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Omp Delegate

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amElnagdy
omp-delegate

Delegate a coding task to Oh My Pi (`omp`) as a background implementer, then review its diff and land it yourself. Use this whenever the user wants to delegate implementation work to Oh My Pi / omp - phrasings like "have omp implement X", "delegate this to oh my pi", "run it through omp", "use oh-my-pi to implement/fix/refactor" - or wants to run a queue of coding tasks through omp while staying the reviewer. DO NOT USE for tasks small enough to do inline, when the user wants the code written directly without delegating, or when they mean the original Pi CLI (`pi`) — that is pi-delegate.

Overview

PublisheramElnagdy
Repositorydelegate-skills
Skill nameomp-delegate
Stars
2.1K
Forks
167
Bundled files
5
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.

  • 5 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

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

Installation

Install the Omp Delegate 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.
  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/amElnagdy/delegate-skills.git /tmp/delegate-skills
mkdir -p .claude/skills
cp -r /tmp/delegate-skills/skills/omp-delegate .claude/skills/omp-delegate
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Omp Delegate 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 Omp Delegate 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 Omp Delegate 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.

Oh My Pi Delegate

You are the orchestrator. Delegate a bounded coding task to a separate implementer - Oh My Pi (omp) - then review what it produced and land it yourself. You write the brief and own the judgment; the implementer makes changes in its own session; you verify and commit.

The loop needs only a shell command and file access, so any comparable orchestrator can drive it.

The binary is omp, not pi

Oh My Pi is a fork of Pi. This skill drives omp (@oh-my-pi/pi-coding-agent). The original Pi CLI is a different binary (pi) with a different skill (pi-delegate). If omp is missing but pi is installed, you have Pi, not Oh My Pi.

When NOT to use this

  • The task is small enough to do inline; delegation overhead is not worth it.
  • The omp CLI is not installed or authenticated.
  • The user asked for the original Pi CLI (pi) — use pi-delegate.
  • You need a sandboxed implementer. Oh My Pi has no sandbox. --read-only restricts the tool surface; a write-capable run executes without prompts (--yolo).

Prerequisites (check once)

  1. Install omp with bun install -g @oh-my-pi/pi-coding-agent (or the install path from https://omp.sh).
  2. Authenticate: /login inside omp for a subscription provider, or an API-key environment variable for an API-key provider. Credentials live under ~/.omp/.
  3. Confirm omp --version succeeds.
  4. Work in, or point --cd at, the target git repository.

Choose the model (optional)

Omit --model (and --provider) to use omp's configured default for this project / profile. The catalog is this install's authenticated providers — not a fixed list in this skill.

To pick another model:

  1. List what this install can actually run. Do not pass omp --list-models — that flag is gone and omp treats it as an unknown flag (exit 2). Use the models subcommand:
    • omp models — every available model, grouped by provider
    • omp models --json — the same catalog, machine-readable
    • omp models find <substring> — filter by provider, id, or name (example: omp models find sonnet)
    • omp models <provider> — one provider's models
  2. Pass that id to the relay. --model <pattern> is omp's own --model: a fuzzy match against the catalog (provider/id, a bare id, or a unique substring). --provider <name> pins the provider when the pattern is ambiguous.
  3. The relay forwards only letters, digits, and . _ : / -. Glob patterns with * are rejected.

--thinking <level> is a separate reasoning dial, not a model id. Allowed values: off, auto, minimal, low, medium, high, xhigh, max. The relay rejects anything else (including inherit) before dispatch — omp would otherwise warn and ignore a bad value.

A fleet lane (--lane) can set provider, model, and effort. Lane effort becomes --thinking; an explicit --thinking / --model / --provider flag wins over the lane.

The relay does not forward --api-key, --smol, --slow, or --plan. Those stay omp's own CLI.

The loop

Run these five steps per task. Steps 1, 4, and 5 require judgment; 2 and 3 are mechanical.

