Tech News Digest

Automated tech news digest system with unified data source model, quality scoring pipeline, and template-based output generation.

Quick Start

1. Configuration Setup: Default configs are in config/defaults/. Copy to workspace for customization:

   mkdir -p workspace/config
   cp config/defaults/sources.json workspace/config/
   cp config/defaults/topics.json workspace/config/
   

2. Environment Variables:

   • X_BEARER_TOKEN - Twitter API bearer token (optional)
   • BRAVE_API_KEY - Brave Search API key (optional)
   • GITHUB_TOKEN - GitHub personal access token (optional, improves rate limits)

3. Generate Digest:

   # Unified pipeline (recommended) — runs all 5 sources in parallel + merge
   python3 scripts/run-pipeline.py \
     --defaults config/defaults \
     --config workspace/config \
     --hours 48 --freshness pd \
     --archive-dir workspace/archive/tech-news-digest/ \
     --output /tmp/td-merged.json --verbose --force
   

4. Use Templates: Apply Discord, email, or markdown templates to merged output

Configuration Files

sources.json - Unified Data Sources

{
  "sources": [
    {
      "id": "openai-rss",
      "type": "rss",
      "name": "OpenAI Blog",
      "url": "https://openai.com/blog/rss.xml",
      "enabled": true,
      "priority": true,
      "topics": ["llm", "ai-agent"],
      "note": "Official OpenAI updates"
    },
    {
      "id": "sama-twitter",
      "type": "twitter", 
      "name": "Sam Altman",
      "handle": "sama",
      "enabled": true,
      "priority": true,
      "topics": ["llm", "frontier-tech"],
      "note": "OpenAI CEO"
    }
  ]
}

topics.json - Enhanced Topic Definitions

{
  "topics": [
    {
      "id": "llm",
      "emoji": "🧠",
      "label": "LLM / Large Models",
      "description": "Large Language Models, foundation models, breakthroughs",
      "search": {
        "queries": ["LLM latest news", "large language model breakthroughs"],
        "must_include": ["LLM", "large language model", "foundation model"],
        "exclude": ["tutorial", "beginner guide"]
      },
      "display": {
        "max_items": 8,
        "style": "detailed"
      }
    }
  ]
}

Scripts Pipeline

run-pipeline.py - Unified Pipeline (Recommended)

python3 scripts/run-pipeline.py \
  --defaults config/defaults [--config CONFIG_DIR] \
  --hours 48 --freshness pd \
  --archive-dir workspace/archive/tech-news-digest/ \
  --output /tmp/td-merged.json --verbose --force

• Features: Runs all 5 fetch steps in parallel, then merges + deduplicates + scores
• Output: Final merged JSON ready for report generation (~30s total)
• Metadata: Saves per-step timing and counts to *.meta.json
• GitHub Auth: Auto-generates GitHub App token if $GITHUB_TOKEN not set
• Fallback: If this fails, run individual scripts below

Individual Scripts (Fallback)

fetch-rss.py - RSS Feed Fetcher

python3 scripts/fetch-rss.py [--defaults DIR] [--config DIR] [--hours 48] [--output FILE] [--verbose]

• Parallel fetching (10 workers), retry with backoff, feedparser + regex fallback
• Timeout: 30s per feed, ETag/Last-Modified caching

fetch-twitter.py - Twitter/X KOL Monitor

python3 scripts/fetch-twitter.py [--defaults DIR] [--config DIR] [--hours 48] [--output FILE]

• Requires X_BEARER_TOKEN, rate limit handling, engagement metrics

fetch-web.py - Web Search Engine

python3 scripts/fetch-web.py [--defaults DIR] [--config DIR] [--freshness pd] [--output FILE]

• Auto-detects Brave API rate limit: paid plans → parallel queries, free → sequential
• Without API: generates search interface for agents

fetch-github.py - GitHub Releases Monitor

python3 scripts/fetch-github.py [--defaults DIR] [--config DIR] [--hours 168] [--output FILE]

• Parallel fetching (10 workers), 30s timeout
• Auth priority: $GITHUB_TOKEN → GitHub App auto-generate → gh CLI → unauthenticated (60 req/hr)

fetch-reddit.py - Reddit Posts Fetcher

python3 scripts/fetch-reddit.py [--defaults DIR] [--config DIR] [--hours 48] [--output FILE]

• Parallel fetching (4 workers), public JSON API (no auth required)
• 13 subreddits with score filtering

merge-sources.py - Quality Scoring & Deduplication

python3 scripts/merge-sources.py --rss FILE --twitter FILE --web FILE --github FILE --reddit FILE

• Quality scoring, title similarity dedup (85%), previous digest penalty
• Output: topic-grouped articles sorted by score

validate-config.py - Configuration Validator

python3 scripts/validate-config.py [--defaults DIR] [--config DIR] [--verbose]

• JSON schema validation, topic reference checks, duplicate ID detection

User Customization

Workspace Configuration Override

Place custom configs in workspace/config/ to override defaults:

