# Raw Fpv Visual Labeler

> Label visible cleanup-relevant movable objects from grouped RAW-FPV frames without creating executable cleanup handles.

- **Type:** Skill
- **Install:** `agentstack add skill-miaodx-roboclaws-raw-fpv-visual-labeler`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [MiaoDX](https://agentstack.voostack.com/s/miaodx)
- **Installs:** 0
- **Category:** [Agent Skills](https://agentstack.voostack.com/c/agent-skills)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [MiaoDX](https://github.com/MiaoDX)
- **Source:** https://github.com/MiaoDX/roboclaws/tree/main/skills/raw-fpv-visual-labeler

## Install

```sh
agentstack add skill-miaodx-roboclaws-raw-fpv-visual-labeler
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# RAW-FPV Visual Labeler

Use this skill only for perception-only RAW-FPV labeling probes. It consumes
public robot FPV frame evidence and emits structured visual labels for review
and offline scoring. It does not call cleanup tools, does not create
`observed_*` handles, and does not authorize navigation, pick, place, or `done`.

## Inputs

Use 3-6 neighboring RAW-FPV frames from the same waypoint, sweep segment, or
source observation neighborhood when available. Each frame may include only:

- public frame id;
- image artifact;
- public waypoint or room context already visible to the cleanup agent;
- optional public runtime-map planning hints marked non-executable.

Never include private labels, generated hidden target ids, acceptable
destination truth, executable observed-object handles, detector candidates, or
camera-label producer candidates.

## Output

Return strict JSON:

```json
{
  "schema": "raw_fpv_visual_labeler_response_v1",
  "labels": [
    {
      "evidence_frame_id": "run/raw_fpv_001",
      "category": "mug",
      "category_family": "dish",
      "coarse_region": "middle_right",
      "confidence": 0.82,
      "is_cleanup_relevant": true,
      "bbox": [0.62, 0.5, 0.12, 0.15],
      "surface_hint": "table",
      "reason_not_actionable": ""
    }
  ]
}
```

Required per label:

- `evidence_frame_id`
- `category`
- `category_family`
- `coarse_region`
- `confidence`
- `is_cleanup_relevant`

Optional per label:

- `bbox`
- `surface_hint`
- `reason_not_actionable`

Allowed category families are `food`, `dish`, `book`, `linen`, `toy`, and
`electronics`. Fixtures and surfaces such as tables, beds, counters, shelves,
sinks, cabinets, and floors may be mentioned only as `surface_hint` or as
`is_cleanup_relevant=false`; they are not object hits.

## Boundary

These labels are perception evidence. The cleanup agent must not consume them
as executable handles in `camera-raw-fpv`. A later assisted RAW-FPV or
`camera-grounded-labels` producer decision would need its own contract change.

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [MiaoDX](https://github.com/MiaoDX)
- **Source:** [MiaoDX/roboclaws](https://github.com/MiaoDX/roboclaws)
- **License:** MIT

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-miaodx-roboclaws-raw-fpv-visual-labeler
- Seller: https://agentstack.voostack.com/s/miaodx
- Browse the marketplace: https://agentstack.voostack.com/browse

---
Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.