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reka-ai

Reka Vision MCP Server

Official
by reka-ai

summarize_video

Read-onlyIdempotent

Get a compact video overview with metadata, indexed features, transcript preview, and scene count to decide which analysis tools to call next.

Instructions

Start here. Get a compact overview of a video: metadata, which features are indexed, a transcript preview, and scene count. Use this to decide which tools to call next — then use segment_video to detect specific objects in time ranges of interest.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
video_idYes
rationaleNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.10

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already provide readOnlyHint and idempotentHint, so the safety profile is clear. The description adds behavioral context about what the overview contains (metadata, indexed features, transcript preview, scene count) and signals it is a low-risk, high-level inspection step. No contradiction with annotations.

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?

Three sentences with no filler. The most actionable guidance ('Start here') is front-loaded, followed by a clear list of outputs and a pointer to the next tool. Every sentence earns its place.

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?

With an output schema present, return values are already defined, so the description only needs to provide entry-point context, content summary, and routing—all of which are present. The tool's role within the larger workflow is fully specified.

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%, and the description provides no parameter-level detail. It implies video_id refers to the video being summarized, but the optional rationale parameter is completely unexplained, leaving a gap for the agent. Some credit for resource context, but it does not compensate for the lack of 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?

States a specific verb ('Get a compact overview') and enumerates the resource contents (metadata, indexed features, transcript preview, scene count), clearly distinguishing it from siblings like get_video or get_transcript. The phrase 'Start here' also establishes its unique entry-point role.

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?

Explicitly positions the tool as the first step ('Start here') and tells the agent to use it to decide which tools to call next. It also names the next appropriate sibling, segment_video, for detecting specific objects, leaving no doubt about when to use this tool versus alternatives.

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