oh-my-opencode
Multi-agent orchestration plugin for OpenCode. Use when the user wants to install, configure, or operate oh-my-opencode — including agent delegation, ultrawork mode, Prometheus planning, background tasks, category-based task routing, model resolution, tmux integration, or any oh-my-opencode feature. Covers installation, configuration, all agents (Sisyphus, Oracle, Librarian, Explore, Atlas, Prometheus, Metis, Momus), all categories, slash commands, hooks, skills, MCPs, and troubleshooting.
What this skill does
# Oh My OpenCode Multi-agent orchestration plugin that transforms OpenCode into a full agent harness with specialized agents, background task execution, category-based model routing, and autonomous work modes. **Package**: `oh-my-opencode` (install via `bunx oh-my-opencode install`) **Repository**: https://github.com/code-yeongyu/oh-my-opencode **Schema**: https://raw.githubusercontent.com/code-yeongyu/oh-my-opencode/master/assets/oh-my-opencode.schema.json --- ## Prerequisites 1. **OpenCode** installed and configured (`opencode --version` should be 1.0.150+) ```bash curl -fsSL https://opencode.ai/install | bash # or: npm install -g opencode-ai # or: bun install -g opencode-ai ``` 2. At least one LLM provider authenticated (`opencode auth login`) 3. **Strongly recommended**: Anthropic Claude Pro/Max subscription (Sisyphus uses Claude Opus 4.5) --- ## Installation Run the interactive installer: ```bash bunx oh-my-opencode install ``` Non-interactive mode with provider flags: ```bash bunx oh-my-opencode install --no-tui \ --claude=<yes|no|max20> \ --openai=<yes|no> \ --gemini=<yes|no> \ --copilot=<yes|no> \ --opencode-zen=<yes|no> \ --zai-coding-plan=<yes|no> ``` Verify: ```bash opencode --version cat ~/.config/opencode/opencode.json # should contain "oh-my-opencode" in plugin array ``` --- ## Two Workflow Modes ### Mode 1: Ultrawork (Quick Autonomous Work) Include `ultrawork` or `ulw` in your prompt. That's it. ``` ulw add authentication to my Next.js app ``` The agent will automatically: 1. Explore your codebase to understand existing patterns 2. Research best practices via specialized background agents 3. Implement the feature following your conventions 4. Verify with diagnostics and tests 5. Keep working until 100% complete ### Mode 2: Prometheus (Precise Planned Work) For complex or critical tasks: 1. **Press Tab** → switches to Prometheus (Planner) mode 2. **Describe your work** → Prometheus interviews you, asking clarifying questions while researching your codebase 3. **Confirm the plan** → review generated plan in `.sisyphus/plans/*.md` 4. **Run `/start-work`** → Atlas orchestrator takes over: - Distributes tasks to specialized sub-agents - Verifies each task completion independently - Accumulates learnings across tasks - Tracks progress across sessions (resume anytime) **Critical rule**: Do NOT use Atlas without `/start-work`. Prometheus and Atlas are a pair — always use them together. --- ## Agents All agents are enabled by default. Each has a default model and provider priority fallback chain. | Agent | Role | Default Model | Provider Priority Chain | |-------|------|---------------|------------------------| | **Sisyphus** | Primary orchestrator | `claude-opus-4-5` | anthropic → kimi-for-coding → zai-coding-plan → openai → google | | **Sisyphus-Junior** | Focused task executor (used by `delegate_task` with categories) | Determined by category | Per-category chain | | **Hephaestus** | Autonomous deep worker — goal-oriented, explores before acting | `gpt-5.2-codex` (medium) | openai → github-copilot → opencode (requires gpt-5.2-codex) | | **Oracle** | Architecture, debugging, high-IQ reasoning (read-only) | `gpt-5.2` | openai → google → anthropic | | **Librarian** | Official docs, OSS search, remote codebase analysis | `glm-4.7` | zai-coding-plan → opencode → anthropic | | **Explore** | Fast codebase grep (contextual search) | `claude-haiku-4-5` | anthropic → github-copilot → opencode | | **Multimodal Looker** | Image/PDF/diagram analysis | `gemini-3-flash` | google → openai → zai-coding-plan → kimi-for-coding → anthropic → opencode | | **Prometheus** | Work planner (interview-based plan generation) | `claude-opus-4-5` | anthropic → kimi-for-coding → openai → google | | **Metis** | Pre-planning consultant (ambiguity/failure-point analysis) | `claude-opus-4-5` | anthropic → kimi-for-coding → openai → google | | **Momus** | Plan reviewer (clarity, verifiability, completeness) | `gpt-5.2` | openai → anthropic → google | | **Atlas** | Plan orchestrator (executes Prometheus plans via `/start-work`) | `k2p5` / `claude-sonnet-4-5` | kimi-for-coding → opencode → anthropic → openai → google | | **OpenCode-Builder** | Default build agent (disabled by default