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Omh Report Package

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rlaope
omh-report-package

[omh] Periodic report for executives: weekly/monthly reports, executive briefs, PPT-ready outlines, and upload packages. Use when the user says: report-package, report package, weekly report, monthly report, executive report, exec brief, leadership deck, status package.

Overview

Publisherrlaope
Repositoryoh-my-hermes
Skill nameomh-report-package
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 Report Package 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-report-package
  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-report-package .claude/skills/omh-report-package
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Omh Report Package 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 Report Package 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 Report Package 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.

Report Package

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

Why This Exists

report-package exists to make reporting a first-class operations surface: Hermes can produce clean report and slide outlines while keeping approvals, delivery, and binary deck export as separate evidence.

Do Not Use When

  • The user needs SLO, incident, or error-budget review; use omh-reliability-review.
  • The user asks for a live .pptx deck file rather than a PPT-ready outline.
  • The request is meeting minutes, scrum history, or action-item tracking.

Examples

Good example:

  • Prompt: report-package 월간 리더십 보고서 PPT outline 만들어줘.
  • Expected behavior: Prepare a report package with sections, assumptions, missing inputs, and Markdown/JSON outline scope.
  • Why: The request is packaging known information for reporting, not reliability validation or code work.

Bad example:

  • Prompt: report-package prove our SLO passed and close the incident.
  • Expected behavior: Route to reliability-review and require metric or incident evidence.
  • Why: Report packaging cannot satisfy reliability closure evidence.

Completion Checklist

  • The reporting window, inputs, audience, narrative, and evidence gaps are named.
  • Draft report, generated package, approval, and delivery are separate states.
  • The next action says whether to gather evidence, generate, revise, approve, or deliver.

Recovery Notes

  • If input evidence is incomplete, mark the section as pending rather than fabricating a report claim.
  • If delivery or attachment is unavailable, keep the report package prepared_not_observed.

When to Use

Use when Hermes should turn supplied inputs into a report, executive brief, PPT-ready outline, or upload package without claiming presentation delivery.

Strong routing signals: `report-package`, `report package`, `weekly report`, `monthly report`, `executive report`, `exec brief`, `leadership deck`, `status package`, `ppt outline`, `presentation outline`, `slide outline`, `upload package`, `PPT`, `보고서 패키지`, `주간 보고서`, `월간 보고서`, `경영진 보고`, `리더십 보고`, `피피티`, `슬라이드`, `발표자료`, `업로드 패키지`

Catalog Metadata

Category: reporting Phase: package-outline Quality tier: report-gated Reasoning demand: standard

Quality bar:

  • Name audience, reporting period, sections, supplied facts, assumptions, and missing data.
  • Keep report packaging independent from reliability review unless explicitly requested.
  • Export only Markdown/JSON outlines unless a separate presentation tool produces a binary deck.
  • On Hermes, that tool can be the bundled powerpoint skill, and a deck it builds counts as generated from its read-back (pptx_read.py --outline).
  • On Hermes, a rung taken from a bundled document skill is observed only from that skill's result for that exact file, judged by its field, not its exit code: "rendered": false or "recalculated": false exits 0 yet leaves that rung not observed, blocked on the missing tools it names; other observed evidence for a rung still counts.
  • On Hermes, powerpoint gives slide_count (pptx_read.py --outline) and render_screenshot (pptx_render.py into a fresh directory, its image count matching slide_count, since it lists every image already in that directory). Images that exist are not a render pass until each one has been inspected.

Required inputs:

  • audience
  • reporting period or scope
  • supplied facts
  • missing data or assumptions

Expected outputs:

  • report package
  • PPT-ready Markdown or JSON outline
  • assumptions and missing-input list
  • Optional supplied achievements summary when requested; plugin-backed badge retrieval is unavailable in this projection.

Artifact expectations:

  • operation_artifact/v1 report-package artifact when a wrapper or CLI records it

Safety rules:

  • Do not claim source review completion from a prepared report package.
  • Do not claim stakeholder approval or presentation delivery without observed evidence.
  • Do not couple report packages to SLO, incident, or error-budget evidence by default.

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 Report Package AI skill do?

[omh] Periodic report for executives: weekly/monthly reports, executive briefs, PPT-ready outlines, and upload packages. Use when the user says: report-package, report package, weekly report, monthly report, executive report, exec brief, leadership deck, status package.

Why use Omh Report Package on TypingMind?

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

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

Which AI models can use Omh Report Package?

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 Report Package?

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

Is the Omh Report Package 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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