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Skill · AI Ml

Odw

Dynamic multi-agent workflows — plan first, then orchestrate parallel agents with adversarial verification via the local odw daemon. Use when the user asks for a "workflow", says "ultracode", or hands you a task spanning many files/items that benefits from parallel agents.

Agentic Awesome SkillsLicense: MITAdded Sep 5, 2026
Use it in my AI

How to use it

  1. Start your plan and connect your AI once
  2. Add the skill to your AI, one time only: press Copy skill and paste it into your AI's instructions: a project in ChatGPT, Claude or Grok, a Gem in Gemini, an agent in Microsoft 365 Copilot, or a rule in Cursor. It stays there for every new chat. In Kimi, paste it at the start of a new chat.
  3. Ask for the task in your own words, or say it directly:
Use the Odw skill to help me with this.
SKILL.md

Open Dynamic Workflows (Antigravity)

When to Use

Use this skill when you need dynamic multi-agent workflows — plan first, then orchestrate parallel agents with adversarial verification via the local odw daemon. Use when the user asks for a "workflow", says "ultracode", or hands you a task spanning many files/items that benefits from parallel agents.

Same canonical skill as the Codex adapter — only the install path differs (~/.gemini/skills/odw/). The bridge scripts live next to this skill in scripts/.

Model & API key (read this first)

Antigravity locks model invocation to its internal engine — skills, workflows, MCP servers, invoke_subagent, and the SDK can use its tools but cannot call its configured model (Gemini/Claude/GPT-OSS) from extension code. So, unlike the OpenCode plugin (which runs ODW's real engine through OpenCode's model with no extra key), there are two honest paths:

  • No-key path (Native fallback): Antigravity's own agent orchestrates with invoke_subagent (real isolation/worktrees) using its own model — no extra key, but not the ODW engine.
  • Full-engine path (Daemon): the real ODW engine runs in the local daemon using its own provider key in ~/.odw/config.json (Ollama is keyless/local). This is the only way to get the full engine on Antigravity today.

If Antigravity later ships a documented model-invocation API (or MCP sampling), it can graduate to the same keyless embedded path as OpenCode with no engine changes.

Step 0 — Daemon check

Run: node scripts/daemon-bridge.js --check

  • Exit 0 → daemon is up; use the daemon path below.
  • Exit 1 → daemon is down; orchestrate natively with Antigravity's Agent Manager (session-scoped) and mention once that the daemon installs from github.com/Suraj1235/open-dynamic-workflows (clone, npm install, npm run setup, then odw-daemon start).

Daemon path

  1. Plan: node scripts/daemon-bridge.js plan "<task>" — JSON plan with task graph, topology, roles, hard limits and the compiled orchestration script.
  2. Confirm: summarize topology / agent count / est. cost / est. time before executing anything beyond read-only work.
  3. Execute: node scripts/daemon-bridge.js exec plan.json → wf_... id. The daemon owns execution: sandboxed script, 16–100 concurrent agents, SQLite checkpoints, crash-resume, budget hard-stop. It keeps running even if this IDE session ends.
  4. Report: node scripts/daemon-bridge.js result <wf_id> blocks until done; relay the synthesized result.

Native fallback path

Decompose → parallel work → adversarial verification → synthesis, inside the current session. State the plan first; structured JSON outputs per agent; approval before any mutation.

Notes

  • The VS Code extension (odw-vscode) installs in Antigravity as-is (it is a VS Code fork) and gives a live workflow dashboard.
  • Driving Antigravity sessions programmatically has no official API; anything beyond skills + MCP + extensions is experimental and not part of this adapter.

Example

User request:

Use @odw for this task: Dynamic multi-agent workflows — plan first, then orchestrate parallel agents with adversarial verification via the local odw daemon.

Limitations

  • Use this skill only when the task clearly matches its upstream source and local project context.
  • Verify commands, generated code, dependencies, credentials, and external service behavior before applying changes.
  • Do not treat examples as a substitute for environment-specific tests, security review, or user approval for destructive or costly actions.