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reka-ai

Reka Vision MCP Server

Official
by reka-ai

get_feature_catalog

Read-onlyIdempotent

Discover available video analysis features and their dependencies to select the right pipeline for indexing videos.

Instructions

List available video analysis features with their dependencies and descriptions. Use this to understand what features exist and what pipelines to use with index_video.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rationaleNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.10

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already mark the tool read-only and idempotent, and the description's 'List' wording is consistent with that. The description adds useful context beyond the annotations by promising that catalog entries include dependencies and descriptions and by positioning the call as a step before using index_video. No operational hazards exist to disclose for this safe catalog endpoint.

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 tight sentences with no filler or tautology. The first sentence states what the tool does; the second states why and how to use it. Every sentence earns its place.

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?

For a simple, safe, read-only catalog endpoint with an output schema, the description covers the goal, the content of the catalog, and the connection to index_video. The only weakness is the unexplained rationale parameter, but it is optional and likely nonbehavioral, so the overall context is nearly complete.

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

Parameters1/5

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

Schema description coverage is 0%, and the only parameter, rationale, is not explained anywhere in the description. Since the description must compensate when parameter coverage is low, and it does not address the parameter at all, the description adds no semantic value for calling it correctly. The rationale parameter's role in the request remains unclear.

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 uses a specific verb ('List') and resource ('available video analysis features'), and further specifies that output includes dependencies and descriptions. It clearly distinguishes this catalog tool from sibling list operations like list_videos and list_groups. The tie to index_video makes the purpose concrete.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly says to use this tool to understand what features exist and which pipelines to use with index_video, providing clear context. It does not mention when not to use it or name alternative discovery tools, so it stops short of full exclusionary guidance.

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