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Reorder elements within a clip

reorder_elements

Reorder the elements inside a clip. List position IS the z-index — later entries in ordered_element_ids render on top of earlier ones.

You MUST pass the full set of element IDs currently in the clip. The handler rejects partial lists so a reorder can never silently drop an element. Get the current list via get_clip — the order it returns is exactly the order this takes.

Works on grouped clips. Elements keep their group; moving a group's members together moves the whole group relative to everything else. The one thing a group cannot do is render in two pieces, so an order that puts a non-member BETWEEN two members of the same group is rejected and names the group — put the group's elements next to each other, or take the element out of the group first with update_elements(group).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
clip_indexYesZero-based clip index.
project_idYesProject ID.
ordered_element_idsYesAll element IDs currently in the clip, in the new order. Position N = z-index N (later = on top).

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",
-  "clip_index",
-  "ordered_element_ids",
-  "context",
-  "llm_model"
-]New value: +[
+  "project_id",
+  "clip_index",
+  "ordered_element_ids"
+]
  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",
-  "clip_index",
-  "ordered_element_ids"
-]New value: +[
+  "project_id",
+  "clip_index",
+  "ordered_element_ids",
+  "context",
+  "llm_model"
+]
  3. Changed3 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
    • addedInput schema / properties / clip_index / maximum
      Added value: +9007199254740991
  4. First observed

TDQS

A4.9/5.0
Behavior5/5

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

The description discloses several important behaviors beyond annotations: the rejection of partial lists to prevent silent drops, the z-index rendering rule, grouped-clip behavior, and the specific rejection of orders that split a group with a non-member between its members. This gives an agent accurate expectations for validation and failure modes.

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 the essential z-index rule, followed by input requirements and group caveats. Every sentence carries meaningful operational information, and the structure guides the agent from general behavior to specific constraints without wasted words.

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 tool with three required parameters and no output schema, the description is complete: it explains what the tool does, how to source the required list, what order semantics are, and how the handler handles invalid or group-splitting inputs. No critical calling information is missing.

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%, and the ordered_element_ids schema already explains position and z-index. The description adds value by requiring the full current list, directing the agent to get_clip for the exact order, and explaining group-related constraints on the order. This is more than the baseline but not a large semantic leap beyond the 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?

The first sentence uses a specific verb and resource: 'Reorder the elements inside a clip,' and immediately defines the core semantic (list position is z-index, later entries render on top). This clearly distinguishes reorder_elements from siblings like add_elements, remove_elements, 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 explicit usage conditions: callers must pass the full set of element IDs currently in the clip, partial lists are rejected, and get_clip is named as the correct way to obtain the current order. It also names an alternative action, update_elements(group), for removing an element from a group before reordering.

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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