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AaronGoldsmith

mcp-printable

blender_boolean

Destructive

Cut, union, or intersect two meshes using exact or fast solvers, with built-in connectivity and manifold checks to prevent silent boolean failures.

Instructions

Boolean op on two meshes with built-in connectivity + manifold checks. Always prefer this over raw modifiers in execute_code.

operation: DIFFERENCE | UNION | INTERSECT. solver: EXACT (reliable) | FAST. use_self (EXACT only): classify self-intersecting operands via winding numbers. Set True when an operand contains multiple overlapping shells (multi-shell meshes) — without it the EXACT solver can silently annihilate the target (an ANNIHILATION warning in the result flags this). Slower; default False. use_hole_tolerant (EXACT only): better results when operands have holes (non-watertight geometry). Slower; default False. Returns face counts, connected components, warnings. A WARNING means the boolean may have silently failed — inspect the numbers and re-run.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cutterYes
solverNoEXACT
targetYes
use_selfNo
operationNoDIFFERENCE
keep_cutterNo
use_hole_tolerantNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

Annotations indicate destructiveHint=true, but the description adds substantial context: it mentions built-in checks, warns about silent annihilation when use_self is not set, explains the meaning of warnings, and describes return values. This goes well beyond the annotation.

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

Conciseness4/5

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

The description is well-structured, starting with purpose, followed by parameter details, and ending with return behavior. Each sentence provides useful information without redundancy, though the length is slightly full due to detailed parameter explanations.

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?

Given 7 parameters, conditional constraints, and an output schema, the description covers most critical aspects: operations, solver specifics, edge-case flags, and failure warnings. However, it leaves keep_cutter unexplained and does not clarify the nature of target/cutter identifiers, making it not fully complete.

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

Parameters3/5

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

With 0% schema description coverage, the description must compensate for parameter understanding. It explains operation, solver, use_self (with EXACT-only constraint), and use_hole_tolerant, but omits keep_cutter and does not explicitly define target/cutter as mesh names. Partial compensation, hence a mid score.

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?

Description clearly states it performs a boolean operation on two meshes with connectivity and manifold checks. It enumerates supported operations (DIFFERENCE, UNION, INTERSECT) and explicitly differentiates from raw modifiers in execute_code, making its purpose unambiguous.

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

Usage Guidelines5/5

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

The description explicitly instructs to 'Always prefer this over raw modifiers in execute_code', providing a clear directive on when to use this tool over an alternative. This satisfies the usage guidance criterion with an explicit recommendation.

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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