• Sources: Append new sources, disable defaults with "enabled": false
• Topics: Override topic definitions, search queries, display settings
• Merge Logic:
  • Sources with same id → user version takes precedence
  • Sources with new id → appended to defaults
  • Topics with same id → user version completely replaces default

Example Workspace Override

// workspace/config/sources.json
{
  "sources": [
    {
      "id": "simonwillison-rss",
      "enabled": false,
      "note": "Disabled: too noisy for my use case"
    },
    {
      "id": "my-custom-blog", 
      "type": "rss",
      "name": "My Custom Tech Blog",
      "url": "https://myblog.com/rss",
      "enabled": true,
      "priority": true,
      "topics": ["frontier-tech"]
    }
  ]
}

Templates & Output

Discord Template (references/templates/discord.md)

• Bullet list format with link suppression (<link>)
• Mobile-optimized, emoji headers
• 2000 character limit awareness

Email Template (references/templates/email.md)

• Rich metadata, technical stats, archive links
• Executive summary, top articles section
• HTML-compatible formatting

Markdown Template (references/templates/markdown.md)

• GitHub-compatible tables and formatting
• Technical details section
• Expandable sections support

Default Sources (133 total)

• RSS Feeds (49): AI labs, tech blogs, crypto news, Chinese tech media
• Twitter/X KOLs (49): AI researchers, crypto leaders, tech executives
• GitHub Repos (22): Major open-source projects (LangChain, vLLM, DeepSeek, Llama, etc.)
• Reddit (13): r/MachineLearning, r/LocalLLaMA, r/CryptoCurrency, r/ChatGPT, r/OpenAI, etc.
• Web Search (4 topics): LLM, AI Agent, Crypto, Frontier Tech

All sources pre-configured with appropriate topic tags and priority levels.

Dependencies

pip install -r requirements.txt

Optional but Recommended:

• feedparser>=6.0.0 - Better RSS parsing (fallback to regex if unavailable)
• jsonschema>=4.0.0 - Configuration validation

All scripts work with Python 3.8+ standard library only.

Monitoring & Operations

Health Checks

# Validate configuration
python3 scripts/validate-config.py --verbose

# Test RSS feeds
python3 scripts/fetch-rss.py --hours 1 --verbose

# Check Twitter API
python3 scripts/fetch-twitter.py --hours 1 --verbose

Archive Management

• Digests automatically archived to <workspace>/archive/tech-news-digest/
• Previous digest titles used for duplicate detection
• Old archives cleaned automatically (90+ days)

Error Handling

• Network Failures: Retry with exponential backoff
• Rate Limits: Automatic retry with appropriate delays
• Invalid Content: Graceful degradation, detailed logging
• Configuration Errors: Schema validation with helpful messages

API Keys & Environment

Set in ~/.zshenv or similar:

export X_BEARER_TOKEN="your_twitter_bearer_token"
export BRAVE_API_KEY="your_brave_search_api_key"  # Optional

• Twitter: Read-only bearer token, pay-per-use pricing
• Brave Search: Optional, fallback to agent web_search if unavailable

Cron / Scheduled Task Integration

OpenClaw Cron (Recommended)

The cron prompt should NOT hardcode the pipeline steps. Instead, reference references/digest-prompt.md and only pass configuration parameters. This ensures the pipeline logic stays in the skill repo and is consistent across all installations.

Daily Digest Cron Prompt

Read <SKILL_DIR>/references/digest-prompt.md and follow the complete workflow to generate a daily digest.

Replace placeholders with:
- MODE = daily
- TIME_WINDOW = past 1-2 days
- FRESHNESS = pd
- RSS_HOURS = 48
- ITEMS_PER_SECTION = 3-5
- BLOG_PICKS_COUNT = 2-3
- EXTRA_SECTIONS = (none)
- SUBJECT = Daily Tech Digest - YYYY-MM-DD
- WORKSPACE = <your workspace path>
- SKILL_DIR = <your skill install path>
- DISCORD_CHANNEL_ID = <your channel id>
- EMAIL = (optional)
- LANGUAGE = English
- TEMPLATE = discord

Follow every step in the prompt template strictly. Do not skip any steps.

Weekly Digest Cron Prompt

Read <SKILL_DIR>/references/digest-prompt.md and follow the complete workflow to generate a weekly digest.

Replace placeholders with:
- MODE = weekly
- TIME_WINDOW = past 7 days
- FRESHNESS = pw
- RSS_HOURS = 168
- ITEMS_PER_SECTION = 5-8
- BLOG_PICKS_COUNT = 3-5
- EXTRA_SECTIONS = 📊 Weekly Trend Summary (2-3 sentences summarizing macro trends)
- SUBJECT = Weekly Tech Digest - YYYY-MM-DD
- WORKSPACE = <your workspace path>
- SKILL_DIR = <your skill install path>
- DISCORD_CHANNEL_ID = <your channel id>
- EMAIL = (optional)
- LANGUAGE = English
- TEMPLATE = discord

Follow every step in the prompt template strictly. Do not skip any steps.

