surrealfsSurrealFS virtual filesystem for AI agents. Rust core + Python agent (Pydantic AI). Persistent file operations backed by SurrealDB. Part of the surreal-skill...
Install via ClawdBot CLI:
clawdbot install 24601/surrealfsGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Accesses sensitive credential files or environment variables
/etc/passwdContains telemetry, tracking, or analytics calls not mentioned in documentation
telemetry, set: `export LOGFIRE_SENDCalls external URL not in known-safe list
https://example.comAI Analysis
The skill's primary risk is telemetry injection via Pydantic Logfire, which is documented but may send data externally unless explicitly disabled. The credential access signal is a false positive from an example command (`curl https://example.com`), and the external URL is also from the same benign example. No hidden instructions, credential harvesting, or obfuscation are present.
Generated Mar 21, 2026
AI agents can use SurrealFS to maintain persistent workspaces across sessions, storing and retrieving files like code snippets, research notes, and project drafts. This enables continuity in tasks such as content creation or software development, with hierarchical organization and search capabilities via SurrealDB queries.
Multiple AI agents can share and access a centralized virtual filesystem hosted on SurrealDB, allowing collaborative editing and querying of documents, datasets, and templates. This supports use cases like team-based research, strategy planning, or content management with controlled permissions.
Marketing or creative teams can deploy AI agents with SurrealFS to store, organize, and retrieve content templates, campaign assets, and metadata. Agents can generate and update materials like blog posts or social media content, leveraging persistent storage for version control and reuse.
Developers can integrate SurrealFS into AI agents to automate project setup by storing boilerplate code, configuration files, and documentation templates. Agents can quickly scaffold new projects, apply updates, and manage dependencies, improving efficiency in software lifecycle management.
In industries like finance or healthcare, AI agents can use SurrealFS with remote SurrealDB backends to handle sensitive documents, ensuring data persistence and audit trails. The sandboxed virtual filesystem and credential management help comply with security standards while enabling content search and retrieval.
Offer a cloud-based service where users subscribe to managed SurrealDB instances with integrated SurrealFS, providing AI agents with persistent file storage, collaboration tools, and analytics. Revenue comes from tiered plans based on storage, query limits, and agent integrations.
Sell enterprise licenses for on-premises or private cloud deployments of SurrealFS, including custom integrations, security audits, and dedicated support. Target large organizations needing compliance, scalability, and tailored solutions for AI-driven workflows.
Provide a free tier of SurrealFS for individual developers and small teams, with premium features like advanced telemetry, multi-agent coordination, and priority updates. Monetize through upsells to pro plans and partnerships with AI platform providers.
💬 Integration Tip
Ensure SurrealDB credentials are securely managed using environment variables, and consider containerizing the Python agent to isolate network access and pipe commands for enhanced security.
Scored Apr 19, 2026
Audited Apr 18, 2026 · audit v1.0
Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.
Give your AI agent eyes to see the entire internet. 7500+ GitHub stars. Search and read 14 platforms: Twitter/X, Reddit, YouTube, GitHub, Bilibili, XiaoHongS...
A self-evolution engine for AI agents. Analyzes runtime history to identify improvements and applies protocol-constrained evolution. Communicates with EvoMap...
Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.
Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express...
Meta-agent skill for orchestrating complex tasks through autonomous sub-agents. Decomposes macro tasks into subtasks, spawns specialized sub-agents with dynamically generated SKILL.md files, coordinates file-based communication, consolidates results, and dissolves agents upon completion. MANDATORY TRIGGERS: orchestrate, multi-agent, decompose task, spawn agents, sub-agents, parallel agents, agent coordination, task breakdown, meta-agent, agent factory, delegate tasks