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Orchestrate Omp

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dsebban
orchestrate-omp

Coordinate OMP subagents on substantial work. Use when parallel discovery, specialist review, or clearly partitioned implementation will shorten or strengthen the result; skip trivial tasks.

Overview

Publisherdsebban
Repositoryskills
Skill nameorchestrate-omp
Stars
72
Forks
6
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by dsebban on GitHub. Read the source before you install it.

Installation

Install the Orchestrate Omp AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/dsebban/skills/tree/main/skills/orchestrate-omp
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/dsebban/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/orchestrate-omp .claude/skills/orchestrate-omp
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Orchestrate Omp in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Orchestrate Omp on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Orchestrate Omp is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Orchestrate on OMP

Stay available to the user while substantive work runs behind the scenes. The root coordinator owns the plan, user interaction, approvals, scope, integration, and final verification.

1. Frame

  1. State the done predicate and the final artifact or decision.
  2. Split only independent discovery, specialist review, or implementation with clear ownership. Keep tightly coupled work in one session.
  3. Assign distinct primary ownership and name shared contracts before dispatch. Do not duplicate investigations or serialize a useful batch merely to avoid possible file overlap.
  4. Keep external side effects and approval decisions with the root.

2. Choose agents

Use the exact names exposed by the live task tool; its inventory is authoritative. For the current OMP roster:

WorkAgentEffort when exposed
Narrow read-only codebase discoveryscoutlo
Routine scoped implementationOmit agent for the default workermed
Difficult or ambiguous implementationOmit agent for the default workerhi
Mechanical edits or data collectionsoniclo
UI/UX implementation or reviewOmit agent for the default worker; the brief carries the design specializationmed or hi
Code-quality verdictreviewermed or hi
Security verdictsecurity-reviewerhi
External library or API researchlibrarianlo or med

When the live task schema exposes effort, match it to the assignment: lo for narrow questions, med for routine work, and hi when ambiguity or consequence justifies it. Otherwise rely on the selected agent's configured model role and do not pass an unavailable field. /skill:setup-pstack configures those roles.

Honor read-only and blocking markers in the live inventory. Never pass the default worker's name explicitly.

3. Dispatch

  1. When the live schema exposes tasks[], put independent participants in one batch so they start together and structure shared context as Goal, Constraints, and Contract. Otherwise start one participant per task call without passing context.
  2. Give every item a stable CamelCase name of at most 32 characters, the most specific specialist agent when one fits, a complete standalone task, and a solutionSpace that states how open-ended the problem is rather than how much work it carries. Omit agent only for the default worker. Add effort only when the live schema exposes it.
  3. Structure each assignment as Target, Change, and Acceptance. Include essential repository state, decisions, restrictions, and dependencies because children start without conversation history.
  4. Give every writer an exact writable scope. When the live schema exposes isolated, use isolated: true for concurrent writers that need separate workspaces, then inspect the returned metadata to learn whether changes were applied or retained as artifacts.
  5. Tell ordinary workers: Complete this assignment directly. Do not call task or spawn subagents. Allow nested delegation only when the assignment explicitly makes that worker a coordinator, and remember that task.maxRecursionDepth is 2 by default, so a coordinator's children are the last layer.
  6. Tell workers to skip project-wide formatting, linting, and test suites. The root runs shared validation once after integration.

Large context belongs in a local file referenced with local://<path>, not duplicated across assignments.

Use outputSchema only when the coordinator needs a machine-readable result and the live schema exposes it. Set schemaMode: "strict" when invalid output must fail rather than return with a warning.

4. Coordinate

  • Results auto-deliver. Continue handling user messages and independent root work instead of polling. wait is for the case where the root is genuinely blocked.
  • read proc:// lists live jobs and read proc://<id> inspects one without consuming its delivery.
  • write agent://<id> sends a bounded correction, an answer, or the next coupled phase, and revives a parked session. agent://all broadcasts. Name expected dependencies in shared context so sibling messages are purposeful rather than discovery by negotiation.
  • write proc://<id>/kill cancels stale or superseded work.
  • Read complete results from agent://<id> and use history://<id> when a report is incomplete or suspicious.
  • A completed job means the child yielded successfully. It does not mean its artifact is accepted.

5. Handoffs

A worker's final message is the handoff, and it is the only thing that moves information up the tree. Require the same shape from every worker: status (PASS, ISSUES, BLOCKED), branch or artifact paths, what it did, notes and deviations, suggested follow-ups.

  • Keep the worker's words. Read agent://<id> for the full text rather than paraphrasing a truncated preview into the plan.
  • BLOCKED is one task's dead end, not the tree's. Retry, repair, or clarify with a follow-up message and keep the rest moving.
  • Stop the whole tree only when continuing would waste effort across every branch: a broken base, a wrong contract, a failing shared dependency.
  • A child that dies without a report is a gap, not a success. Record it explicitly and decide whether to respawn.
  • Treat the notes section as the richest part. Each deviation or concern is a candidate task, and complaints about unclear scope are evidence that the brief was too thin.

6. Integrate

  1. Drain every required participant or record the cancellation or gap.
  2. Inspect each claimed artifact and reconcile conflicts against the declared ownership and contracts.
  3. Run the affected validation and real user path from the root at the integrated head.
  4. Return one concise result with agent identifiers, accepted findings or changes, verification evidence, and unresolved gaps.

Claim model or backend diversity only when returned metadata proves it.

Frequently asked questions

What does the Orchestrate Omp AI skill do?

Coordinate OMP subagents on substantial work. Use when parallel discovery, specialist review, or clearly partitioned implementation will shorten or strengthen the result; skip trivial tasks.

Why use Orchestrate Omp on TypingMind?

Because you install it once and use it with any model. Orchestrate Omp is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Orchestrate Omp in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/dsebban/skills/tree/main/skills/orchestrate-omp. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Orchestrate Omp?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Orchestrate Omp?

As many as you like. As long as a model supports skills, you can use Orchestrate Omp with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Orchestrate Omp AI skill free?

Yes. It is published on GitHub by dsebban under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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