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Read one layer

get_node
Read-onlyIdempotent

Retrieve one FigCraft layer as JSON by node ID, including geometry, styles, layout, text, component, interaction, export, and annotation data. Use it to inspect or edit a specific layer.

Instructions

One layer as JSON: id, name, type, geometry, fills, strokes, effects, auto layout, sizing, constraints, text properties, component links, overrides, interactions, exports, dev status and annotations.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYes
depthNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3/5.0
Behavior3/5

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

Annotations already declare readOnly, idempotent, non-destructive, closed-world, so the safety profile is covered. The description adds that the return is JSON with a specific field set, but says nothing about the most consequential behavior: whether the 'depth' parameter expands the returned subtree, and what happens for a missing or invalid id. With annotations carrying safety, this is a middling 3.

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?

A single front-loaded sentence that leads with the return shape. The long field enumeration is borderline padding, but for a tool with no output schema it doubles as return-value documentation.

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?

No output schema exists, so the field list is a reasonable partial stand-in for describing the response. However, the depth parameter's traversal behavior, error cases, and payload size implications are unaddressed, leaving the agent under-informed for a tool whose schema is entirely undescribed.

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

Parameters2/5

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

Schema description coverage is 0% for both parameters, so the description must compensate and does not: it never mentions 'id' or 'depth'. The word 'layer' hints that id is a node identifier, but the semantics of depth (subtree expansion, max 64) are entirely undocumented anywhere an agent can see.

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 resource ('one layer') and enumerates the returned fields, so the agent knows this is a single-node read that yields a rich property bundle. It distinguishes itself implicitly from create_node/set_properties by being a read, but never names a sibling like get_design_context or inspect_document to sharpen the boundary.

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?

There is no statement of when to use this versus get_design_context, get_metadata, inspect_document, or get_code, all of which plausibly overlap with reading design data. The agent must infer the selection rule from the field list alone.

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