail [error] # Mark task failed (retries 3x)
loop_engine.py status # Print stats
loop_engine.py summary # Full task list with icons
loop_engine.py reset # Clear queue
loop_engine.py add '' # Add task to existing queue
What’s Included
Skills
| Skill | Source | Loop? | Description |
|---|---|---|---|
deep-research |
OmAgents | Yes | Multi-source, iterative research with items × fields, gap detection, Jinja2 reports |
parallel-execution |
OmAgents | - | Background parallel task dispatch with Job Board tracking |
agents-python-tools |
OmAgents | - | Routes Python tooling to the dedicated ~/.venvs/omagents venv |
markitdown-converter |
OmAgents | - | Convert documents (PDF, DOCX, XLSX, etc.) to Markdown |
officecli |
OmAgents | - | Create, analyze, proofread, and modify Office documents (.docx, .xlsx, .pptx) via officecli |
playwright-web-scraping |
OmAgents | - | Web scraping and page fetching with Playwright |
init-deep |
OmAgents | - | Auto-generate hierarchical AGENTS.md files |
doctor |
OmAgents | - | Diagnose OmAgents installation and configuration |
remove-ai-slops |
OmAgents | Yes | Clean up AI-generated code artifacts (loop: file-by-file) |
remove-deadcode |
OmAgents | Yes | Find and remove unreferenced code (loop: candidate-by-candidate) |
github-triage |
OmAgents | Yes | Triage and categorize GitHub issues (loop: issue-by-issue) |
tech-debt-audit |
OmAgents | Yes | Audit codebase for technical debt (loop: category-by-category) |
lsp-guide |
OmAgents | - | Guide agents to use the right code intelligence tool (LSP, codegraph, grep, ast-grep) |
ast-grep |
OmAgents | Optional | AST-aware code search and rewrite with grep fallback |
work-with-pr |
OmAgents | - | PR lifecycle management with github MCP |
pre-publish-review |
OmAgents | Yes | Pre-publish release gate checklist (loop: check-by-check) |
hyperplan |
OmAgents | Yes | Adversarial plan review with 3 parallel critics (loop: critic tracking) |
refactor |
OmAgents | Yes | Systematic code refactoring with verification (loop: file-by-file) |
superpowers (14 skills) |
Superpowers | - | Brainstorming, TDD, debugging, planning, git worktrees, and more |
MCP Servers
| MCP | Type | Notes |
|---|---|---|
agentmemory |
Local | Session memory and audit |
codegraph |
Local | Codebase symbol graph and exploration |
context7 |
Remote | Documentation search (free tier available) |
websearch |
Remote | Web search via Exa (free tier available) |
github / grep_app |
Remote | GitHub Copilot MCP when GITHUB_TOKEN is set; otherwise mcp.grep.app for public code search |
Parallel Execution
- Background task dispatch via OpenCode’s native
task(background: true) - Job Board tracking with automatic result injection
- Persistence: Job Board survives restart (saved to
job-board.json) - Session isolation: Each session only sees its own jobs (no cross-session leak)
- Compaction safe: Loop engine and Job Board state preserved across context compaction
/pscommand to check running taskscancel_tasktool to cancel background tasksparallel_statustool for programmatic status checks
Architecture
OmAgents is designed as a layered system:
┌─────────────────────────────────────────────────┐
│ User Choice Layer (not bundled, install separately) │
│ OpenSpec · gstack · custom workflows · none │
├─────────────────────────────────────────────────┤
│ Process Skills Layer (bundled: superpowers) │
│ Brainstorming · TDD · Debugging · Plans · │
│ Code Review · Git Worktrees · Verification │
├─────────────────────────────────────────────────┤
│ Infrastructure Layer (bundled: OmAgents) │
│ MCP servers · Parallel execution · │
│ Deep research · Python tooling · venv │
├─────────────────────────────────────────────────┤
│ OpenCode runtime │
└─────────────────────────────────────────────────┘
OmAgents is the infrastructure layer. It provides the tools and capabilities agents need: MCP servers for external data, parallel execution for background tasks, research workflows, and Python environment management.
Superpowers is the process skills layer. It provides reusable development workflows: brainstorming before implementation, test-driven development, systematic debugging, plan writing and execution, code review, and git worktree management.
The user choice layer is not bundled. Development methodology is a choice - spec-driven development (OpenSpec), team-based engineering workflow (gstack), or no methodology at all. OmAgents stays neutral so users can pick what fits their project.
Uninstallation
- Remove the plugin from your OpenCode config:
# Using jq
jq '.plugin = [.plugin[] | select(. != "@omagents/omagents")]' \
~/.config/opencode/opencode.json > /tmp/oc.json && \
mv /tmp/oc.json ~/.config/opencode/opencode.json
- Remove the Python venv (optional):
rm -rf ~/.venvs/omagents
- Restart OpenCode.
Development
Project structure:
omagents/
├── index.js # Unified entry (OpenCode plugin export + Codex CLI installer)
├── .opencode/plugins/
│ ├── index.js # OpenCode plugin (merges superpowers + omagents hooks)
│ └── parallel.js # Parallel execution engine
├── .codex/plugins/
│ └── install.js # Codex installer (run via npx @omagents/omagents)
├── hooks/
│ └── setup-venv.sh # Shared venv setup hook (OpenCode + Codex)
├── skills/ # Bundled skills (18 OmAgents + 14 Superpowers)
│ ├── _shared/scripts/ # Shared scripts (loop_engine.py)
│ ├── deep-research/ # Research workflow with gap detection
│ └── ... # 16 more skills
├── mcp-servers/
│ └── base.json # MCP server definitions (single source of truth)
├── tests/ # Node.js built-in test runner
├── AGENTS.md # AI agent context file
├── package.json # Includes superpowers as dependency
└── README.md
Testing
# Run all tests
npm test
# Check formatting
npm run format:check
# Format code
npm run format
Publishing
OmAgents uses OIDC Trusted Publishing - no npm token required.
# Bump version
npm version patch # 0.1.0 -> 0.1.1
# Push tag (triggers GitHub Actions auto-publish)
git push && git push --tags
Configure Trusted Publisher at npmjs.com -> Settings -> Trusted Publisher.
License
MIT - see LICENSE.
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Установка
npx skillfish add omagents/omagents