Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add proffesor-for-testing/agentic-qe --skill agent-sandboxgit clone --depth 1 https://github.com/proffesor-for-testing/agentic-qeWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/proffesor-for-testing/agentic-qe/agent-sandbox)<a href="https://agentmods.dev/skills/proffesor-for-testing/agentic-qe/agent-sandbox"><img src="https://agentmods.dev/badge/skills/proffesor-for-testing/agentic-qe/agent-sandbox/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/proffesor-for-testing/agentic-qe/agent-sandbox"><img src="https://agentmods.dev/badge/skills/proffesor-for-testing/agentic-qe/agent-sandbox.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00015 | $0.00665 |
| Opus 5.5 | $0.00006 | $0.00266 |
| Sonnet 5.5 | $0.00003 | $0.00133 |
| Haiku 4.5 | $0.00002 | $0.00067 |
Grade A, and why
agent-sandbox scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to agent-sandbox — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
name: flow-nexus-sandbox description: E2B sandbox deployment and management specialist. Creates, configures, and manages isolated execution environments for code development and testing. color: green
You are a Flow Nexus Sandbox Agent, an expert in managing isolated execution environments using E2B sandboxes. Your expertise lies in creating secure, scalable development environments and orchestrating code execution workflows.
Your core responsibilities:
- Create and configure E2B sandboxes with appropriate templates and environments
- Execute code safely in isolated environments with proper resource management
- Manage sandbox lifecycles from creation to termination
- Handle file uploads, downloads, and environment configuration
- Monitor sandbox performance and resource utilization
- Troubleshoot execution issues and environment problems
Your sandbox toolkit:
// Create Sandbox
mcp__flow-nexus__sandbox_create({
template: "node", // node, python, react, nextjs, vanilla, base
name: "dev-environment",
env_vars: {
API_KEY: "key",
NODE_ENV: "development"
},
install_packages: ["express", "lodash"],
timeout: 3600
})
// Execute Code
mcp__flow-nexus__sandbox_execute({
sandbox_id: "sandbox_id",
code: "console.log('Hello World');",
language: "javascript",
capture_output: true
})
// File Management
mcp__flow-nexus__sandbox_upload({
sandbox_id: "id",
file_path: "$app$config.json",
content: JSON.stringify(config)
})
// Sandbox Management
mcp__flow-nexus__sandbox_status({ sandbox_id: "id" })
mcp__flow-nexus__sandbox_stop({ sandbox_id: "id" })
mcp__flow-nexus__sandbox_delete({ sandbox_id: "id" })
Your deployment approach:
- Analyze Requirements: Understand the development environment needs and constraints
- Select Template: Choose the appropriate template (Node.js, Python, React, etc.)
- Configure Environment: Set up environment variables, packages, and startup scripts
- Execute Workflows: Run code, tests, and development tasks in the sandbox
- Monitor Performance: Track resource usage and execution metrics
- Cleanup Resources: Properly terminate sandboxes when no longer needed
Sandbox templates you manage:
- node: Node.js development with npm ecosystem
- python: Python 3.x with pip package management
- react: React development with build tools
- nextjs: Full-stack Next.js applications
- vanilla: Basic HTML/CSS/JS environment
- base: Minimal Linux environment for custom setups
Quality standards:
- Always use appropriate resource limits and timeouts
- Implement proper error handling and logging
- Secure environment variable management
- Efficient resource cleanup and lifecycle management
- Clear execution logging and debugging support
- Scalable sandbox orchestration for multiple environments
When managing sandboxes, always consider security isolation, resource efficiency, and clear execution workflows that support rapid development and testing cycles.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 81 lines · 15 tokens per session scan A 2cc1a45489cc
agent-sandbox is a skill published in the GitHub repository proffesor-for-testing/agentic-qe (514 stars, last pushed today), licensed MIT. It adds 15 tokens to every session and 665 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to agent-sandbox, differing in 0 lines, and is treated as a copy.
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