# Send Briefing Room to your agent
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
## Fast path
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
## Suggested prompts
### New install

```text
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete.
```
### Upgrade existing

```text
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run.
```
## Machine-readable fields
```json
{
  "schemaVersion": "1.0",
  "item": {
    "slug": "briefing-room",
    "name": "Briefing Room",
    "source": "tencent",
    "type": "skill",
    "category": "内容创作",
    "sourceUrl": "https://clawhub.ai/matusvojtek/briefing-room",
    "canonicalUrl": "https://clawhub.ai/matusvojtek/briefing-room",
    "targetPlatform": "OpenClaw"
  },
  "install": {
    "downloadUrl": "/downloads/briefing-room",
    "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=briefing-room",
    "sourcePlatform": "tencent",
    "targetPlatform": "OpenClaw",
    "packageFormat": "ZIP package",
    "primaryDoc": "SKILL.md",
    "includedAssets": [
      "CHANGELOG.md",
      "README.md",
      "SKILL.md",
      "scripts/briefing.sh",
      "scripts/config.py"
    ],
    "downloadMode": "redirect",
    "sourceHealth": {
      "source": "tencent",
      "status": "healthy",
      "reason": "direct_download_ok",
      "recommendedAction": "download",
      "checkedAt": "2026-04-23T16:43:11.935Z",
      "expiresAt": "2026-04-30T16:43:11.935Z",
      "httpStatus": 200,
      "finalUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=4claw-imageboard",
      "contentType": "application/zip",
      "probeMethod": "head",
      "details": {
        "probeUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=4claw-imageboard",
        "contentDisposition": "attachment; filename=\"4claw-imageboard-1.0.1.zip\"",
        "redirectLocation": null,
        "bodySnippet": null
      },
      "scope": "source",
      "summary": "Source download looks usable.",
      "detail": "Yavira can redirect you to the upstream package for this source.",
      "primaryActionLabel": "Download for OpenClaw",
      "primaryActionHref": "/downloads/briefing-room"
    },
    "validation": {
      "installChecklist": [
        "Use the Yavira download entry.",
        "Review SKILL.md after the package is downloaded.",
        "Confirm the extracted package contains the expected setup assets."
      ],
      "postInstallChecks": [
        "Confirm the extracted package includes the expected docs or setup files.",
        "Validate the skill or prompts are available in your target agent workspace.",
        "Capture any manual follow-up steps the agent could not complete."
      ]
    }
  },
  "links": {
    "detailUrl": "https://openagent3.xyz/skills/briefing-room",
    "downloadUrl": "https://openagent3.xyz/downloads/briefing-room",
    "agentUrl": "https://openagent3.xyz/skills/briefing-room/agent",
    "manifestUrl": "https://openagent3.xyz/skills/briefing-room/agent.json",
    "briefUrl": "https://openagent3.xyz/skills/briefing-room/agent.md"
  }
}
```
## Documentation

### 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"):

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

KeyDefaultDescriptionlocation.cityBratislavaCity name for weather + local newslocation.latitude48.15Weather API latitudelocation.longitude17.11Weather API longitudelocation.timezoneEurope/BratislavaTimezone for weather APIlanguageenDefault briefing languageoutput.folder~/Documents/Briefing RoomOutput directoryaudio.enabledtrueGenerate audioaudio.formatmp3Audio format (mp3, wav, aiff)audio.tts_engineautoTTS engine (auto, mlx, kokoro, builtin)sectionsall 11 (see below)Which sections to includehost.name(empty = agent name)Radio host name for the briefingtrends.regionsunited-states,united-kingdom,X/Twitter trend regions (comma-separated, trailing comma = worldwide)webtrends.regionsUS,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.

### 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

Web Trends (from Google Trends RSS — what people are searching):

bash SKILL_DIR/scripts/briefing.sh webtrends

This fetches trending Google searches from US, UK, and Worldwide with:

Search term and approximate traffic volume
Top news headline explaining why it's trending
Use this data for the Web Trends section. The headlines already provide context — no extra searching needed for most items.

