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get_previs_system_prompt

Returns the complete Previs Director V2 system prompt ready to inject into a Blender AI session for guided 3D previsualization planning.

Instructions

Get the complete Previs Director V2 system prompt ready to inject into a Blender AI session (e.g., Blender GPT, Blender MCP, or manual paste). Returns the full prompt text.

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.5.0

TDQS

A3.9/5.0
Behavior3/5

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

No annotations are provided, so the description carries the behavioral burden. "Get" and "Returns the full prompt text" imply a safe read, but the description does not explicitly state read-only behavior, side effects, or any operational constraints.

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?

The description is two tight sentences, front-loaded with the core action and followed by the concrete use context. Every sentence adds useful information without repetition or fluff.

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?

For a zero-parameter getter with an output schema, the description supplies enough context to call it correctly: what it returns and how the returned prompt is meant to be used. The main remaining gap is explicit read-only/no-side-effect disclosure, which annotations would normally carry but are absent here.

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?

There are zero parameters, so the baseline is 4. No parameter semantics are needed, and the description correctly does not invent any.

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

Purpose4/5

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

The description uses a clear verb+resource: "Get the complete Previs Director V2 system prompt." It distinguishes the content as the full director prompt, but does not explicitly contrast this with sibling tools like get_previs_help or get_phase_instructions.

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?

It gives clear usage context: the prompt is "ready to inject into a Blender AI session" with examples including Blender GPT, Blender MCP, or manual paste. It does not state when to avoid this tool or how it differs from adjacent prompt/help tools.

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