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wefi-ai

eKYC Suite MCP Server

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by wefi-ai

video_liveness_detect

Analyzes face videos to detect liveness and identify spoofing attacks such as deepfakes and replays, ensuring genuine identity verification.

Instructions

Detect whether a face video is genuine or a replay/deepfake/synthetic attack. Includes retry handling for transient upstream busy responses. Best for higher-risk eKYC, remote onboarding, transaction step-up, and Know Your Agent human-binding gates. Video limit: max 20MB; upstream recommends short clips <=20s.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fileYesFace video: local file path, HTTPS URL, data URL, or base64. Max 20MB.
Behavior3/5

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

No annotations provided, so description carries full burden. It mentions retry handling and file limits but does not disclose authorization needs, return value format, or side effects.

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 sentences with no wasted words. The purpose is front-loaded, followed by key behavioral info and limits.

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?

The description covers purpose, use cases, retry, and limits. It does not describe the output format, but since there is no output schema, the description is reasonably complete for a detection tool.

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%, so baseline is 3. The description adds useful constraints (max 20MB, recommended clip length) that are not in the schema, enhancing understanding.

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 clearly states it detects whether a face video is genuine or an attack, with a specific verb and resource. It distinguishes from siblings like photo_liveness_detect by focusing on video.

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 description provides example use cases (eKYC, onboarding) but lacks explicit guidance on when not to use or which sibling tool to choose instead (e.g., photo vs video).

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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