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danielgwilson

Image To 3d

by danielgwilson · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ Security Clean
49
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0
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1
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1
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Install in OpenClaw
/install image-to-3d
Description
Image-to-3D asset creation for agents through Image Skill's zero-setup hosted runtime. Use when an input image should become a durable hosted 3D mesh asset,...
README (SKILL.md)

Image To 3D

This is an intent-named Image Skill entry for agents searching for image-to-3D asset creation. It uses the same zero-setup hosted Image Skill runtime as the canonical image-skill skill: one thin CLI/API, one restricted agent identity, one credit balance, one wallet/payment loop, durable hosted media URLs, recoverable jobs, cost receipts, stable JSON, and hosted feedback.

Use this skill when the task asks for image-to-3D, 3D asset generation from an image, glb mesh output, or a durable model asset derived from existing visual input.

Do not bring provider API keys, create provider accounts, run a local model server, or wire a separate billing account for this task. Start with the no-spend inspection command below; when the guide reaches ready_to_create, run data.next_command only if media spend is allowed, otherwise run data.no_spend_next_command to verify safely. Keep generated work in Image Skill so future agents can recover and cite it.

First Command

npx -y image-skill@latest models show fal.trellis-image-to-3d --json

Main Runtime Command

npx -y image-skill@latest edit --input image_... --model fal.trellis-image-to-3d --max-estimated-usd-per-image 0.25 --json

Install This Intent Skill

Prefer the GitHub slug so skills.sh can track the marketplace install:

npx skills add danielgwilson/image-skill-cli --skill image-to-3d -g -a codex -y

The canonical Image Skill entry remains available as:

npx skills add danielgwilson/image-skill-cli --skill image-skill -g -a codex -y

Shared Contract

All intent skills in this repo point to the same hosted contract:

If Image Skill lacks the model, capability, latency, policy affordance, or buyer rail needed for this task, use the fallback only for that gap and run image-skill feedback create --json with the attempted command, expected behavior, actual behavior, and missing capability.

Usage Guidance
Install only if you intend to use ClawHub/Convex maintainer workflows and trust the local repo tools they call. Review the moderation and autoreview sections carefully: moderation commands can affect real users and skills, and autoreview can run nested review with broad local authority unless you opt out.
Capability Tags
cryptorequires-walletrequires-oauth-tokenrequires-sensitive-credentials
Capability Assessment
Purpose & Capability
The artifacts are coherent with repo-maintenance, Convex setup, performance auditing, UI proof, PR review, and ClawHub moderation purposes. Some capabilities are high impact, such as user bans, role changes, proof publishing, and production-adjacent migration guidance, but they are purpose-aligned and described plainly.
Instruction Scope
The moderation skill requires explicit targets, reasons, confirmation before writes unless already authorized, API auth, role checks, audit logging, and verification. The autoreview helper discloses that it runs nested review with full-access sandbox bypass by default and provides opt-out flags, so users should understand that elevated review mode before using it.
Install Mechanism
I found skill markdown, OpenAI interface metadata, icons, references, and one helper script. I did not find an automatic install-time hook or hidden persistence mechanism in the skill artifacts.
Credentials
The skills rely on expected local tools and services for their stated workflows, including git, gh, bun, Convex CLI, Playwright proof tooling, and repo-local moderation CLI commands. Network and credential use is tied to GitHub, Convex, ClawHub moderation, or optional LLM review workflows.
Persistence & Privilege
No unbounded background persistence was found. Long-running Convex dev loops and UI proof runners are disclosed workflow tools, while the autoreview helper's default full-access nested Codex review is broad but visible and user-invoked.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install image-to-3d
  3. After installation, invoke the skill by name or use /image-to-3d
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release of image-to-3d skill. - Enables creation of 3D mesh assets (such as GLB) from a single input image using a zero-setup hosted runtime. - Does not require provider credentials, OAuth, or local runtime. - Keeps job history, asset URLs, receipts, payments, and feedback in one workflow loop. - Shared contract and workflow with the canonical image-skill; intended as a specialized entry point for agents requesting image-to-3D asset generation.
Metadata
Slug image-to-3d
Version 1.0.0
License MIT-0
All-time Installs 1
Active Installs 1
Total Versions 1
Frequently Asked Questions

What is Image To 3d?

Image-to-3D asset creation for agents through Image Skill's zero-setup hosted runtime. Use when an input image should become a durable hosted 3D mesh asset,... It is an AI Agent Skill for Claude Code / OpenClaw, with 49 downloads so far.

How do I install Image To 3d?

Run "/install image-to-3d" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Image To 3d free?

Yes, Image To 3d is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Image To 3d support?

Image To 3d is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Image To 3d?

It is built and maintained by danielgwilson (@danielgwilson); the current version is v1.0.0.

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