1. Write the brief

Oh My Pi sees only the text you send plus what it can inspect in the workspace - no chat history or shared context. Include the goal, current state, what to change, what to leave untouched, the project's actual gates, and a report contract. Tell omp not to commit. Keep one task per brief. omp auto-loads AGENTS.md/CLAUDE.md context files from the workspace and its parents, so repo instructions reach it without inlining. See references/writing-the-brief.md.

2. Dispatch

Use the bundled relay. It pipes the brief to omp --mode json on stdin, captures the JSON event stream, and writes result.json. (<skill-dir> is the installed folder containing this SKILL.md.)

bash
node "<skill-dir>/scripts/relay.mjs" --brief brief.txt --cd /path/to/repo
# list models first:                       omp models   (or: omp models --json)
# choose a model:                          add --model <id from omp models>
# choose a provider:                       add --provider <name>
# set thinking level:                      add --thinking high
# read-only run (review/diagnosis):        add --read-only
# trust project .omp resources:            add --approve
# resume the most recent session:          add --resume-last  (delta brief only)
# resume a specific session:               add --session <id> (delta brief only)
# hard time limit (watchdog):              add --timeout 2h  (the 30m default suits short runs; implementation briefs routinely need 1-2h)
# see all options:                         node .../relay.mjs --help

The child process's cwd pins the workspace. The relay writes artifacts under the system temp dir by default and never commits. See references/dispatch-and-poll.md.

3. Wait for completion

The relay blocks until omp finishes. Run it with the orchestrator's background-command facility, or background it in the shell and poll for result.json. A pre-run usage error exits 2 and writes no result; a missing omp exits 127 and writes status: "omp_unavailable".

Trust process state and the working tree over a progress display. Completion means the process exited and result.json exists. omp's full report is the finalMessage field in result.json (also printed in full on stdout between the report markers).

4. Review - do not trust the self-report

Treat omp's final message and gate claims as claims:

  • Re-run the project's gates yourself.
  • Read the diff against the brief, starting with touchedFiles.
  • Run relevant guard skills if installed.
  • Round-trip migrations and grep for dangling references after removals or renames.

See references/review-and-land.md.

5. Land it

The implementer edits the working tree; the orchestrator commits. Commit only after the gates pass and the diff holds. If rework is needed, send a delta brief with --resume-last or --session <id>, then review again.

Autonomy and permissions

Oh My Pi has no sandbox. Print mode has no approval UI, so a write-capable relay run always passes --yolo (tools.approvalMode: yolo) — otherwise a user's always-ask or write config would stall until the watchdog. The other controls are:

  1. --read-only restricts omp's callable tools to --tools read,grep,glob. It does not pass --yolo. Installed extension code still runs with the user's host permissions if project resources are trusted.
  2. The relay passes --no-extensions --no-skills --no-rules by default, so project .omp extensions, skills, and rules stay undiscovered. --approve is the explicit opt-in for a repository the user trusts.
  3. touchedFiles and the diff are the record of what changed. Inspect them after every run.

Authorization model

Delegation is something the human opts into. Once they have ("run this queue", "proceed"), committing verified, gate-passing work is the agreed contract. Two limits remain: surface, don't absorb (report omp's design decisions, defensible-but-unasked turns, and non-blocking nitpicks) and stop for scope changes (if correct completion needs going beyond the brief, ask instead of expanding the mandate). See references/review-and-land.md.

References

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Omp Delegate AI skill do?

Delegate a coding task to Oh My Pi (`omp`) as a background implementer, then review its diff and land it yourself. Use this whenever the user wants to delegate implementation work to Oh My Pi / omp - phrasings like "have omp implement X", "delegate this to oh my pi", "run it through omp", "use oh-my-pi to implement/fix/refactor" - or wants to run a queue of coding tasks through omp while staying the reviewer. DO NOT USE for tasks small enough to do inline, when the user wants the code written directly without delegating, or when they mean the original Pi CLI (`pi`) — that is pi-delegate.

Why use Omp Delegate on TypingMind?

Because you install it once and use it with any model. Omp Delegate 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 Omp Delegate in TypingMind?

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

Which AI models can use Omp Delegate?

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 Omp Delegate?

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

Is the Omp Delegate AI skill free?

Yes. It is published on GitHub by amElnagdy 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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