when Sisyphus is active) | System default | System default | ### Agent Invocation Agents are invoked via `delegate_task()` or the `--agent` CLI flag — NOT with `@` prefix. ```javascript // Invoke a specific agent delegate_task(subagent_type="oracle", prompt="Review this architecture...") // Invoke via category (routes to Sisyphus-Junior with category model) delegate_task(category="visual-engineering", load_skills=["frontend-ui-ux"], prompt="...") // Background execution (non-blocking) delegate_task(subagent_type="explore", run_in_background=true, prompt="Find auth patterns...") ``` CLI: ```bash opencode --agent oracle opencode run --agent librarian "Explain how auth works in this codebase" ``` ### When to Use Which Agent | Situation | Agent | |-----------|-------| | General coding tasks | Sisyphus (default) | | Autonomous goal-oriented deep work | Hephaestus (requires gpt-5.2-codex) | | Architecture decisions, debugging after 2+ failures | Oracle | | Looking up library docs, finding OSS examples | Librarian | | Finding code patterns in your codebase | Explore | | Analyzing images, PDFs, diagrams | Multimodal Looker | | Complex multi-day projects needing a plan | Prometheus + Atlas (via Tab → `/start-work`) | | Pre-planning scope analysis | Metis | | Reviewing a generated plan for gaps | Momus | | Quick single-file changes | delegate_task with `quick` category | --- ## Categories Categories route tasks to Sisyphus-Junior with domain-optimized models via `delegate_task()`. | Category | Default Model | Variant | Provider Priority Chain | Best For | |----------|---------------|---------|------------------------|----------| | `visual-engineering` | `gemini-3-pro` | — | google → anthropic → zai-coding-plan | Frontend, UI/UX, design, styling, animation | | `ultrabrain` | `gpt-5.2-codex` | `xhigh` | openai → google → anthropic | Deep logical reasoning, complex architecture | | `deep` | `gpt-5.2-codex` | `medium` | openai → anthropic → google | Goal-oriented autonomous problem-solving (Hephaestus-style) | | `artistry` | `gemini-3-pro` | `max` | google → anthropic → openai | Creative/novel approaches, unconventional solutions | | `quick` | `claude-haiku-4-5` | — | anthropic → google → opencode | Trivial tasks, single file changes, typo fixes | | `unspecified-low` | `claude-sonnet-4-5` | — | anthropic → openai → google | General tasks, low effort | | `unspecified-high` | `claude-opus-4-5` | `max` | anthropic → openai → google | General tasks, high effort | | `writing` | `gemini-3-flash` | — | google → anthropic → zai-coding-plan → openai | Documentation, prose, technical writing | ### Category Usage ```javascript delegate_task(category="visual-engineering", load_skills=["frontend-ui-ux"], prompt="Create a dashboard component") delegate_task(category="ultrabrain", load_skills=[], prompt="Design the payment processing flow") delegate_task(category="quick", load_skills=["git-master"], prompt="Fix the typo in README.md") delegate_task(category="deep", load_skills=[], prompt="Investigate and fix the memory leak in the worker pool") ``` ### Critical: Model Resolution Priority Categories do NOT use their built-in defaults unless configured. Resolution order: 1. **User-configured model** (in `oh-my-opencode.json`) — highest priority 2. **Category's built-in default** (if category is in config) 3. **System default model** (from `opencode.json`) — fallback To use optimal models, add categories to your config. See [references/configuration.md](references/configuration.md). --- ## Built-in Skills | Skill | Purpose | Usage | |-------|---------|-------| | `playwright` | Browser automation via Playwright MCP (default browser engine) |
Related in AI Agents
skill-development
IncludedComprehensive meta-skill for creating, managing, validating, auditing, and distributing Claude Code skills and slash commands (unified in v2.1.3+). Provides skill templates, creation workflows, validation patterns, audit checklists, naming conventions, YAML frontmatter guidance, progressive disclosure examples, and best practices lookup. Use when creating new skills, validating existing skills, auditing skill quality, understanding skill architecture, needing skill templates, learning about YAML frontmatter requirements, progressive disclosure patterns, tool restrictions (allowed-tools), skill composition, skill naming conventions, troubleshooting skill activation issues, creating custom slash commands, configuring command frontmatter, using command arguments ($ARGUMENTS, $1, $2), bash execution in commands, file references in commands, command namespacing, plugin commands, MCP slash commands, Skill tool configuration, or deciding between skills vs slash commands. Delegates to docs-management skill for official documentation.