World News:

web_search("top world news today {date}", count=8)
web_search("breaking news today", count=5)

Politics:

web_search("US politics news today {date}", count=5)
web_search("EU politics news today {date}", count=5)
web_search("geopolitics news today", count=5)

⚠️ Source diversity: All sources have bias. For balanced reporting:

Search the same story with different framing
Present what happened factually, note what each side says
Don't adopt any outlet's framing as truth
Stick to verifiable facts: numbers, dates, quotes, actions

Tech & AI:

web_search("tech news today {date}", count=5)
web_search("AI artificial intelligence news today {date}", count=5)

Local news (based on configured city):

web_search("$CITY news today {date}", count=5)

Also search in the configured language if not English:

web_search("$CITY [news today] in $LANG {date}", count=5)

Examples:

Slovak: "Bratislava správy dnes"
German: "Wien Nachrichten heute"
Czech: "Praha zprávy dnes"

Sports:

web_search("sports news today {date}", count=5)
web_search("football soccer results today", count=5)

### Step 3: Gather Data — Markets & Crypto (APIs + Search)

# Or use helper:
bash SKILL_DIR/scripts/briefing.sh crypto

curl -s "https://api.coinbase.com/v2/prices/BTC-USD/spot"
curl -s "https://api.coinbase.com/v2/prices/ETH-USD/spot"
curl -s "https://api.coinbase.com/v2/prices/SOL-USD/spot"
curl -s "https://api.coinbase.com/v2/prices/XRP-USD/spot"

web_search("S&P 500 Dow Jones Nasdaq today {date}", count=5)
web_search("stock market today movers {date}", count=5)
web_search("gold price silver price today", count=3)
web_search("crypto market today {date}", count=5)

### Step 4: Compose the Briefing Script

Write as a conversational radio-host monologue.

Style guidelines:

Write like a smart, engaging radio host — NOT a list of headlines
Use the host name — introduce yourself: "Good morning, I'm [host name], and this is your Briefing Room for [date]..."
Sprinkle the name naturally throughout (sign-off, transitions) — don't overdo it
Do NOT start markdown with a # Title header — pandoc adds title from metadata
Connect stories with transitions
Add context: "here's why this matters"
Stay neutral and balanced — report facts, present sides, let listener decide
Target ~2,500-3,500 words for ~10 minutes
No emojis in the script (break TTS)
Write out numbers/abbreviations for TTS:

"$96,500" → "ninety-six thousand five hundred dollars"
"S&P 500" → "S and P 500"
"BTC" → "Bitcoin"
"°C" → "degrees celsius"

If language is not English, write the entire script in that language.

Section order:

Opening — Date, quick teaser of top stories
Weather — Current + week outlook for configured city
Trending on X — What's hot on X/Twitter
Web Trends — What people are searching (Google Trends)
World — Top 3-5 global stories
Politics — US, EU, geopolitics
Tech & AI — Launches, breakthroughs
Local — News for configured city/country
Sports — Headlines, results
Markets — S&P 500, Dow, Nasdaq, movers
Crypto & Commodities — BTC, ETH, alts, gold, silver
This Day in History — 1-2 interesting events that happened on this date
Closing — Wrap-up, sign-off

This Day in History: No research needed — use your own knowledge. Pick 1-2 interesting, surprising, or fun events that happened on today's date. Mix it up: science, culture, politics, weird stuff. Keep it conversational: "And before I let you go — did you know that on this day in 1996..."

Only include sections from the configured sections list. Skip sections the user has removed.

Save as /tmp/briefing_draft_$TIMESTAMP.md (working file).

For the markdown, include:

Section headers with emojis: ## 🌤️ Weather, ## 🌍 World, ## 📜 This Day in History, etc.
Source links after key facts
Key data in bold

### Step 5: Generate DOCX

pandoc "/tmp/briefing_draft_$TIMESTAMP.md" \\
  -o "$OUTPUT_DIR/briefing-$TIMESTAMP.docx" \\
  --metadata title="Briefing Room - $DATE"

If pandoc is not available, skip DOCX and note it.

### Step 6: Generate Audio

Read the config to determine TTS engine and voice for the current language.

