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create_session

Creates an isolated sandbox environment with specified language and dependencies for secure code execution.

Instructions

Creates an isolated sandbox environment (Docker container).

The sandbox starts empty — specify ALL needed packages in dependencies.
For data analysis, always include pandas and numpy.

Args:
    language: Sandbox language/runtime. Use "python", "node", or "r".
    dependencies: Packages to pre-install. Keys are package names,
        values are version strings (use "" for latest). Always use strings,
        never numbers — e.g. "2.2" not 2.2. Null/None is treated as "".
        Example: {"pandas": "", "numpy": "1.26", "matplotlib": "3.9.0"}.

Returns:
    JSON with session_id and session info.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
languageNopython
dependenciesNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description carries full burden. It discloses isolation (Docker) and emptiness, but omits details like rate limits, authentication needs, or whether existing sessions are affected. Adequate but not comprehensive.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Compact and well-structured: one-line purpose, followed by usage tip, then formatted Args and Returns sections. Every sentence is informative with no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers purpose, parameter usage, and return format. Missing details like error handling or resource limits, but given low complexity (2 params, output schema present) and sibling tools, it is largely complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema has 0% description coverage, but description adds complete semantics: language options (python, node, r), dependency structure (package names, version strings, use quotes, null handling), and example. Adds high value beyond schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states it creates an isolated sandbox environment (Docker container), with a specific verb and resource. Distinguishes from sibling tools (execute, file ops, stop) which focus on other actions.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit guidance: sandbox starts empty so specify all needed packages, and for data analysis include pandas and numpy. Implies when to use, but does not explicitly state when not to use or list alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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