# Halowerk VTuber Rigging Weight Smoother

> Halowerk VTuber Rigging Weight Smoother is a paid API for AI agents from creator.halowerk.com, paid per call via x402, $0.004/call, status unknown (last checked 2026-09-15).

Validates frame/channel dimensions, clamps blend-shape weights to 0–1, and applies exponential temporal smoothing across named animation channels over a sequence of timestamped frames.

## Facts

- Endpoint: POST https://creator.halowerk.com/v1/vtuber-rigging
- Price: $0.004/call
- Payment: x402
- Status: unknown
- Last checked: 2026-09-15
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/halowerk-vtuber-rigging-weight-smoother-2193c64c
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_TyaFS9YHnybMg3Da5Nj-N

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability halowerk-vtuber-rigging-weight-smoother-2193c64c -d '<json body>'
```

Example prompt: I have 200 frames of raw face-tracking blend shape data across 52 channels like 'eyeBlinkLeft' and 'mouthOpen' — can you clamp all the weights and apply exponential smoothing with an alpha of 0.3 to reduce jitter before I send them to the rigging pipeline?

## When to prefer this

Choose this endpoint when you need a lightweight, deterministic operation to clamp and temporally smooth blend-shape or morph-target weight arrays for VTuber or virtual avatar animation — especially when raw face-tracking output is noisy or out of range. It is not a substitute for full rigging, skeleton retargeting, face inference, or video processing tools.

## Known failure modes

- Mismatched frames vs channels array lengths cause validation errors
- Weight array length per frame not matching channels count
- Timestamp values out of 0–1,000,000,000,000 ms range
- More than 5000 frames or 256 channels triggers size limit rejection
- smoothing_alpha outside 0–1 range returns schema validation error
- Empty frames or channels arrays are rejected

## How this service works

Validates frame/channel dimensions, clamps weights to 0–1 and applies exponential smoothing over time in each named channel. It does not infer a face, build a rig, retarget skeletons, process video or replace animator review.

## Output

Returns per-frame, per-channel smoothed weight values after clamping raw inputs to the 0–1 range and applying exponential moving average smoothing controlled by the smoothing_alpha parameter. The output reflects temporally coherent animation weights suitable for downstream rigging or rendering pipelines.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "frames": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "timestamp_ms",
     "weights"
    ],
    "properties": {
     "weights": {
      "type": "array",
      "items": {
       "type": "number",
       "maximum": 10,
       "minimum": -10
      },
      "maxItems": 256,
      "minItems": 1
     },
     "timestamp_ms": {
      "type": "number",
      "maximum": 1000000000000,
      "minimum": 0
     }
    },
    "additionalProperties": false
   },
   "maxItems": 5000,
   "minItems": 1
  },
  "channels": {
   "type": "array",
   "items": {
    "type": "string",
    "maxLength": 64,
    "minLength": 1
   },
   "maxItems": 256,
   "minItems": 1,
   "uniqueItems": true
  },
  "smoothing_alpha": {
   "type": "number",
   "maximum": 1,
   "minimum": 0,
   "description": "Weight of the current clamped frame; 1 means no temporal smoothing."
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/halowerk-vtuber-rigging-weight-smoother-2193c64c/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from creator.halowerk.com](https://www.zero.xyz/host/creator.halowerk.com/llms.txt)