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zhenstaff

private computation

by Justin Liu · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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Install in OpenClaw
/install private-computation
Description
Zero-Knowledge Execution for Sensitive Agent Tasks - Privacy computing framework for AI Agents
Usage Guidance
This registry entry is an instruction-only README that promises advanced privacy features but contains no code or install metadata. Before using it or running the suggested npm install: 1) Verify the package exists on npm (or the GitHub repo) and inspect its source code — do not blindly npm install. 2) Confirm where audit logs are stored or transmitted, and how the masterKey is generated and protected. 3) Avoid storing real production secrets (medical, banking, or live LLM keys) until you can audit the implementation. 4) If you need these features for compliance, prefer well-audited libraries or vendor-provided solutions and consider an independent security review. If you want, I can: (a) check npm or GitHub for the referenced package and report what I find, or (b) list specific questions to ask the package author to verify safety.
Capability Analysis
Type: OpenClaw Skill Name: private-computation Version: 1.0.0 The skill bundle provides documentation and usage instructions for a privacy-focused computation framework ('openclaw-private-computation') designed for AI agents. The SKILL.md file outlines features for encrypted secret management (AES-256-GCM), secure task execution, and audit logging, which are consistent with its stated purpose of enhancing security and compliance (GDPR/HIPAA). No evidence of malicious intent, data exfiltration, or harmful prompt injection was found in the provided files (_meta.json, SKILL.md).
Capability Assessment
Purpose & Capability
The SKILL.md advertises encryption, TEE isolation, ZK proofs and blockchain-style audit logs and shows npm install instructions, but the registry entry contains only the SKILL.md (no code files, no install spec). That makes the claimed capabilities unverifiable from this bundle and indicates a mismatch between the described functionality and what the skill actually provides.
Instruction Scope
Instructions show API usage patterns that store and retrieve secrets (agent.setSecret / getSecret), execute sensitive tasks, and write audit logs (storagePath defaults to ~/.openclaw). These calls are in-scope for a private-computation library, but the document gives no details about where audit logs are transmitted, how the masterKey is stored/derived, or how isolation is achieved — missing details that matter for secrets handling.
Install Mechanism
Although the README shows 'npm install openclaw-private-computation' and 'clawhub install', the registry provides no install spec and no packaged code. That difference is suspicious: either this is documentation-only (which is fine) or the intended package must be fetched from an external registry (which should be audited before use).
Credentials
The skill declares no required environment variables or credentials, yet the examples demonstrate storing/using many sensitive API keys (OPENAI_API_KEY, MEDICAL_API_KEY, BANK_API_KEY, etc.). Absence of declared required envs is not itself dangerous, but you should not assume the skill (or the separately published npm package) treats or transmits those secrets safely without review.
Persistence & Privilege
The skill does not request always:true and is user-invocable only. However, the documented default storagePath (~/.openclaw) implies the library (if installed) would write to the user's home directory — verify storage/encryption details before saving secrets.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install private-computation
  3. After installation, invoke the skill by name or use /private-computation
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release of OpenClaw Private Computation. - Introduces a privacy-first computation framework for AI Agents, supporting zero-knowledge execution of sensitive tasks. - Features encrypted credential storage (AES-256-GCM), isolated/secure task execution, and immutable audit logs. - Supports multiple security levels, including basic, TEE isolation, and strict zero-knowledge modes. - Designed for GDPR and HIPAA compliance. - Provides a simple TypeScript/Node.js API for credential management, secure task execution, and audit logging. - Documentation, examples, and roadmap included.
Metadata
Slug private-computation
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is private computation?

Zero-Knowledge Execution for Sensitive Agent Tasks - Privacy computing framework for AI Agents. It is an AI Agent Skill for Claude Code / OpenClaw, with 273 downloads so far.

How do I install private computation?

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

Is private computation free?

Yes, private computation is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does private computation support?

private computation is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created private computation?

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

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