# Add to your Claude Code skills
git clone https://github.com/Razshy/WiggleWiggle is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by Razshy. Wiggle is a sandbox to run code in. It has 56 GitHub stars.
Wiggle's catalog security scan is still queued. You can run an instant dependency and prompt-injection check now with the "Scan for vulnerabilities" button above.
Clone the repository with "git clone https://github.com/Razshy/Wiggle" and add it to your Claude Code skills directory (see the Installation section above).
Wiggle is primarily written in Python. It is open-source under Razshy on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh Wiggle against similar tools.
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Unlocks once the catalog security scan passes (runs nightly).
⚠️ Third-Party Software Notice
This skill is third-party open-source software developed and hosted independently on GitHub. SkillsLLM is an informational directory and does not control or maintain the underlying repository.
Any security checks, ratings, or warnings displayed by SkillsLLM are automated and limited in scope. They do not constitute a security certification or guarantee that the software is safe, error-free, or free from malicious code, vulnerabilities, compromised dependencies, or prompt-injection risks.
Review the source code, permissions, dependencies, and configuration before installing or running any third-party skill. Use is at your own risk. To the maximum extent permitted by applicable law, SkillsLLM is not liable for losses arising from third-party software.
The deep catalog scan for this skill is still queued. Run an instant dependency check now instead.
A working copy of the sandbox that Claude (claude.ai) runs code in.
When Claude executes a command, reads a file, converts a document, or takes a screenshot, it is not running on a web server. It is running inside a small virtual machine, one per conversation. This repository is that machine: the same files, tools, packages, and instructions, packaged so you can run it yourself on Docker, e2b, Modal, or any Linux host.
Codename wiggle is what Anthropic calls this VM internally.
docker build -t wiggle .
docker run -it wiggle bash
# inside:
soffice --version # LibreOffice 24.2
python3 -c "import pandas" # full data science stack
ls /mnt/skills # the 40 playbooks Claude follows
Want the exact bytes instead of a rebuild? The GitHub release carries the full filesystem of a live session (8.9 GB, sanitized):
cat wiggle-part-aa wiggle-part-ab > wiggle.tar.zst
zstd -d -c wiggle.tar.zst | docker import - wiggle:live
See ROOTFS.md for the full download and verification steps.
/mnt/user-data. In production
those are remote storage; here they are plain directories.Machine spec to match if you care about parity: 1 vCPU, 3.9 GiB RAM, no swap. Details in meta/box-spec.md.
| Capability | What gives you that |
|---|---|
| Documents (docx, xlsx, pptx, pdf) | LibreOffice 24.2, pandoc, python-docx, openpyxl |
| OCR (make scans searchable) | tesseract 5 with English models, byte-identical to the public Google release |
| File-type detection | magika (Google model, public build) |
| Web automation and screenshots | Playwright 1.56 with a pinned Chromium at /opt/pw-browsers, plus puppeteer with Chrome-headless-shell |
| Diagrams and charts | mermaid-cli, matplotlib, graphviz |
| Numbers and data | pandas, numpy, scipy, scikit-learn, Jupyter |
| Typesetting and PDFs | TeX Live 2023, poppler, qpdf, ImageMagick, wkhtmltopdf |
| Media | ffmpeg |
| The playbooks Claude follows | mnt-skills/, 40 skills, verbatim |
The skills are the interesting part. They are plain Markdown instruction files that Claude reads before doing certain jobs: how to fill a PDF form, how to run deep research (including the sub-agent prompts), how to drive the desktop with computer use, how to build a skill. Public ones cover office documents and file reading; example ones cover deep-research, morning briefings, painting, MCP server building, and more. Browse them under mnt-skills/.
Two custom Anthropic binaries are included: extract-text (turns uploaded
documents into text, Rust) and the mount daemon interface (rclone-filestore,
Go, documented in meta/filestore-api.md).
Four things live outside the filesystem, so no dump could contain them:
/mnt/user-data, whose contract is
documented in meta/filestore-api.md.For e2b users: e2b's own daemon takes the supervisor's role, which is why this image drops straight into an e2b template.
Any agent that can shell into a container can use this box exactly the way
Claude does: read the relevant /mnt/skills/*/SKILL.md, then run the tools it
names. Inject the environment from
meta/env-contract.md and the behavior matches
production, quirks included.
pandoc x.md -o x.pdf fails until you add fonts-lmodern or use the
Chromium fallback. The real sandbox has the same hole.pip install is blocked by PEP 668. Use uv. The offline wheel cache is
included.-quality for webp. Use Pillow or
sharp.test -s out && file out)
instead of trusting success.extract-text segfaults under x86 emulation on ARM Macs. It is fine on
native x86-64 hosts./mnt/skillsThe build recipe, scripts, and documentation in this repo are MIT (LICENSE).
Everything Anthropic-made is theirs, not MIT:
LICENSE.txt), which does not clearly allow redistribution. They are here
as captured research artifacts.mnt-skills/ and remove the one
COPY mnt-skills/ line from the Dockerfile. The box still builds and runs;
any user can re-obtain the skills by asking Claude to show them.Not affiliated with Anthropic.