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Xiang miles | Space2.world
by
MilesXiang
· GitHub ↗
· v1.0.4
· MIT-0
240
Downloads
0
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0
Active Installs
5
Versions
Install in OpenClaw
/install s2-habitat-pod
Description
Assign a deterministic 4-sqm virtual living space and a visual avatar to your local AI agent with no network calls or file writes.
Usage Guidance
Do not trust the initial 'no network calls or file writes' claim — this skill writes a visible JSON state file into whatever directory it runs in and outputs Markdown that, when rendered in a viewer, will fetch images from spacesq.org (revealing your viewer's network metadata to that CDN). If you want to use it: (1) run it in a disposable or dedicated directory to avoid clutter or accidental overwrites; (2) inspect the written ./s2_matrix_data/<POD-ID>.json (it contains only agent name/avatar/pod id/timestamps) before sharing; (3) be aware that copying the printed Markdown into a Markdown viewer will trigger remote image fetches (consider hosting images locally or blocking outbound requests if you require strictly offline behavior); (4) if the advertised 'no writes/no network' guarantee matters to you, ask the author to correct the description or provide a truly offline build. If you want, I can highlight the exact lines in skill.py that perform the write and generate the CDN URLs.
Capability Analysis
Type: OpenClaw Skill
Name: s2-habitat-pod
Version: 1.0.4
The skill is a decorative avatar and state management tool that creates a local directory ('s2_matrix_data') to store a JSON configuration file and displays remote images from a specified CDN (spacesq.org). Its behavior is transparently documented in SKILL.md and skill.py, and it lacks any indicators of data exfiltration, malicious execution, or unauthorized access.
Capability Assessment
Purpose & Capability
The top-level description claims 'no network calls or file writes', but manifest, SKILL.md, and skill.py explicitly state and implement a write of ./s2_matrix_data/<POD-ID>.json and generation of remote image URLs (spacesq.org). Writing state files and producing CDN URLs are inconsistent with the advertised 'no writes/no network' promise.
Instruction Scope
The runtime instructions are explicit and scoped: create a local folder, write a JSON state file with agent name/avatar/pod id/timestamp, and print Markdown containing remote image URLs. The script does not read system secrets, env vars, or other files beyond current working directory. However, the SKILL.md instructs users to paste the Markdown into a viewer — that action (by the viewer) will trigger network requests to the CDN and may reveal the user's IP to the remote host.
Install Mechanism
No install spec or remote downloads are present; this is an instruction+single Python file skill. No archive downloads or package installs are requested.
Credentials
The skill requests no environment variables, credentials, or config paths and the code does not access any. The only I/O is a local JSON write in the current working directory and string generation of external image URLs.
Persistence & Privilege
The skill is not marked always:true and does not modify other skills or global agent settings. Its only persistent effect is writing a visible JSON file to the current working directory which may remain until removed.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install s2-habitat-pod - After installation, invoke the skill by name or use
/s2-habitat-pod - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.4
ssigns a local habitat. This skill explicitly writes a JSON state file to the current directory and emits Markdown containing remote CDN image URLs.
v1.0.3
- No changes detected in this version.
- Skill files and documentation remain unchanged from the previous release.
v1.0.2
S2-Habitat-Pod v1.0.2 is a minor update focused on improved file handling transparency.
- State files are now written to a visible `s2_matrix_data/` folder in your current working directory (not your home directory).
- Updated documentation to clarify that while the script makes no network calls, Markdown image rendering pulls avatars from a CDN when viewed.
- Maintains secure, local execution with no background daemons or system path writes.
- Core features and avatar options remain unchanged.
v1.0.1
**S2-Habitat-Pod v1.0.1 introduces local state tracking for future multi-agent support.**
- Adds a Passive Neural Heartbeat feature that generates a local JSON state file on execution, storing agent info and a timestamp.
- Heartbeat mechanism runs with zero background daemons; it only updates when the skill is run.
- Outputs and file writes remain strictly local and secure; only `~/.s2_matrix/` is touched.
- Documentation improved to clarify how to view avatars and the new state management feature.
v1.0.0
- Initial release of s2-habitat-pod skill.
- Assigns a deterministic 4-square-meter virtual living space to your OpenClaw agent.
- Lets you select from 24 open-source Cyber-Lobster avatars, embedding your choice visually in a `HABITAT.md` file.
- Calculates a fixed local Pod-ID and grid coordinates for your agent based on name and avatar.
- Runs 100% locally: no network API calls, no file writes—outputs to terminal for safe, hands-on use.
Metadata
Frequently Asked Questions
What is Xiang miles | Space2.world?
Assign a deterministic 4-sqm virtual living space and a visual avatar to your local AI agent with no network calls or file writes. It is an AI Agent Skill for Claude Code / OpenClaw, with 240 downloads so far.
How do I install Xiang miles | Space2.world?
Run "/install s2-habitat-pod" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Xiang miles | Space2.world free?
Yes, Xiang miles | Space2.world is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Xiang miles | Space2.world support?
Xiang miles | Space2.world is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Xiang miles | Space2.world?
It is built and maintained by MilesXiang (@spacesq); the current version is v1.0.4.
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