reprompter
IncludedTransform messy prompts into well-structured, effective prompts — single or multi-agent. Use when: "reprompt", "reprompt this", "clean up this prompt", "structure my prompt", rough text needing XML tags and best practices, "reprompter teams", "repromptception", "run with quality", "smart run", "smart agents", multi-agent tasks, audits, parallel work, anything going to agent teams. Don't use when: simple Q&A, pure chat, immediate execution-only tasks. See "Don't Use When" section for details. Outputs: Structured XML/Markdown prompt, quality score (before/after), optional team brief + per-agent sub-prompts, agent team output files. Success criteria: Single mode quality score ≥ 7/10; Repromptception per-agent prompt quality score 8+/10; all required sections present, actionable and specific.
adaptive-compaction
IncludedAdaptive add-on policy and recovery layer that decides WHEN to compact, prune, snapshot, or fork -- replacing fixed-percent auto-compaction across Claude Code, Codex, and MCP-capable hosts. Trigger on auto-compact timing or damage: "when should I compact", "is it safe to compact now or start a fresh session", "auto-compact fires too early/mid-task", "switching to an unrelated task but the window still has space", "context rot", "answers get worse the longer the session runs", "the agent forgot the plan or my decisions after it summarized", "add a layer on top that manages context without changing the agent", raising autoCompactWindow to give the policy room, or installing/tuning a cross-tool compaction policy or PreCompact hook -- even when "compaction" is never said but the problem is context-window pressure or post-summarization memory loss. Do NOT use to summarize a conversation, build RAG, write a summarization prompt (decides WHEN not HOW), or answer max-context-length trivia.
agent-skill-creator
IncludedCreate cross-platform agent skills from workflow descriptions. Activates when users ask to create an agent, automate a repetitive workflow, create a custom skill, or need advanced agent creation. Triggers on phrases like create agent for, automate workflow, create skill for, every day I have to, daily I need to, turn process into agent, need to automate, create a cross-platform skill, validate this skill, export this skill, migrate this skill. Supports single skills, multi-agent suites, transcript processing, template-based creation, interactive configuration, cross-platform export, and spec validation.
llm-wiki
IncludedUse when building or maintaining a persistent personal knowledge base (second brain) in Obsidian where an LLM incrementally ingests sources, updates entity/concept pages, maintains cross-references, and keeps a synthesis current. Triggers include "second brain", "Obsidian wiki", "personal knowledge management", "ingest this paper/article/book", "build a research wiki", "compound knowledge", "Memex", or whenever the user wants knowledge to accumulate across sessions instead of being re-derived by RAG on every query.
skill-master
IncludedAgent Skills authoring, evaluation, and optimization. Create, edit, validate, benchmark, and improve skills following the agentskills.io specification. Use when designing SKILL.md files, structuring skill folders (references, scripts, assets), ingesting external documentation into skills, running trigger evals, benchmarking skill quality, optimizing descriptions, or performing blind A/B comparisons. Keywords: agentskills.io, SKILL.md, skill authoring, eval, benchmark, trigger optimization.