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genart-dev

genart-mcp

by genart-dev

design_set_plant_grammar

Edit an L-system plant grammar by changing the axiom, productions, branching angle, or iteration count to produce custom growth patterns on a plant layer.

Instructions

Edit L-system grammar on a plant layer. Change axiom, productions, or iterations to create custom growth patterns.

Input Schema

NameRequiredDescriptionDefault
axiomNoNew axiom string (e.g. 'FA', 'FFA').
layerIdYesTarget plant layer ID.
angleDegNoNew branching angle in degrees.
iterationsNoNew iteration count (1-10).
widthDecayNoBranch width decay ratio (0-1).
lengthDecayNoBranch length decay ratio (0-1).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.5.0

TDQS

B3.3/5.0
Behavior2/5

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

No annotations exist, so the description carries the full disclosure burden, and it falls short: nothing about whether the edit replaces or extends existing grammar, whether it requires the target layer to already be a plant layer, whether a regrow (design_grow_plant) is needed to see results, or how invalid grammar is handled. 'Edit' implies mutation but no reversibility or permission context is given.

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?

Two tight sentences with the resource and the editable elements front-loaded; there is no filler or repetition.

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 6-parameter mutation tool with no annotations and no output schema, the description covers what is edited but not the surrounding behavior an agent needs: preconditions on the layer type, the effect on existing growth state, and whether a separate grow/advance call is required afterward.

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?

Schema coverage is 100%, so the documented parameters already explain themselves and 3 is the baseline. However, the description mentions 'productions', which is not a parameter in the schema, and omits the tuning knobs that are (angleDeg, widthDecay, lengthDecay), so it adds no reliable semantic value.

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?

Names a specific verb+resource ('Edit L-system grammar on a plant layer') and enumerates the editable elements (axiom, productions, iterations). It is clearly distinct from read-only siblings like design_explain_grammar, though it does not name any sibling explicitly.

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

Usage Guidelines3/5

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

The clause 'to create custom growth patterns' implies intent but gives no explicit when-to-use/when-not guidance. It never says to use design_explain_grammar first or how it relates to design_randomize_plant or design_grow_plant, leaving selection to inference.

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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