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feat: add dataset-management skill, update sam2-segmentation and skills.json
- New skill: skills/annotation/dataset-management/ with deploy scripts - Update sam2-segmentation SKILL.md - Update skills.json with new entries
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‎skills.json‎

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"capabilities": [
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"interactive_segmentation",
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"video_tracking"
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]
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},
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{
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"id": "annotation-data",
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"name": "Annotation Data",
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"description": "Dataset annotation management — COCO labels, sequences, export, and Kaggle upload for Annotation Studio.",
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"version": "1.0.0",
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"category": "annotation",
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"path": "skills/annotation/dataset-management",
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"tags": [
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"annotation",
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"dataset",
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"coco",
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"labeling"
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],
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"platforms": [
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"linux-x64",
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"linux-arm64",
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"darwin-arm64",
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"darwin-x64",
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"win-x64"
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],
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"requirements": {
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"python": ">=3.9"
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},
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"capabilities": [
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"dataset_management",
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"coco_export"
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],
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"ui_unlocks": [
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"annotation_studio"

‎skills/annotation/dataset-management/SKILL.md‎

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---
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name: annotation-data
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description: "Dataset annotation management — COCO labels, sequences, export, and Kaggle upload"
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version: 1.0.0
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entry: scripts/annotation_manager.py
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deploy: deploy.sh
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parameters:
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- name: datasets_dir
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label: "Datasets Directory"
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type: string
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default: ""
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description: "Root directory for annotation datasets (auto-detected if empty)"
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group: Storage
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capabilities:
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live_transform:
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script: scripts/annotation_manager.py
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description: "Dataset CRUD, annotation save/load, COCO export"
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ui_unlocks:
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- annotation_studio
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---
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# Annotation Data Management
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Manages annotation datasets for Aegis Annotation Studio. Handles dataset CRUD, label management, COCO-format export, and Kaggle upload.
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## Protocol (stdin/stdout JSONL)
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### Aegis → Skill
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```jsonl
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{"command": "list_datasets", "request_id": "req_001"}
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{"command": "get_dataset", "name": "my_dataset", "request_id": "req_002"}
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{"command": "save_dataset", "name": "my_dataset", "labels": [...], "request_id": "req_003"}
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{"command": "delete_dataset", "name": "my_dataset", "request_id": "req_004"}
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{"command": "save_annotation", "dataset": "my_dataset", "frame_id": "f1", "annotations": [...], "request_id": "req_005"}
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{"command": "list_labels", "dataset": "my_dataset", "request_id": "req_006"}
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{"command": "export_coco", "dataset": "my_dataset", "request_id": "req_007"}
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{"command": "get_stats", "dataset": "my_dataset", "request_id": "req_008"}
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{"command": "stop"}
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```
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### Skill → Aegis
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```jsonl
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{"event": "annotation", "type": "ready", "request_id": "", "data": {"version": "1.0.0"}}
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{"event": "annotation", "type": "datasets", "request_id": "req_001", "data": [...]}
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{"event": "annotation", "type": "dataset", "request_id": "req_002", "data": {...}}
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{"event": "annotation", "type": "saved", "request_id": "req_005", "data": {"frame_id": "f1", "count": 3}}
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{"event": "annotation", "type": "exported", "request_id": "req_007", "data": {"path": "/path/to/coco.json"}}
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```

