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BlockRunAI

BlockRun MCP

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blockrun_realface

Enroll a real person's face using a phone liveness check to create a RealFace asset for Seedance 2.0 video generation. Also supports direct virtual portraits for AI characters without liveness.

Instructions

Enroll a real person's face as a BytePlus RealFace asset, then drive Seedance 2.0 video with it (blockrun_video real_face_asset_id).

A RealFace asset (ta_xxxx) lets Seedance 2.0 / 2.0-fast generate video of a SPECIFIC real person — not a generic seed image. Enrollment is a multi-step flow because BytePlus requires a live phone liveness check (the real person nods + blinks on camera) before a face photo can be uploaded.

Actions:

  • init: FREE. Create an asset group + a phone H5 link. The tool renders the link as a QR code and opens it; the real person scans it on their phone and completes the ~1 min liveness check. Pass group_id to refresh an expired link.

  • status: FREE. Poll a group until status:"active" (ready_to_finalize:true). The H5 link is valid ~120s — re-init if it expires.

  • enroll: PAID ($0.01 USDC, Base only). After the group is active, upload a clear front-facing photo (image_url) of the SAME person. Returns the ta_xxxx asset id.

  • portrait: PAID ($0.01 USDC, Base only). Virtual Portrait — enroll an AI-GENERATED character from an image URL directly, NO liveness needed (one step: name + image_url → ta_xxxx). For fictional/AI characters only; for a real person use the init→status→enroll liveness flow.

  • list: FREE. List the RealFace + Virtual Portrait assets enrolled by this wallet (their ta_xxxx ids + names) so you can pick one for blockrun_video.

Typical flow:

  1. blockrun_realface action:"init" name:"Alice" → scan QR on phone, do liveness

  2. blockrun_realface action:"status" group_id:"legacy_rf_…" → repeat until ready_to_finalize:true

  3. blockrun_realface action:"enroll" name:"Alice" group_id:"legacy_rf_…" image_url:"https://…/alice.jpg" → ta_xxxx

  4. blockrun_video model:"bytedance/seedance-2.0" real_face_asset_id:"ta_xxxx" prompt:"…"

Privacy: BlockRun does not store face/liveness data — only the asset id, name, and the photo URL you supply.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoDisplay name for the person/character (required for init, enroll, and portrait).
actionYesWhat to do
agent_idNoAgent identifier for budget tracking and enforcement (enroll only).
group_idNoAsset-group id from init (required for status and enroll; pass to init to refresh an expired H5 link). Not used by portrait.
image_urlNoPublic HTTPS URL to a clear front-facing face image (JPG/PNG/WEBP, ≤10MB). Required for enroll and portrait.

Tool Definition Quality

A4.6/5.0
Behavior5/5

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

Given minimal annotations (only readOnlyHint:false), the description compensates fully. It details the multi-step liveness flow, the 120s H5 link validity, costs per action, and privacy policy. It does not contradict annotations.

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 well-organized into action list and example flow, but is slightly verbose. Every sentence earns its place for a complex tool, so it remains efficient.

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 the entire workflow, including privacy and costs. No output schema exists, but the returns are implied (e.g., asset ID for enroll, list outputs). It could explicitly state return structures for each action, but this is a minor gap given the complexity.

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

Parameters5/5

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

With 100% schema coverage, the baseline is 3. However, the description provides rich context: explaining each action's parameter requirements, the role of group_id in refreshing expired links, and that image_url must be public and ≤10MB. This adds significant value.

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 opens with a clear verb+resource statement: 'Enroll a real person's face as a BytePlus RealFace asset, then drive Seedance 2.0 video with it'. It distinctly defines the tool's role in the ecosystem and differentiates from sibling tools like blockrun_video by specifying the asset ID usage.

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 provides a typical flow and contrasts real-person enrollment with virtual portrait. It mentions when to use each action and references blockrun_video for downstream use. It could explicitly state when not to use, but the context is clear.

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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