--- name: Briefing Room description: "Daily news briefing generator — produces a conversational radio-host-style audio briefing + DOCX document covering weather, X/Twitter trends, web trends, world news, politics, tech, local news, sports, markets, and crypto. macOS only (uses Apple TTS and afplay). Use when user asks for a news briefing, morning briefing, daily update, or similar." metadata: { "openclaw": { "emoji": "📻", "requires": { "bins": ["curl"] } } } ---

Briefing Room 📻

Your personal daily news briefing — audio + document.

On demand, research and compose a comprehensive ~10 minute news briefing in a conversational radio-host style. Output: audio file (MP3) + formatted document (DOCX).

💸 100% Free

• No subscriptions, API keys, or paid services
• Uses free public APIs (Open-Meteo weather, Coinbase prices, Google Trends RSS), web search, and local TTS
• TTS is fully local, no keys needed: MLX-Audio Kokoro (English) or Apple say (any language)
• Reads/writes: ~/.briefing-room/config.json (settings) and ~/Documents/Briefing Room/ (output)

First-Run Setup

On first use, check if ~/.briefing-room/config.json exists. If not, run:

python3 SKILL_DIR/scripts/config.py init

This creates default config. The user can customize:

• Location — city, latitude, longitude, timezone (for weather)
• Language — en, sk, de, etc.
• Voices — per-language TTS engine and voice selection
• Sections — which news sections to include
• Output folder — where briefings are saved

Show setup status:

python3 SKILL_DIR/scripts/config.py status

Quick Start

When user asks for a briefing (e.g. "give me a briefing", "morning update", "what's happening today"):

1. Check config exists (run setup if not)
2. Play notification sound: afplay /System/Library/Sounds/Blow.aiff &
3. Spawn a sub-agent with the full pipeline task immediately
4. Reply: "📻 Briefing Room is firing up — gathering today's news. I'll ping you when it's ready!"
5. DO NOT BLOCK — spawn and move on instantly

Language override: If user says "po slovensky", "v slovenčine", "auf deutsch", "en français", etc. → pass that to the sub-agent. Otherwise use the configured default language. Any language macOS supports will work — the agent writes the script in that language and TTS auto-detects a matching voice.

Spawn Command

sessions_spawn(
  task="<full pipeline instructions — see below>",
  label="briefing-room",
  runTimeoutSeconds=600,
  cleanup="delete"
)

The task message should include ALL the pipeline steps below so the sub-agent is fully self-contained. Replace all SKILL_DIR references with the actual absolute path to this skill's directory.

Host name: Read host.name from config. If empty, use your own agent name (from your identity). Pass it to the sub-agent as the radio host name (e.g. "Good morning, I'm Jackie, and this is your Briefing Room...").

Configuration

Config file: ~/.briefing-room/config.json

Read values:

python3 SKILL_DIR/scripts/config.py get location.city
python3 SKILL_DIR/scripts/config.py get language
python3 SKILL_DIR/scripts/config.py get voices.en.mlx_voice

Set values:

python3 SKILL_DIR/scripts/config.py set location.city "Vienna"
python3 SKILL_DIR/scripts/config.py set location.latitude 48.21
python3 SKILL_DIR/scripts/config.py set location.longitude 16.37
python3 SKILL_DIR/scripts/config.py set language "de"

Key Config Options

| Key | Default | Description | |-----|---------|-------------| | location.city | Bratislava | City name for weather + local news | | location.latitude | 48.15 | Weather API latitude | | location.longitude | 17.11 | Weather API longitude | | location.timezone | Europe/Bratislava | Timezone for weather API | | language | en | Default briefing language | | output.folder | ~/Documents/Briefing Room | Output directory | | audio.enabled | true | Generate audio | | audio.format | mp3 | Audio format (mp3, wav, aiff) | | audio.tts_engine | auto | TTS engine (auto, mlx, kokoro, builtin) | | sections | all 11 (see below) | Which sections to include | | host.name | (empty = agent name) | Radio host name for the briefing | | trends.regions | united-states,united-kingdom, | X/Twitter trend regions (comma-separated, trailing comma = worldwide) | | webtrends.regions | US,GB, | Google Trends regions (ISO codes, trailing comma = worldwide) |

