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Omh Codebase Uml

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rlaope
omh-codebase-uml

[omh] OMH Codebase UML workflow: turn a repository into one readable, interface-level PlantUML architecture picture - packages or modules, the public symbols other units actually import, bounded import edges - and get it rendered to a single PNG a chat surface can show. Use when the user says: codebase-uml, codebase uml, uml, plantuml, uml diagram, class diagram, package diagram, module diagram.

Overview

Publisherrlaope
Repositoryoh-my-hermes
Skill nameomh-codebase-uml
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 Codebase Uml 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-codebase-uml .claude/skills/omh-codebase-uml
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Omh Codebase Uml 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 Codebase Uml 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 Codebase Uml 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.

Codebase Uml

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

Why This Exists

codebase-uml exists so 'visualize our codebase' produces one deterministic, readable picture instead of a hand-drawn guess: the interface each unit exposes is ranked by who imports it, the layout is bounded before PlantUML sees it, and every omission the bounding made is printed on the image.

Do Not Use When

  • The user wants the local code index refreshed or a task-scoped handoff pack, not a picture; use codegraph-refresh.
  • The user wants a narrative first-read tour, reading path, or glossary; use codebase-onboarding.
  • The user wants a summary card, thumbnail, or explainer image of a PR, meeting, or release rather than a structural diagram; use img-summary.

Examples

Good example:

  • Prompt: Visualize our codebase and drop the picture here so the new teammate can see how the routing package fits.
  • Expected behavior: Run omh codegraph uml --focus src/routing --output .omh/uml/routing.puml, render with the plan's command, attach the PNG, and read back the legend (units shown, folded, edges pruned).
  • Why: The request is a structural picture of one area for a chat surface, which is exactly the bounded diagram this workflow produces.

Bad example:

  • Prompt: Just sketch what you think the architecture looks like from the README.
  • Expected behavior: Decline to draw from memory; generate the diagram from the tree with omh codegraph uml or say the renderer is missing and name the install step.
  • Why: A diagram not derived from the actual tree misleads more than no diagram.

Completion Checklist

  • The view (package, focus, or module) matches the question asked, and only one view was rendered unless more were requested.
  • The render command and its observed result are recorded before the image is claimed.
  • The legend's omissions were read back to the user in the reply.
  • Follow-up exploration used narrower generated views, not recollection of the first picture.

Recovery Notes

  • If the render plan is blocked, send the PlantUML source path plus the install hint; do not attach a stale or hand-drawn image.
  • If the picture is still unreadable, lower --max-nodes, narrow --focus, or raise --depth by one, and say which knob changed.
  • If Graphviz dot is missing, rerun with --layout smetana; the layout differs but the content is identical.

Use When

Use when the user wants to see the shape of a codebase as one picture - a package, module, or focused-area diagram they can drop into Slack, Discord, a PR, or a doc - rather than a prose tour or a refreshed code index.

Strong routing signals: `codebase-uml`, `codebase uml`, `uml`, `plantuml`, `uml diagram`, `class diagram`, `package diagram`, `module diagram`, `architecture diagram`, `dependency diagram`, `module dependency diagram`, `visualize the codebase`, `visualize this codebase`, `visualize the code`, `visualize the architecture`, `codebase visualization`, `code visualization`, `diagram of the codebase`, `diagram the codebase`, `draw the architecture`, `draw the codebase`, `architecture picture`, `codebase picture`, `picture of the codebase`, `코드베이스 시각화`, `코드베이스 시각화해줘`, `코드베이스를 시각화`, `아키텍처 다이어그램`, `UML 다이어그램`, `패키지 다이어그램`, `클래스 다이어그램`, `코드베이스 다이어그램`, `코드 구조 그림`, `코드베이스 그림으로`, `코드 구조도`

Catalog Metadata

Category: planning Phase: codebase-uml Quality tier: codegraph-gated Reasoning demand: standard

Quality bar:

  • Scope first: whole-repo package view for 'show me the codebase', --focus <path> for one area, --level module for a subsystem; never render more than one view per request unless asked.
  • Generate with omh codegraph uml --repo <root> --output <dir>/codebase.puml and read the printed render plan; when it is blocked, report the exact blocker and install hint instead of improvising a renderer.
  • Render with the plan's command verbatim (-DPLANTUML_LIMIT_SIZE=8192 stays on) and attach the PNG; use --layout smetana when Graphviz dot is absent and --format svg only when the user asked for SVG.
  • Read the legend back to the user in one line: units shown, units folded, edges pruned, symbols hidden - so nobody mistakes 16 boxes for the whole system.
  • Answer follow-up exploration by re-running with a narrower --focus or --level module rather than describing what the first picture omitted from memory.
  • Keep the omh theme unless the user asks for --theme mono; the theme exists so every OMH diagram reads as one family.

Required inputs:

  • repo root or current workspace
  • view: whole repo at package level, one area by --focus <path>, or module level for a subsystem
  • delivery target (chat attachment, PR, doc) which fixes the format: PNG for chat, SVG only when asked
  • renderer readiness from the command's render plan (plantuml on PATH, or PLANTUML_JAR plus java)

Expected outputs:

  • codebase_uml/v1 model (units, interfaces, edges, omissions) via omh codegraph uml --json
  • PlantUML source written by omh codegraph uml --output <file>.puml
  • uml_render_plan/v1 naming the exact render command or the blocker
  • one rendered PNG (or SVG on request) attached to the reply, with the omissions legend visible
  • not-evidence boundary

Artifact expectations:

  • codebase_uml/v1 with view (level, depth, focus, caps), nodes carrying fan-in-ranked public interfaces, weighted edges, layout hardening, and omissions counts
  • uml_render_plan/v1 with status, renderer, layout_engine, command, blockers, and notes
  • the rendered image path only after the render command is observed to exit 0 and the file exists

Safety rules:

  • Do not hand-draw the diagram from memory or from a partial read; the boxes and arrows come from omh codegraph uml over the actual tree.
  • Do not claim the image was rendered or attached without the observed render command result and file.
  • Do not present the picture as complete architecture: the legend's folded units, pruned edges, and hidden symbols are part of the answer.
  • Never send the diagram to a chat surface or repository the user did not name; the render is local and the attachment is the wrapper's observed action.
  • The render surface is the local Java CLI or PLANTUML_JAR invocation only; browser/TeaVM PlantUML render options are not part of this workflow.

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 Codebase Uml AI skill do?

[omh] OMH Codebase UML workflow: turn a repository into one readable, interface-level PlantUML architecture picture - packages or modules, the public symbols other units actually import, bounded import edges - and get it rendered to a single PNG a chat surface can show. Use when the user says: codebase-uml, codebase uml, uml, plantuml, uml diagram, class diagram, package diagram, module diagram.

Why use Omh Codebase Uml on TypingMind?

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

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

Which AI models can use Omh Codebase Uml?

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 Codebase Uml?

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

Is the Omh Codebase Uml 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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