Why This Pattern?

• Single source of truth: Pipeline logic lives in digest-prompt.md, not scattered across cron configs
• Portable: Same skill on different OpenClaw instances, just change paths and channel IDs
• Maintainable: Update the skill → all cron jobs pick up changes automatically
• Anti-pattern: Do NOT copy pipeline steps into the cron prompt — it will drift out of sync

Multi-Channel Delivery Limitation

OpenClaw enforces cross-provider isolation: a single session can only send messages to one provider (e.g., Discord OR Telegram, not both). If you need to deliver digests to multiple platforms, create separate cron jobs for each provider:

# Job 1: Discord + Email
- DISCORD_CHANNEL_ID = <your-discord-channel-id>
- EMAIL = user@example.com
- TEMPLATE = discord

# Job 2: Telegram DM
- DISCORD_CHANNEL_ID = (none)
- EMAIL = (none)
- TEMPLATE = telegram

Replace DISCORD_CHANNEL_ID delivery with Telegram delivery in the second job's prompt (use message tool with channel=telegram).

This is a security feature, not a bug — it prevents accidental cross-context data leakage.

Security Notes

Execution Model

This skill uses a prompt template pattern: the agent reads digest-prompt.md and follows its instructions. This is the standard OpenClaw skill execution model — the agent interprets structured instructions from skill-provided files. All instructions are shipped with the skill bundle and can be audited before installation.

Network Access

The Python scripts make outbound requests to:

• RSS feed URLs (configured in sources.json)
• Twitter/X API (api.x.com)
• Brave Search API (api.search.brave.com)
• GitHub API (api.github.com)

No data is sent to any other endpoints. All API keys are read from environment variables declared in the skill metadata.

Shell Safety

Email delivery uses the gog CLI with hardcoded subject formats (Daily Tech Digest - YYYY-MM-DD). The prompt template explicitly prohibits interpolating untrusted content into shell arguments.

File Access

Scripts read from config/ and write to workspace/archive/. No files outside the workspace are accessed.

Support & Troubleshooting

Common Issues

1. RSS feeds failing: Check network connectivity, use --verbose for details
2. Twitter rate limits: Reduce sources or increase interval
3. Configuration errors: Run validate-config.py for specific issues
4. No articles found: Check time window (--hours) and source enablement

Debug Mode

All scripts support --verbose flag for detailed logging and troubleshooting.

Performance Tuning

• Parallel Workers: Adjust MAX_WORKERS in scripts for your system
• Timeout Settings: Increase TIMEOUT for slow networks
• Article Limits: Adjust MAX_ARTICLES_PER_FEED based on needs

Security Considerations

Shell Execution

The digest prompt instructs agents to run Python scripts via shell commands. All script paths and arguments are skill-defined constants — no user input is interpolated into commands. Two scripts use subprocess:

• run-pipeline.py orchestrates child fetch scripts (all within scripts/ directory)
• fetch-github.py has two subprocess calls:
  1. openssl dgst -sha256 -sign for JWT signing (only if GH_APP_* env vars are set — signs a self-constructed JWT payload, no user content involved)
  2. gh auth token CLI fallback (only if gh is installed — reads from gh's own credential store)

No user-supplied or fetched content is ever interpolated into subprocess arguments. Email delivery writes HTML to a temp file before passing to gog CLI, avoiding shell interpolation. Email subjects are static format strings only.

Credential & File Access

Scripts do not directly read ~/.config/, ~/.ssh/, or any credential files. All API tokens are read from environment variables declared in the skill metadata. The GitHub auth cascade is:

1. $GITHUB_TOKEN env var (you control what to provide)
2. GitHub App token generation (only if you set GH_APP_ID, GH_APP_INSTALL_ID, and GH_APP_KEY_FILE — uses inline JWT signing via openssl CLI, no external scripts involved)
3. gh auth token CLI (delegates to gh's own secure credential store)
4. Unauthenticated (60 req/hr, safe fallback)

If you prefer no automatic credential discovery, simply set $GITHUB_TOKEN and the script will use it directly without attempting steps 2-3.

Dependency Installation

This skill does not install any packages. requirements.txt lists optional dependencies (feedparser, jsonschema) for reference only. All scripts work with Python 3.8+ standard library. Users should install optional deps in a virtualenv if desired — the skill never runs pip install.

Input Sanitization

• URL resolution rejects non-HTTP(S) schemes (javascript:, data:, etc.)
• RSS fallback parsing uses simple, non-backtracking regex patterns (no ReDoS risk)
• All fetched content is treated as untrusted data for display only

Network Access

Scripts make outbound HTTP requests to configured RSS feeds, Twitter API, GitHub API, Reddit JSON API, and Brave Search API. No inbound connections or listeners are created.