Voice Configuration Per Language

Each language can have its own TTS engine and voice:

{
  "voices": {
    "en": {
      "engine": "mlx",
      "mlx_voice": "af_heart",
      "mlx_voice_blend": {"af_heart": 0.6, "af_sky": 0.4},
      "builtin_voice": "Samantha",
      "speed": 1.05
    },
    "sk": {
      "engine": "builtin",
      "builtin_voice": "Laura (Enhanced)",
      "builtin_rate": 220
    },
    "de": {
      "engine": "builtin",
      "builtin_voice": "Petra (Premium)",
      "builtin_rate": 200
    }
  }
}

Engine priority (when auto):

• English: mlx → kokoro → builtin
• Other languages: builtin (Apple TTS has good multilingual voices)

Users can add any language by adding a voices entry + a matching builtin_voice from say -v '?'.

Output Structure

~/Documents/Briefing Room/YYYY-MM-DD/
├── briefing-YYYY-MM-DD-HHMM.docx    # Formatted document
└── briefing-YYYY-MM-DD-HHMM.mp3     # Audio briefing (~10 min)

Do NOT save the .md working file in the output folder. Use /tmp/ for working files, delete after.

Full Pipeline

Step 0: Setup

# Read config
CITY=$(python3 SKILL_DIR/scripts/config.py get location.city)
LAT=$(python3 SKILL_DIR/scripts/config.py get location.latitude)
LON=$(python3 SKILL_DIR/scripts/config.py get location.longitude)
TZ=$(python3 SKILL_DIR/scripts/config.py get location.timezone)
LANG=$(python3 SKILL_DIR/scripts/config.py get language)
OUTPUT_FOLDER=$(python3 SKILL_DIR/scripts/config.py get output.folder)

DATE=$(date +%Y-%m-%d)
TIMESTAMP=$(date +%Y-%m-%d-%H%M)
OUTPUT_DIR="$OUTPUT_FOLDER/$DATE"
mkdir -p "$OUTPUT_DIR"

Step 1: Gather Data — Weather

Use the configured location coordinates:

# Current weather
TZ_ENC="${TZ/\//%2F}"
BASE="https://api.open-meteo.com/v1/forecast"
CURRENT="temperature_2m,relative_humidity_2m"
CURRENT="$CURRENT,apparent_temperature,precipitation"
CURRENT="$CURRENT,weather_code,wind_speed_10m"
curl -s "$BASE?latitude=$LAT&longitude=$LON\
&current=$CURRENT&timezone=$TZ_ENC"

# 7-day forecast
DAILY="temperature_2m_max,temperature_2m_min"
DAILY="$DAILY,precipitation_sum,weather_code"
curl -s "$BASE?latitude=$LAT&longitude=$LON\
&daily=$DAILY&timezone=$TZ_ENC"

Or use the helper: bash SKILL_DIR/scripts/briefing.sh weather

Map weather_code to descriptions:

• 0: Clear sky ☀️
• 1-3: Partly cloudy ⛅
• 45-48: Fog 🌫️
• 51-55: Drizzle 🌦️
• 61-65: Rain 🌧️
• 71-75: Snow ❄️
• 80-82: Rain showers 🌦️
• 95-99: Thunderstorm ⛈️

Step 2: Gather Data — News (Web Search)

Use web_search tool for each section. Add current date to queries for freshness. Use the configured $CITY for local news.

X/Twitter Trends (from getdaytrends.com — real-time, no API key):

bash SKILL_DIR/scripts/briefing.sh trends

This fetches top 25 trends from US, UK, and Worldwide. Use the output to:

• Identify the most interesting/newsworthy trends (skip generic ones like "Good Tuesday", "Taco Tuesday")
• Filter out non-Latin script trends unless they're globally significant
• Pick ~5-10 trends that overlap across regions or seem newsworthy
• Use web_search to get context on the top trends you selected

...