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add_annotation_stroke

Add a stroke to an annotation layer using XYZ coordinates and pen pressure. Creates a new stroke on the specified layer.

Instructions

Add a stroke to an annotation layer.

Creates a new stroke with the given points on the specified layer. Note: AnnotationStroke does not support per-point strength/opacity.

Args: annotation_name: Name of the annotation data block. layer_name: Name of the layer to add the stroke to. points: List of XYZ coordinates, e.g. [[0,0,0], [1,1,0], [2,0,0]]. Maximum 10000 points. pressure: Pen pressure for all points. Range: 0.0-1.0.

Returns: Confirmation dict with point count.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
annotation_nameYes
layer_nameYes
pointsYes
pressureNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

No annotations, so description carries burden. Discloses new stroke creation, lack of per-point strength/opacity, max 10000 points, pressure range, and return type. Lacks mention of appending behavior or error handling, but sufficient for basic understanding.

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?

Concise and well-structured: purpose statement, note, parameter list, return type. Each sentence serves a purpose, no fluff. Front-loaded with primary action.

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 parameters, return, and key behavioral notes. Lacks error conditions (e.g., missing layer or invalid points) and does not confirm append vs. overwrite behaviour. Output schema exists but not provided; still, description sufficient for typical use.

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?

With 0% schema description coverage, description fully compensates by explaining each parameter: annotation_name (data block name), layer_name (target layer), points (XYZ list with example and limit), pressure (range). Adds essential meaning 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 adds a stroke to an annotation layer, creating a new stroke with points. Distinguishes from siblings like add_annotation_layer (layer) and set_annotation_stroke_property (modify).

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?

Implied usage from name and description, but no explicit when-to-use or alternatives guidance. Could mention when to use this vs. add_annotation_layer or set_annotation_stroke_property.

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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