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Secure Python Code Sandbox

核心功能是在隔离安全环境执行任意Python代码,预置requests、NumPy、pandas等常用库。适用于动态代码执行、数据处理、实时计算、API集成等场景。输入为待执行代码和超时秒数,输出包含标准输出、错误输出及执行结果,需通过AgentPMT平台调用。

agentpmt
热度 23.16
最近更新 2026-06-10 08:14:26
分类:开发依赖:MCP 服务 / 第三方 API应用场景:API 集成 / 数据处理 / 自动化脚本 / 调试排错

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add secure-python-code-sandbox
Metadata
name
secure-python-code-sandbox
description
Secure Python Code Sandbox: Execute arbitrary Python code in an isolated sandbox with pre-installed libraries (requests, NumPy, pandas). Returns stdout, stderr, and execution results. Use when an agent needs secure python code sandbox, dynamic code execution, data manipulation, on the fly calculation, api integration, invoke, code, timeout seconds through AgentPMT-hosted remote tool calls. Discovery terms: secure python code sandbox, dynamic code execution, data manipulation.
version
1.0.0
homepage
https://www.agentpmt.com/marketplace/secure-python-code-sandbox
compatibility
Agent instructions for AgentPMT-hosted remote tool calls. Follow this skill body for supported account, wallet, and setup routes. No local command runtime is declared.
metadata
{"author":"agentpmt","openclaw":{"homepage":"https://www.agentpmt.com/marketplace/secure-python-code-sandbox"}}

Secure Python Code Sandbox

Freshness

Last updated: 2026-06-10.

If the current date is more than 7 days after the last updated date, reinstall this skill from skills.sh or ClawHub before relying on endpoints, schemas, setup steps, or examples.

What This Tool Does

For safely executing arbitrary Python code snippets within an isolated, secure environment. The sandbox comes pre-installed with common data science and web request libraries, including requests, NumPy, and pandas. It is ideal for performing quick computations, data transformations, or dynamic API calls without requiring external infrastructure.

When To Use

  • Use this skill for Secure Python Code Sandbox on AgentPMT.
  • Use it when an agent needs this specific tool's behavior, schema, inputs, outputs, and invocation shape.
  • Search and activation keywords: secure python code sandbox, dynamic code execution, data manipulation, on the fly calculation, api integration, invoke, code, timeout seconds.
  • Supported action names: invoke.

Use Cases

  • Dynamic Code Execution
  • Data Manipulation
  • On-the-fly Calculation
  • API Integration
  • Data Analysis
  • Custom Scripting
  • Algorithmic Tasks
  • Web Scraping

Categories And Industries

No categories or industry tags are published for this tool.

Actions And Schema

Complete generated action schema: ./schema.md. Supported action count: 1. x402 availability: not enabled for this product.

  • invoke (action slug: invoke): For safely executing arbitrary Python code snippets within an isolated, secure environment. The sandbox comes pre-installed with common data science and web request libraries, including requests, NumPy, and pandas. It is ideal for performing quick computations, data transformations, or dynamic API calls without requiring external infrastructure. Price: 10 credits. Parameters: code, timeout_seconds.

Live Schema And Examples

Use the compact schema above for ordinary calls. Before a new production integration, or whenever parameters, enum values, nested objects, outputs, or examples are unclear, fetch live details first.

  • Exact schema: call agentpmt-tool-search-and-execution with action: "get_schema", and tool_id: "secure-python-code-sandbox".
  • Detailed examples: call agentpmt-tool-search-and-execution with action: "get_instructions" and tool_id: "secure-python-code-sandbox", or call this product with action: "get_instructions" when the product tool is already selected.
  • Treat returned live schema and instructions as more specific than this generated summary.

MCP schema lookup through the main AgentPMT MCP server:

{
  "method": "tools/call",
  "params": {
    "name": "AgentPMT-Tool-Search-and-Execution",
    "arguments": {
      "action": "get_schema",
      "tool_id": "secure-python-code-sandbox"
    }
  }
}

For live examples, keep the same MCP tool and use these arguments:

{
  "action": "get_instructions",
  "tool_id": "secure-python-code-sandbox"
}

Authenticated AgentPMT REST schema lookup body:

{
  "name": "agentpmt-tool-search-and-execution",
  "parameters": {
    "action": "get_schema",
    "tool_id": "secure-python-code-sandbox"
  }
}

Authenticated AgentPMT REST live examples body:

{
  "name": "agentpmt-tool-search-and-execution",
  "parameters": {
    "action": "get_instructions",
    "tool_id": "secure-python-code-sandbox"
  }
}

Call This Tool

Product slug: secure-python-code-sandbox

Marketplace page: https://www.agentpmt.com/marketplace/secure-python-code-sandbox

  • AgentPMT account route: first use ../agentpmt-account-mcp-rest-api-setup to connect the main MCP server or REST API for an Agent Group where this tool is enabled.
  • x402 route: not enabled for this product.
  • AgentPMT overview: use ../what-is-agentpmt for marketplace, Agent Group, workflow, MCP, REST, and payment concepts.

If those setup skills are not installed beside this product skill, use the downloads below.

Core AgentPMT setup skills:

  • What AgentPMT is: ../what-is-agentpmt
  • AgentPMT account MCP/REST setup: ../agentpmt-account-mcp-rest-api-setup

skills.sh install script:

npx skills add AgentPMT/agent-skills --skill what-is-agentpmt
npx skills add AgentPMT/agent-skills --skill agentpmt-account-mcp-rest-api-setup

MCP call shape after the main AgentPMT MCP server is connected:

{
  "method": "tools/call",
  "params": {
    "name": "Secure-Python-Code-Sandbox",
    "arguments": {
      "action": "invoke",
      "code": "example code",
      "timeout_seconds": 10
    }
  }
}

Use the exact tool name returned by tools/list; the name above is the expected readable form.

Authenticated AgentPMT REST call body:

{
  "name": "secure-python-code-sandbox",
  "parameters": {
    "action": "invoke",
    "code": "example code",
    "timeout_seconds": 10
  }
}

Use the setup skill for the account connection details before making REST calls.

Response Handling

  • Treat the returned JSON as the source of truth for this tool call.
  • If the response includes warnings or correction targets, apply them before retrying.
  • If the response includes a passed or success-style boolean, use it as the workflow gate.
  • If validation fails or the response shape is unclear, call get_schema or get_instructions before retrying.
  • If invoke fails, preserve the request parameters and retry only after fixing schema, auth, or payment errors.

Security

  • Do not place account secrets, wallet private keys, mnemonics, signatures, or payment headers in prompts or logs.
  • Keep tool inputs scoped to the minimum content needed for the task.
  • Use the setup skills for credential handling; this product skill only defines product-specific behavior.

AgentPMT Reference