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Clawd Photo Compositor

Community
xixicc186
clawd-photo-compositor

Add the canonical Clawd character to a user-provided photograph by selecting one bundled pose reference and compositing it with the photo through built-in image generation. Use this skill whenever the user asks to put, add, place, hide, hang, sit, stand, sleep, lean, climb, hug, push, pull, or otherwise make Clawd interact with an object in a photo, including requests phrased in Chinese such as “把 Clawd 放进图里”, “让它探头”, “挂在屏幕上”, or “抱住电线”.

Overview

Publisherxixicc186
Repositoryclawd-emotes-skill
Skill nameclawd-photo-compositor
Stars
79
Forks
9
Bundled files
20
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.

  • 20 bundled files

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

  • Open source

    Published by xixicc186 on GitHub. Read the source before you install it.

Installation

Install the Clawd Photo Compositor 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/xixicc186/clawd-emotes-skill/tree/main/clawd-photo-compositor
  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/xixicc186/clawd-emotes-skill.git /tmp/clawd-emotes-skill
mkdir -p .claude/skills
cp -r /tmp/clawd-emotes-skill/clawd-photo-compositor .claude/skills/clawd-photo-compositor
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Clawd Photo Compositor 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 Clawd Photo Compositor 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 Clawd Photo Compositor 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.

Clawd Photo Compositor

Use the bundled pose image as the source of truth for Clawd. Let the prompt describe placement and interaction, not redesign the character.

Workflow

  1. Inspect the user's photograph with view_image before editing it.
  2. Read references/pose-index.yaml and select exactly one pose:
    • Prefer the action explicitly requested by the user.
    • Otherwise match the clearest object, edge, surface, cable, or obstacle in the photograph.
    • Ask only when no reasonable target or interaction can be inferred.
  3. Resolve the selected file relative to this skill directory and inspect that pose image with view_image.
  4. Treat the inputs consistently:
    • Image 1: the user's photograph and edit target.
    • Image 2: the selected Clawd character-and-pose reference.
  5. Call built-in image generation with both images as references. Pass one Clawd pose only; multiple pose references can cause mixed limbs or duplicate characters.
  6. Build a short prompt from the template below. Always include both prompt_constants.identity_lock and prompt_constants.proxy_exclusion from the pose index. Include the pose entry's relation_hint only when the action depends on occlusion or contact.
  7. Check the result before accepting it:
    • Clawd remains a flat 2D block graphic even though the surrounding photograph is realistic.
    • Its body silhouette, body aspect ratio, two block hands, four short rectangular legs, and relative part sizes still match Image 2.
    • No gray proxy platform, wall, cylinder, line, box, or reference shadow from Image 2 was copied into the photograph. If one check fails, retry once by strengthening only the failed identity or proxy sentence.
  8. Return the generated image. Do not add a second character, substitute another pose, or generate a standalone Clawd asset unless the user requested that instead.

Prompt template

Prefer two short sentences:

text
以图1为原图,把图2里的Clawd按图2动作放在图一的{target/location},让它{interaction};保持图一其他内容不变。{relation_hint}
{identity_lock}
{proxy_exclusion}

Translate the same structure when the user writes in another language. Keep the prompt focused on target, action, and necessary contact or occlusion. Do not expand it into a long character specification unless a previous result failed for one specific reason.

Selection rules

  • Use A-series references for ordinary standing views without a physical interaction.
  • Use B-series references for contact poses.
  • Keep the photograph photorealistic while keeping Clawd visibly flat and graphic. Do not harmonize Clawd into the photo's realistic material or lighting style.
  • Allow only uniform whole-character scaling and rotation. Do not independently stretch, compress, widen, narrow, or round the body or limbs.
  • Map the gray proxy geometry in a pose reference onto the real object in the photograph. The proxy conveys only pose, contact, and occlusion; it is never an asset to copy into the result.
  • Preserve the user's requested target and action even if another scene object could also work.
  • For ambiguous placement, choose an area with enough visual space and contrast while keeping the photograph's main subject readable.
  • Do not use multi-expression sheets or negative/error examples as image-generation references.

Prompt discipline

  • Keep the user's wording when it already specifies the object and action.
  • Keep the identity-lock sentence even when shortening the rest of the prompt; the reference pose alone does not reliably prevent photorealistic restyling or proportion drift.
  • Keep the proxy-exclusion sentence even when shortening the rest of the prompt; this is the one negative constraint that every pose-reference composition needs.
  • Mention layer order only when it communicates the interaction, such as “body behind the cable, hands in front”.
  • Add a scale instruction only when the likely default would be obviously wrong.
  • Avoid inventories of colors, facial features, limbs, camera details, and negative constraints: Image 2 already carries those details.
  • If a retry is needed, change only the failed relationship, scale, placement, identity lock, or proxy exclusion rather than rewriting the whole prompt.

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 Clawd Photo Compositor AI skill do?

Add the canonical Clawd character to a user-provided photograph by selecting one bundled pose reference and compositing it with the photo through built-in image generation. Use this skill whenever the user asks to put, add, place, hide, hang, sit, stand, sleep, lean, climb, hug, push, pull, or otherwise make Clawd interact with an object in a photo, including requests phrased in Chinese such as “把 Clawd 放进图里”, “让它探头”, “挂在屏幕上”, or “抱住电线”.

Why use Clawd Photo Compositor on TypingMind?

Because you install it once and use it with any model. Clawd Photo Compositor 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 Clawd Photo Compositor in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/xixicc186/clawd-emotes-skill/tree/main/clawd-photo-compositor. 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 Clawd Photo Compositor?

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 Clawd Photo Compositor?

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

Is the Clawd Photo Compositor AI skill free?

Yes. It is published on GitHub by xixicc186 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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