Reel-E

Read the edit

get_edit_summary

Read-onlyIdempotent

The current edit as structured text: every shot in play order (photoId, room, what it shows, length, speed, movement, AI+), transitions, music (tempo, sections), opening title, text, stickers, branding, voiceover and credits left. Most edits start from the photoIds and positions it lists.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "listingId": "<listingId>"
    },
    "name": "get_edit_summary"
  }
}

Input Schema

Name	Required	Description	Default
`listingId`	Yes	Listing id from list_listings.

Output Schema

Name	Required	Description	Default
`status`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 9, 2026

TDQS

A3.5/5.0

Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false, and openWorldHint=false, so the safety profile is fully covered. The description adds that the output is the current edit, in play order, with a complete inventory, but contains no extra behavioral context such as latency, pagination, or state assumptions. With annotations carrying safety, this is adequate but not rich.

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?

The description is two sentences, front-loaded with 'The current edit as structured text', and the long content list earns its place by telling the agent what to expect. It is dense but not wasteful; the only minor weakness is the unexplained 'AI+' shorthand.

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?

This is a simple single-parameter read with rich annotations and an output schema, and the description covers the scope of the return well enough. The parameter source (list_listings) is documented in the schema, so no critical element is missing for correct invocation.

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

Parameters3/5

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

Schema description coverage is 100% and the single parameter's description points to list_listings, so the schema does the heavy lifting. The tool description does not mention listingId at all, adding no meaning beyond the structured field. Baseline 3 is appropriate.

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?

The description states a specific verb and resource: read the current edit as structured text, and enumerates what it contains (shots, transitions, music, title, text, stickers, branding, voiceover, credits). It is clear without opening the schema, but it does not name or contrast with siblings such as recent_changes or read_narration_script, so it misses the top score.

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?

The line 'Most edits start from the photoIds and positions it lists' implies this is a first-step read and hints at where the data is used, but there is no explicit when-to-use/when-not guidance or named alternative. Usage is inferable rather than stated.

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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