MLX-Audio (English, or if configured for language):

python3 SKILL_DIR/scripts/config.py get voices.$LANG.engine
# → if "mlx":

import os, re, glob, json, subprocess
from datetime import datetime

timestamp = datetime.now().strftime("%Y-%m-%d-%H%M")  # must match TIMESTAMP from Step 0

# Read config
config_path = os.path.expanduser("~/.briefing-room/config.json")
with open(config_path) as f:
    config = json.load(f)

lang = config.get("language", "en")
voices = config.get("voices", {})
voice_cfg = voices.get(lang, voices.get("en", {}))

# Read and strip markdown from draft
with open(f"/tmp/briefing_draft_{timestamp}.md", "r") as f:
    text = f.read()
text = re.sub(r'#+ ', '', text)
text = re.sub(r'\\*\\*([^*]+)\\*\\*', r'\\1', text)
text = re.sub(r'\\*([^*]+)\\*', r'\\1', text)
text = re.sub(r'\\[([^\\]]+)\\]\\([^)]+\\)', r'\\1', text)
text = re.sub(r'---+', '', text)
text = re.sub(r'\\n{3,}', '\\n\\n', text)

# Resolve voice
blend = voice_cfg.get("mlx_voice_blend")
voice = voice_cfg.get("mlx_voice", "af_heart")
if blend:
    model = config.get("mlx_audio", {}).get("model", "mlx-community/Kokoro-82M-bf16")
    model_slug = model.replace("/", "--")
    cache_dir = os.path.expanduser(f"~/.cache/huggingface/hub/models--{model_slug}")
    parts = []
    for v, w in sorted(blend.items(), key=lambda x: -x[1]):
        parts.append(f"{v}_{int(w * 100)}")
    blend_name = "_".join(parts) + ".safetensors"
    matches = glob.glob(os.path.join(cache_dir, "snapshots/*/voices", blend_name))
    if matches:
        voice = matches[0]

speed = voice_cfg.get("speed", 1.05)
lang_code = config.get("mlx_audio", {}).get("lang_code", "a")

# Find MLX-Audio
mlx_path = config.get("mlx_audio", {}).get("path", "")
if not mlx_path:
    for p in ["~/.openclaw/tools/mlx-audio", "~/.local/share/mlx-audio"]:
        ep = os.path.expanduser(p)
        if os.path.exists(os.path.join(ep, ".venv/bin/python3")):
            mlx_path = ep
            break

# Generate via subprocess (uses MLX-Audio's venv)
python_bin = os.path.join(mlx_path, ".venv/bin/python3")
# ... generate_audio call with resolved voice, speed, lang_code

Built-in Apple TTS (any language):

If there's no voice configured for the language, auto-detect one:

# Try to get configured voice, fall back to auto-detect
VOICE=$(python3 SKILL_DIR/scripts/config.py get voices.$LANG.builtin_voice)
if [ "$VOICE" = "None" ] || [ -z "$VOICE" ]; then
    # Auto-detect: match locale (e.g. sk_SK, de_DE, fr_FR)
    # Prefer Enhanced/Premium voices, fall back to any
    VOICE=$(say -v '?' | grep "${LANG}_" \\
      | grep -i "Enhanced\\|Premium" | head -1 \\
      | sed 's/ *[a-z][a-z]_[A-Z][A-Z].*//' | xargs)
    [ -z "$VOICE" ] && VOICE=$(say -v '?' \\
      | grep "${LANG}_" | head -1 \\
      | sed 's/ *[a-z][a-z]_[A-Z][A-Z].*//' | xargs)
fi
RATE=$(python3 SKILL_DIR/scripts/config.py get voices.$LANG.builtin_rate)
# Strip markdown for TTS
DRAFT="/tmp/briefing_draft_$TIMESTAMP.md"
TTS_TXT="/tmp/briefing_tts_$TIMESTAMP.txt"
sed -E 's/#+//g; s/\\*+//g; s/\\[([^]]*)\\]\\([^)]*\\)/\\1/g' \\
  "$DRAFT" > "$TTS_TXT"
say -v "$VOICE" ${RATE:+-r $RATE} \\
  -o "$OUTPUT_DIR/briefing-$TIMESTAMP.aiff" \\
  -f "$TTS_TXT"
rm -f "/tmp/briefing_tts_$TIMESTAMP.txt"

Kokoro PyTorch (fallback):

Similar to MLX but uses PyTorch backend. See TubeScribe skill for Kokoro usage patterns.