‎skills/annotation/dataset-management/deploy.bat‎

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@echo off
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REM deploy.bat — Bootstrapper for Annotation Data Management Skill (Windows)
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REM Lightweight — no GPU needed, stdlib-only Python.
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setlocal enabledelayedexpansion
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set "SKILL_DIR=%~dp0"
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if "%SKILL_DIR:~-1%"=="\" set "SKILL_DIR=%SKILL_DIR:~0,-1%"
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set "VENV_DIR=%SKILL_DIR%\.venv"
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set "LOG_PREFIX=[annotation-data-deploy]"
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REM ─── Find Python ───────────────────────────────────────────────────────
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set "PYTHON_CMD="
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for %%V in (3.12 3.11 3.10 3.9) do (
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if not defined PYTHON_CMD (
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py -%%V --version >nul 2>&1
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if !errorlevel! equ 0 set "PYTHON_CMD=py -%%V"
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)
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)
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if not defined PYTHON_CMD (
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python3 --version >nul 2>&1
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if !errorlevel! equ 0 set "PYTHON_CMD=python3"
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)
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if not defined PYTHON_CMD (
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python --version >nul 2>&1
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if !errorlevel! equ 0 set "PYTHON_CMD=python"
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)
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if not defined PYTHON_CMD (
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echo %LOG_PREFIX% ERROR: No Python found>&2
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echo {"event": "error", "stage": "python", "message": "No Python found"}
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exit /b 1
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)
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for /f "tokens=*" %%A in ('!PYTHON_CMD! --version 2^>^&1') do set "PY_VERSION=%%A"
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echo %LOG_PREFIX% Using Python: %PYTHON_CMD% (%PY_VERSION%)>&2
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echo {"event": "progress", "stage": "python", "message": "Found %PY_VERSION%"}
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REM ─── Create venv ───────────────────────────────────────────────────────
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if not exist "%VENV_DIR%\Scripts\python.exe" (
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%PYTHON_CMD% -m venv "%VENV_DIR%"
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)
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echo {"event": "progress", "stage": "venv", "message": "Virtual environment ready"}
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REM ─── Verify ────────────────────────────────────────────────────────────
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"%VENV_DIR%\Scripts\python.exe" -c "import json, pathlib; print('Annotation data skill ready')" 2>&1
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echo {"event": "complete", "backend": "cpu", "message": "Annotation data skill installed"}
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echo %LOG_PREFIX% Done!>&2
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endlocal
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exit /b 0

‎skills/annotation/dataset-management/deploy.sh‎

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#!/usr/bin/env bash
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# deploy.sh — Bootstrapper for Annotation Data Management Skill
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# Lightweight — no GPU needed, stdlib-only Python.
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set -euo pipefail
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SKILL_DIR="$(cd "$(dirname "$0")" && pwd)"
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VENV_DIR="$SKILL_DIR/.venv"
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LOG_PREFIX="[annotation-data-deploy]"
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log() { echo "$LOG_PREFIX $*" >&2; }
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emit() { echo "$1"; }
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# ─── Find Python ──────────────────────────────────────────────────────────
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find_python() {
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for cmd in python3.12 python3.11 python3.10 python3.9 python3; do
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if command -v "$cmd" &>/dev/null; then
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local ver
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ver="$("$cmd" --version 2>&1 | grep -oE '[0-9]+\.[0-9]+')"
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local major minor
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major=$(echo "$ver" | cut -d. -f1)
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minor=$(echo "$ver" | cut -d. -f2)
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if [ "$major" -ge 3 ] && [ "$minor" -ge 9 ]; then
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echo "$cmd"
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return 0
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fi
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fi
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done
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return 1
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}
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PYTHON_CMD=$(find_python) || {
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log "ERROR: No Python >=3.9 found."
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emit '{"event": "error", "stage": "python", "message": "No Python >=3.9 found"}'
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exit 1
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}
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log "Using Python: $PYTHON_CMD ($($PYTHON_CMD --version 2>&1))"
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emit "{\"event\": \"progress\", \"stage\": \"python\", \"message\": \"Found $($PYTHON_CMD --version 2>&1)\"}"
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# ─── Create venv ──────────────────────────────────────────────────────────
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if [ ! -d "$VENV_DIR" ]; then
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"$PYTHON_CMD" -m venv "$VENV_DIR"
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fi
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emit '{"event": "progress", "stage": "venv", "message": "Virtual environment ready"}'
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# ─── Verify ───────────────────────────────────────────────────────────────
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"$VENV_DIR/bin/python" -c "import json, pathlib; print('Annotation data skill ready')" 2>&1 | while read -r line; do log "$line"; done
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emit '{"event": "complete", "backend": "cpu", "message": "Annotation data skill installed"}'
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log "Done!"

‎skills/annotation/dataset-management/requirements.txt‎

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# Annotation Data Management — minimal deps (stdlib only)
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# No external packages needed — all Python stdlib

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