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Omh Running Work Board

CommunityPopular
rlaope
omh-running-work-board

[omh] Live view of running coding units: showing which coding units are running right now, on which runtime and model, with observed tokens and elapsed time. Use when the user says: running-work-board, running work board, which units are running, what models are running, 지금 뭐 돌고 있어, 뭐가 돌고 있어, 어떤 모델로 돌고 있어, 실행 중인 작업 보여줘.

Overview

Publisherrlaope
Repositoryoh-my-hermes
Skill nameomh-running-work-board
Stars
3.6K
Forks
269
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 rlaope on GitHub. Read the source before you install it.

Installation

Install the Omh Running Work Board 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/rlaope/oh-my-hermes/tree/main/agent-skills/omh-running-work-board
  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/rlaope/oh-my-hermes.git /tmp/oh-my-hermes
mkdir -p .claude/skills
cp -r /tmp/oh-my-hermes/agent-skills/omh-running-work-board .claude/skills/omh-running-work-board
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Omh Running Work Board 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 Omh Running Work Board 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 Omh Running Work Board 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.

Running Work Board

This is an OMH running-work-board workflow skill, projected for Agent Skills hosts (Claude Code, Codex, Cursor, opencode, OpenClaw, pi).

Why This Exists

running-work-board exists because multi-session coding work was invisible: the runtime was tracked but the model was dropped, token counts had no write site at all, and a blocking dispatch could not report that it was still running. The board answers which model on which runtime, or says unknown.

Do Not Use When

  • The user wants to start, plan, or dispatch coding work rather than observe it.
  • The user wants review, CI, or merge evidence, which a status board never provides.
  • The user is asking about their own application's runtime status rather than OMH coding units.

Examples

Good example:

  • Prompt: what is running right now
  • Expected behavior: One line per unit: label, runtime, model, status, elapsed, tokens, with unknown printed where nothing was observed.
  • Why: The request is about observed local coding activity, not about starting work.

Bad example:

  • Prompt: is the deploy done and did CI pass
  • Expected behavior: Route to verification or CI evidence instead of the activity board.
  • Why: Observed activity is not result, review, CI, or merge evidence.

Completion Checklist

  • Runtime and model are named per unit, or explicitly reported as unknown.
  • Token counts and session references are observed values or the literal unknown, never estimates.
  • Elapsed time for an unfinished unit comes from its start marker, which cannot prove the unit is still alive.
  • The board is labelled observed activity, not result, verification, review, CI, or merge evidence.
  • On Hermes, delegate_task children and kanban workers of this conversation come from omh_hud (its subagents rows and kanban block, read from Hermes' own records) beside the OMH units, each labelled by source; /agents is the person's own Hermes list of running agents and tasks in Hermes' own terminal; the OMH TUI refuses /agents, and its agent list (Down on an empty composer while subagents show) shows the subagents of the running turn.

Recovery Notes

  • If no units are found, say so plainly rather than implying nothing ever ran.
  • If omh_hud is not available, say delegate children and kanban workers were not read rather than implying none are running.
  • If a marker is stale because a process died, report it as observed-start-without-end instead of claiming the unit is running.
  • If tokens are unknown for a runtime with no structured output, say the runtime does not report them.

When to Use

Use when the user asks what coding work is running right now -- which unit, which runtime, which model, how long, how many tokens -- rather than asking to start, plan, or review work.

Strong routing signals: `running-work-board`, `running work board`, `which units are running`, `what models are running`, `지금 뭐 돌고 있어`, `뭐가 돌고 있어`, `어떤 모델로 돌고 있어`, `실행 중인 작업 보여줘`

Catalog Metadata

Category: operator Phase: observability Quality tier: evidence-gated Reasoning demand: light

Quality bar:

  • Name the workflow target, constraints, validation evidence, and stop condition.
  • Separate Hermes guidance from executor or wrapper behavior unless evidence proves the step happened.

Required inputs:

  • local coding artifacts
  • on Hermes, this conversation's omh_hud rows

Expected outputs:

  • per-unit runtime and model
  • observed tokens and elapsed
  • on Hermes, delegate children and kanban workers, labelled by source
  • explicit unknowns

Artifact expectations:

  • metadata-only status board projection from local artifacts

Safety rules:

  • Do not imply hidden Hermes runtime behavior.
  • Use the smallest verification that can prove the claim.

Runtime Evidence

Use the current host's own tools and subagent/task mechanism when available; otherwise run the same lanes sequentially or name the unavailable capability. A prepared plan, handoff, checklist, or skill installation is not execution, review, CI, merge-readiness, or merge evidence. Record actual tool results, or not_observed / not_available, in the record; never invent dispatch or host accounting. Treat supplied context as advisory, not proof of hidden memory reads or writes. State scope, constraints, verification, and the stop condition before work. Reply in the user's own words and the host's own voice: the host's persona owns reply language, tone, speech level, and sentence endings, progress updates included (where it sets no language, use the one the user wrote in), and OMH shapes structure and content only; OMH's record terms (surface, lane, wrapper, handoff, evidence boundary, not_observed) stay in records and tool calls, never in the sentence the user reads unless they ask about one; and when a real unresolved user decision or a useful briefing discussion remains, offer one specific, content-linked question. Completed work needs no question; omit unrelated non-action footers and generic offers to continue. Supporting paths are relative to this skill directory; sibling skill paths are relative to its parent. Resolve them from the host-provided skill base directory ({baseDir} on hosts that provide it), never a hardcoded install location. A named workflow not installed here is unavailable, not permission to emulate its host-specific capabilities. Verify through the real surface before done.

Frequently asked questions

What does the Omh Running Work Board AI skill do?

[omh] Live view of running coding units: showing which coding units are running right now, on which runtime and model, with observed tokens and elapsed time. Use when the user says: running-work-board, running work board, which units are running, what models are running, 지금 뭐 돌고 있어, 뭐가 돌고 있어, 어떤 모델로 돌고 있어, 실행 중인 작업 보여줘.

Why use Omh Running Work Board on TypingMind?

Because you install it once and use it with any model. Omh Running Work Board 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 Omh Running Work Board in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/rlaope/oh-my-hermes/tree/main/agent-skills/omh-running-work-board. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Omh Running Work Board?

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 Omh Running Work Board?

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

Is the Omh Running Work Board AI skill free?

Yes. It is published on GitHub by rlaope 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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