### Step 6b: Convert to MP3

# Find the raw audio file (MLX outputs .wav, Apple TTS outputs .aiff)
RAW=""
for ext in wav aiff; do
    if [ -f "$OUTPUT_DIR/briefing-$TIMESTAMP.$ext" ]; then
        RAW="$OUTPUT_DIR/briefing-$TIMESTAMP.$ext"
        break
    fi
done

if [ -n "$RAW" ]; then
    ffmpeg -y \\
      -i "$RAW" \\
      -codec:a libmp3lame -qscale:a 2 \\
      "$OUTPUT_DIR/briefing-$TIMESTAMP.mp3"
    if [ -s "$OUTPUT_DIR/briefing-$TIMESTAMP.mp3" ]; then
        rm "$RAW"
    fi
fi

### Step 6c: Cleanup

rm -f "/tmp/briefing_draft_$TIMESTAMP.md"

### Step 7: Open Output Folder

open "$OUTPUT_DIR"

Do NOT auto-play. Briefings are long and need playback controls.

### Step 8: Report

Report back with:

Date and language of briefing
Sections covered
Top 3-4 headlines
Audio duration
File locations

### Helper Script

bash SKILL_DIR/scripts/briefing.sh setup     # Check dependencies + config
bash SKILL_DIR/scripts/briefing.sh weather    # Fetch weather (uses config location)
bash SKILL_DIR/scripts/briefing.sh trends     # Fetch X/Twitter trends (US + UK + Worldwide)
bash SKILL_DIR/scripts/briefing.sh webtrends  # Fetch Google Trends (US + UK + Worldwide)
bash SKILL_DIR/scripts/briefing.sh crypto     # Fetch crypto prices
bash SKILL_DIR/scripts/briefing.sh open       # Open today's folder
bash SKILL_DIR/scripts/briefing.sh list       # List all briefings
bash SKILL_DIR/scripts/briefing.sh clean      # Remove briefings >30 days old
bash SKILL_DIR/scripts/briefing.sh config     # Show raw config JSON

### Tips

Full pipeline takes 3-5 minutes (research + composition + TTS)
For shorter briefing, say "quick briefing" — cover top 3 sections only
If markets are closed (weekend/holiday), note it and skip detailed data
The agent IS the intelligence — read search results, compose the script, decide what matters
Users can add new languages by adding a voices entry + installing the voice via say -v '?'

### Dependencies

Required:

curl — API calls (built into macOS)
web_search tool — News research (OpenClaw built-in)

Recommended:

MLX-Audio Kokoro — fast English TTS
pandoc — DOCX generation: brew install pandoc
ffmpeg — MP3 conversion: brew install ffmpeg

Built-in (macOS):

Apple say — multilingual TTS (always available as fallback)

### Error Handling

IssueActionNo config fileRun python3 SKILL_DIR/scripts/config.py initAPI timeoutRetry once, skip that source, note itWeb search emptyTry alternative query, note gapsTTS failsFall back to Apple say (always available)Pandoc not foundSkip DOCX, deliver MP3 onlyNo internetCannot generate — inform user
## Trust
- Source: tencent
- Verification: Indexed source record
- Publisher: matusvojtek
- Version: 1.0.3
## Source health
- Status: healthy
- Source download looks usable.
- Yavira can redirect you to the upstream package for this source.
- Health scope: source
- Reason: direct_download_ok
- Checked at: 2026-04-23T16:43:11.935Z
- Expires at: 2026-04-30T16:43:11.935Z
- Recommended action: Download for OpenClaw
## Links
- [Detail page](https://openagent3.xyz/skills/briefing-room)
- [Send to Agent page](https://openagent3.xyz/skills/briefing-room/agent)
- [JSON manifest](https://openagent3.xyz/skills/briefing-room/agent.json)
- [Markdown brief](https://openagent3.xyz/skills/briefing-room/agent.md)
- [Download page](https://openagent3.xyz/downloads/briefing-room)