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Install in OpenClaw
/install world-model
Description
World Model - Environment understanding, causal reasoning, and prediction for AGI
Usage Guidance
This package is incomplete and internally inconsistent. Before installing or enabling it: 1) Ask the author for the missing runtime files (world_model.py and the referenced world-model-api.ps1) and for provenance (source repository and release signatures). 2) If you receive those files, inspect them for network calls, subprocess execution, file I/O, and credential use (search for requests, socket, subprocess, os.system, open, exec, importlib.exec_module). 3) Do not run in production or grant broad permissions until you verify behavior; test inside a restricted sandbox and monitor outbound connections. 4) Prefer skills that declare required env vars, config paths, and explicit install steps — large capability claims without corresponding code or declared permissions are a red flag. If you want, provide the missing world_model.py and any install scripts and I can re-evaluate with higher confidence.
Capability Analysis
Type: OpenClaw Skill
Name: world-model
Version: 2.0.0
The `unified_wrapper.py` file passes the `goal` parameter, which originates from the AI agent's prompt, directly to methods of the underlying `world_model.py` skill (e.g., `_original.do(goal)`). This design introduces a significant prompt injection vulnerability, as there is no apparent sanitization or validation of the `goal` string within the wrapper. If the unanalyzed `world_model.py` module were to interpret this input as executable code or commands, it could lead to remote code execution. This is a critical vulnerability that allows for potential attacks, rather than evidence of intentional malicious behavior by the skill itself.
Capability Assessment
Purpose & Capability
The SKILL.md promises an AGI-level world model that monitors 50+ system variables, simulates actions, and can 'try actions before executing', but the package declares no required binaries, env vars, or config paths. The shipped files are static JSON data and a wrapper; the actual implementation (references to world-model-api.ps1 and an expected world_model.py) is missing. This mismatch suggests the package is incomplete or intentionally missing runtime code.
Instruction Scope
The documentation includes PowerShell API examples (world-model-api.ps1) and API functions that imply reading/updating world state and performing simulations and risk assessments. Those examples would normally require scripts and code to interact with the host system or other tools, but those files are not present. The SKILL.md also describes capabilities like anomaly detection and 'simulate before acting' which imply capability to run commands or invoke other tools; this scope is broader than the declared package content and permissions.
Install Mechanism
No install spec (instruction-only) which is low-risk. However the included unified_wrapper.py performs a dynamic import of a local world_model.py (absent from the bundle). If a runtime world_model.py were present, that dynamic loading would execute arbitrary Python code from the skill directory — expected for many skill wrappers but worth reviewing in any complete package. Currently nothing is installed, but the wrapper's behavior means a future or alternative package containing world_model.py could run arbitrary code.
Credentials
The skill requests no environment variables or credentials, yet claims to monitor system/network/tools and to execute/simulate actions. world-state.json lists tools including 'exec' and 'browser' (implying command execution or external access). The absence of declared env/credential requirements is not proportionate to the stated capabilities and increases uncertainty about what the real implementation would require or access.
Persistence & Privilege
The skill is not marked always:true and declares no config paths or persistent privileges. disable-model-invocation is false (normal default), so the agent could invoke the skill autonomously — this is expected platform behavior and not by itself a flag. Combine this with other concerns before allowing autonomous use.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install world-model - After installation, invoke the skill by name or use
/world-model - Provide required inputs per the skill's parameter spec and get structured output
Version History
v2.0.0
World Model Skill v2.0.0
- Major update providing comprehensive environment modeling, causal reasoning, and predictive analytics for AGI applications.
- Adds real-time state tracking (50+ variables), anomaly detection, and causal chain analysis with up to 5 levels depth.
- Introduces robust prediction and simulation functions, supporting what-if analysis, risk assessment, and outcome forecasting.
- Includes detailed PowerShell API for state management, causal inference, prediction, and simulation actions.
- Benchmarked performance: 85% prediction accuracy, 92% causal reasoning, simulations under 50ms.
Metadata
Frequently Asked Questions
What is World Model?
World Model - Environment understanding, causal reasoning, and prediction for AGI. It is an AI Agent Skill for Claude Code / OpenClaw, with 459 downloads so far.
How do I install World Model?
Run "/install world-model" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is World Model free?
Yes, World Model is completely free (open-source). You can download, install and use it at no cost.
Which platforms does World Model support?
World Model is cross-platform and runs anywhere OpenClaw / Claude Code is available (darwin, linux, win32).
Who created World Model?
It is built and maintained by tobisamaa (@tobisamaa); the current version is v2.0.0.
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