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save_state

Save the current scene state to restore it later, enabling precise snapshot and rollback within ManimGL scene operations.

Instructions

Save the current scene state for later restoration.

IMPORTANT: Always use MCP tools for scene operations.

Returns: True if state was saved.

Example: >>> save_state()

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

With no annotations, the description carries the full burden for behavioral disclosure. It mentions the return value (True) but does not disclose whether saving overwrites a previous state, whether a snapshot is taken, any costs or side effects, or behavior on failure. The limited information leaves significant behavioral gaps.

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

Conciseness3/5

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

The description is concise, but it includes an unnecessary 'IMPORTANT' note that is not specific to this tool, and a trivial example. While the length is appropriate, the extra note does not earn its place and slightly detracts from focus. Structure is acceptable but not exemplary.

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

Completeness3/5

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

For a simple zero-parameter tool with an output schema, the description is adequate but not complete. It covers the primary purpose and return value but fails to mention any relationship to restore_state or potential caveats like state overwriting. The simplicity of the tool lowers the bar, so a 3 is appropriate.

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

Parameters4/5

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

The tool has zero parameters, so the schema coverage is 100% and no parameter documentation is needed. Per the rubric, 0 params earns a baseline of 4. The description adds nothing about parameters, but that is acceptable given there are none.

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?

The description clearly states the tool's action ('Save the current scene state') and its purpose ('for later restoration'). This distinguishes it from sibling tools like restore_state, which would be the counterpart operation.

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

Usage Guidelines2/5

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

The description provides no explicit guidance on when to use save_state versus alternatives like restore_state. The 'IMPORTANT' note about using MCP tools is generic and not specific to this tool. There is no mention of prerequisites or context in which saving state is appropriate.

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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