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Omh Apps

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rlaope
omh-apps

[omh] External app actions - email, Slack, Discord, Notion, Linear, Jira, CRM, and similar providers, scoped with auth, payload, confirmation, and result-evidence gates. Use when the user says: connector-operator, connector operator, external app action, external connector action, saas action, api action, send email, email customer.

Overview

Publisherrlaope
Repositoryoh-my-hermes
Skill nameomh-apps
Stars
2.7K
Forks
194
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 Apps 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/rlaope/oh-my-hermes.git /tmp/oh-my-hermes
mkdir -p .claude/skills
cp -r /tmp/oh-my-hermes/agent-skills/omh-apps .claude/skills/omh-apps
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Omh Apps 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 Apps 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 Apps 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.

Connector Operator

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

Why This Exists

connector-operator exists so Hermes users can ask for this workflow in chat and receive a structured, evidence-bounded OMH operating surface instead of ad hoc narration.

Do Not Use When

  • The request is already handled by a narrower explicit skill with stronger evidence.
  • The user asks OMH to secretly run external platforms, connectors, schedulers, file exports, or runtime agents.
  • The only safe answer is to ask for missing authority, credentials, target, or observed evidence first.

Examples

Good example:

  • Prompt: connector-operator draft an email to the customer and prepare a confirmation gate before sending.
  • Expected behavior: Produce prepare_connector_operator_card with required context, wrapper actions, and not-evidence boundaries.
  • Why: The prompt names a real workflow surface that Hermes can orchestrate without hiding execution.

Bad example:

  • Prompt: connector-operator send the Jira update with hidden credentials and claim it was delivered.
  • Expected behavior: Report the missing observed evidence or authority instead of claiming the external step happened.
  • Why: Prepared OMH guidance is not platform, runtime, connector, file, memory, or delivery evidence.

Completion Checklist

  • Provider, target object, allowed action, payload summary, authority, confirmation policy, and stop condition are explicit.
  • Credentials, missing connector setup, external writes, sends, ticket mutations, calendar invites, CRM updates, and webhook delivery are gated or marked missing.
  • Message ids, ticket ids, provider responses, delivery receipts, and API effects are reported only from observed connector evidence.

Recovery Notes

  • If the connector, credentials, or permission is missing, route to toolbelt-readiness before preparing action success claims.
  • If the request is only chat thread delivery policy for Discord, Slack, or Telegram, route to gateway-intent-card instead.
  • If the external app action would create, send, invite, mutate, or delete provider state, require an explicit confirmation gate.

Use When

Use when Hermes should prepare or supervise a provider-backed external app action without claiming connector availability, credentials, API mutation, delivery, or success.

Strong routing signals: `connector-operator`, `connector operator`, `external app action`, `external connector action`, `saas action`, `api action`, `send email`, `email customer`, `gmail draft`, `gmail send`, `create linear ticket`, `create linear issue`, `linear ticket`, `linear issue`, `update linear`, `jira ticket`, `jira issue`, `create jira issue`, `open jira ticket`, `create jira`, `notion page`, `update notion`, `crm update`, `salesforce update`, `hubspot update`, `create calendar event`, `calendar invite`, `google calendar`, `send slack dm`, `slack dm`, `discord dm`, `post to discord`, `post to slack`, `discord post`, `slack post`, `connector action`, `linear ticket`, `이메일 보내`, `이메일 발송`, `메일 보내`, `gmail 초안`, `linear 티켓`, `linear 이슈`, `jira 티켓`, `jira 이슈`, `notion 페이지`, `노션 페이지`, `캘린더 초대`, `외부 앱`, `외부 커넥터`, `커넥터 액션`

Catalog Metadata

Category: connector Phase: connector-task Quality tier: workflow-surface-gated Reasoning demand: standard

Quality bar:

  • Name the user-facing workflow objective, required context, next action, and stop condition.
  • Separate prepared guidance from observed platform, runtime, connector, file, memory, or delivery evidence.
  • Expose missing tools, credentials, targets, or observations as user-visible gaps.

Required inputs:

  • user request
  • target context
  • delivery or status expectation
  • known missing evidence

Expected outputs:

  • connector_task_card/v1
  • connector_scope/v1
  • connector_auth_boundary/v1
  • connector_confirmation_gate/v1 when mutating or sending
  • connector_result_manifest/v1 when observed
  • next action
  • prepared-vs-observed boundary

Artifact expectations:

  • connector_task_card/v1 metadata-only wrapper card when prepared
  • connector_scope/v1 with provider, target object, allowed action, payload summary, and stop condition
  • connector_auth_boundary/v1 separating missing connector, missing credentials, user-supplied authority, and credential-use prohibition
  • connector_confirmation_gate/v1 for sending, ticket mutation, external write, webhook delivery, CRM/database update, or irreversible provider action
  • connector_result_manifest/v1 only when provider response, message id, ticket id, API transcript, or delivery receipt is observed

Safety rules:

  • A connector operator card is not connector availability, credential validation, API call, message send, ticket creation, ticket update, database/CRM mutation, external write, webhook delivery, or provider success evidence unless observed connector-result evidence records it.
  • Do not claim connector, gateway, runtime, file generation, memory mutation, or host automation evidence from prepared guidance.

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. Report actual tool results or not_observed / not_available; 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. 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 Apps AI skill do?

[omh] External app actions - email, Slack, Discord, Notion, Linear, Jira, CRM, and similar providers, scoped with auth, payload, confirmation, and result-evidence gates. Use when the user says: connector-operator, connector operator, external app action, external connector action, saas action, api action, send email, email customer.

Why use Omh Apps on TypingMind?

Because you install it once and use it with any model. Omh Apps 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 Apps in TypingMind?

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

Which AI models can use Omh Apps?

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 Apps?

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

Is the Omh Apps 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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