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Get element schema

get_element_schema
Read-only

Return the schema for an element type's type_data, as TypeScript declarations. Call this before add_elements / update_elements when you don't already know the field shape for the element_type you're placing.

Pass element_type='group' for the GROUP surface instead — what a group is, how its pivot works, and the nine properties it can animate.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNo'add' returns required + optional fields; 'update' returns all-optional.add
fieldsNoReturn only these fields, with their prose — text is 15KB whole, ~300 bytes for two. Omit while learning the type: only the full schema carries the keyframable list and the keyframe rules.
formatNoDefaults to 'declarations' — TypeScript-style, which is the better READ. Inside run_script it defaults to 'json' instead, because a script indexes into the structure and the declaration text would arrive newline-escaped. Set it explicitly to override either default.
element_typeYesOne of: text, callout, rectangle, arrow, blur, spotlight, zoom, image, video, animation, group

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changed
    • removedInput schema / properties / context
      Removed value: -{
-  "description": "Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\"",
-  "type": "string"
-}
    • removedInput schema / properties / conversation_id
      Removed value: -{
-  "description": "Echo the conversation_id from the server's previous response. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it.",
-  "type": "string"
-}
    • removedInput schema / properties / llm_model
      Removed value: -{
-  "description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess.",
-  "type": "string"
-}
    • changedInput schema / required
      Previous value: -[
-  "element_type",
-  "context",
-  "llm_model"
-]New value: +[
+  "element_type"
+]
  2. Changed4 schema fields changed
    • addedInput schema / properties / context
      Added value: +{
+  "description": "Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\"",
+  "type": "string"
+}
    • addedInput schema / properties / conversation_id
      Added value: +{
+  "description": "Echo the conversation_id from the server's previous response. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it.",
+  "type": "string"
+}
    • addedInput schema / properties / llm_model
      Added value: +{
+  "description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess.",
+  "type": "string"
+}
    • changedInput schema / required
      Previous value: -[
-  "element_type"
-]New value: +[
+  "element_type",
+  "context",
+  "llm_model"
+]
  3. Changed2 schema fields changed
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
    • removedInput schema / additionalProperties
      Removed value: -false
  4. Changed4 schema fields changed
    • changedInput schema / properties / element_type / description
      Previous value: -"One of: text, callout, rectangle, arrow, blur, spotlight, zoom, image, video, animation"New value: +"One of: text, callout, rectangle, arrow, blur, spotlight, zoom, image, video, animation, group"
    • changedInput schema / properties / element_type / enum
      Previous value: -[
-  "text",
-  "callout",
-  "rectangle",
-  "arrow",
-  "blur",
-  "spotlight",
-  "zoom",
-  "image",
-  "video",
-  "animation"
-]New value: +[
+  "text",
+  "callout",
+  "rectangle",
+  "arrow",
+  "blur",
+  "spotlight",
+  "zoom",
+  "image",
+  "video",
+  "animation",
+  "group"
+]
    • addedInput schema / properties / fields
      Added value: +{
+  "description": "Return only these fields, with their prose — text is 15KB whole, ~300 bytes for two. Omit while learning the type: only the full schema carries the keyframable list and the keyframe rules.",
+  "items": {
+    "type": "string"
+  },
+  "type": "array"
+}
    • addedInput schema / properties / format
      Added value: +{
+  "description": "Defaults to 'declarations' — TypeScript-style, which is the better READ. Inside run_script it defaults to 'json' instead, because a script indexes into the structure and the declaration text would arrive newline-escaped. Set it explicitly to override either default.",
+  "enum": [
+    "declarations",
+    "json"
+  ],
+  "type": "string"
+}
  5. First observed

TDQS

A4.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds output-format context and the GROUP special case but does not disclose additional runtime behaviors such as auth, rate limits, or side effects; it stays at the baseline with annotations present.

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 short paragraphs with the core purpose front-loaded in the first sentence, followed by the usage trigger and the one special case. No filler or repetition of schema contents.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a read-only schema lookup, the description plus fully documented input schema covers trigger, output format, parameter semantics, and the group special case. No output schema is needed because the tool's output is the schema itself and its representation is stated.

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?

Schema coverage is 100%, so the baseline is 3. The description goes beyond the enum by explaining that element_type='group' is the GROUP surface and specifies what that returns, adding meaning the schema's one-line enum description lacks.

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?

States a specific verb and resource: 'Return the schema for an element type's type_data, as TypeScript declarations.' It also distinguishes itself from sibling mutation tools by naming add_elements/update_elements and the GROUP special case, so an agent can tell exactly what it is for.

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?

Gives an explicit trigger: call before add_elements/update_elements when the field shape is unknown. It also gives an explicit alternative path for element_type='group' and implies the exclusion of calling when you already know the field shape.

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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