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Update project

update_project

Update a project's metadata: rename, change description, move to a different folder, or change aspect ratio.

Only fields you provide are changed. To move a project to the workspace root, pass folder_id="" (empty string).

Aspect ratio: pass any "W:H" (positive integers). The canvas is fit inside 1920×1080 keeping the ratio, so element pixel coordinates use the resulting canvas. Common values:

  • "16:9" → 1920×1080 (landscape, YouTube/web — default)

  • "9:16" → 608×1080 (portrait — TikTok/Reels/Shorts)

  • "1:1" → 1080×1080 (square — Instagram feed)

  • "3:4" → 810×1080 (portrait card)

  • "4:5" → 864×1080 (portrait — Instagram feed)

Element coordinates are stored as fractions of the canvas, so existing elements reflow to the new canvas automatically — no element coordinates are rewritten.

Concurrency: whole-project mutation (conflict domain: the entire project) — serialize. Do not run it in parallel with ANY other mutation on the same project_id, including element/voiceover edits; run them one at a time. (Mutations to different projects run in parallel freely.)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
titleNoNew project title
folder_idNoNew folder ID. Pass '' (empty string) to move to workspace root.
project_idYesThe project ID to update
descriptionNoNew description
aspect_ratioNoNew aspect ratio as 'W:H' (positive integers). Common: '16:9' landscape, '9:16'/'4:5'/'3:4' portrait, '1:1' square.

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: -[
-  "project_id",
-  "context",
-  "llm_model"
-]New value: +[
+  "project_id"
+]
  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: -[
-  "project_id"
-]New value: +[
+  "project_id",
+  "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. First observed

TDQS

A5/5.0
Behavior5/5

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

Beyond the annotations, the description discloses important behavior: partial updates, aspect-ratio canvas fitting, automatic element reflow via fractional coordinates, and concurrency constraints. These are non-obvious traits that materially affect how an agent should invoke and schedule the tool.

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?

The description is front-loaded with purpose, then moves through field behavior, aspect-ratio examples, and concurrency. Every sentence earns its place, and the bullet list for common aspect ratios keeps the content scannable.

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 metadata-update tool, the description covers the parameter semantics, coordinate consequences, and concurrency model. Nothing required to call the tool correctly is missing, and the annotations confirm it is a write operation without contradiction.

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?

Although the schema already documents all 5 parameters, the description adds real semantic value: folder_id="" as the root signal, aspect ratio examples mapped to concrete canvas sizes, and the 'only fields you provide are changed' partial-update contract. This goes well beyond the baseline schema coverage.

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?

The description opens with a specific verb and resource: 'Update a project's metadata: rename, change description, move to a different folder, or change aspect ratio.' This clearly scopes the tool against siblings like create_project, duplicate_project, and update_elements.

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 gives clear context on when to use the tool and how to behave: only provided fields change, folder_id="" moves to root, and actions must be serialized because it's a whole-project mutation. It explicitly warns against running it in parallel with other mutations on the same project_id, which is strong when-not guidance.

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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