Generate tech news digests with unified source model, quality scoring, and multi-format output. Six-source data collection from RSS feeds, Twitter/X KOLs, GitHub releases, GitHub Trending, Reddit, and web search. Pipeline-based scripts with retry mechanisms and deduplication. Supports Discord, email, and markdown templates.
Generate tech news digests with unified source model, quality scoring, and multi-format output. Six-source data collection from RSS feeds, Twitter/X KOLs, GitHub releases, GitHub Trending, Reddit, and web search. Pipeline-based scripts with retry mechanisms and deduplication. Supports Discord, email, and markdown templates.
[{"name":"TWITTER_API_BACKEND","required":false,"description":"Twitter API backend: 'official', 'twitterapiio', or 'auto' (default: auto)"},{"name":"X_BEARER_TOKEN","required":false,"description":"Twitter/X API bearer token for KOL monitoring (official backend)"},{"name":"TWITTERAPI_IO_KEY","required":false,"description":"twitterapi.io API key for KOL monitoring (twitterapiio backend)"},{"name":"TAVILY_API_KEY","required":false,"description":"Tavily Search API key (alternative to Brave)"},{"name":"WEB_SEARCH_BACKEND","required":false,"description":"Web search backend: auto (default), brave, or tavily"},{"name":"BRAVE_API_KEYS","required":false,"description":"Brave Search API keys (comma-separated for rotation)"},{"name":"BRAVE_API_KEY","required":false,"description":"Brave Search API key (single key fallback)"},{"name":"GITHUB_TOKEN","required":false,"description":"GitHub token for higher API rate limits (auto-generated from GitHub App if not set)"},{"name":"GH_APP_ID","required":false,"description":"GitHub App ID for automatic installation token generation"},{"name":"GH_APP_INSTALL_ID","required":false,"description":"GitHub App Installation ID for automatic token generation"},{"name":"GH_APP_KEY_FILE","required":false,"description":"Path to GitHub App private key PEM file"}]
tools
[{"python3":"Required. Runs data collection and merge scripts."},{"mail":"Optional. msmtp-based mail command for email delivery (preferred)."},{"gog":"Optional. Gmail CLI for email delivery (fallback if mail not available)."}]
files
{"read":[{"config/defaults/":"Default source and topic configurations"},{"references/":"Prompt templates and output templates"},{"scripts/":"Python pipeline scripts"},{"<workspace>/archive/tech-news-digest/":"Previous digests for dedup"}],"write":[{"/tmp/td-*.json":"Temporary pipeline intermediate outputs"},{"/tmp/td-email.html":"Temporary email HTML body"},{"/tmp/td-digest.pdf":"Generated PDF digest"},{"<workspace>/archive/tech-news-digest/":"Saved digest archives"}]}
Tech News Digest
Automated tech news digest system with unified data source model, quality scoring pipeline, and template-based output generation.
Quick Start
Configuration Setup: Default configs are in config/defaults/. Copy to workspace for customization:
Use Templates: Apply Discord, email, or PDF 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"}}]}
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/tech-news-digest-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"]}]}
Configuration Errors: Schema validation with helpful messages
API Keys & Environment
Set in ~/.zshenv or similar:
# Twitter (at least one required for Twitter source)export TWITTERAPI_IO_KEY="your_key"# twitterapi.io key (preferred)export X_BEARER_TOKEN="your_bearer_token"# Official X API v2 (fallback)export TWITTER_API_BACKEND="auto"# auto|twitterapiio|official (default: auto)# Web Search (optional, enables web search layer)export WEB_SEARCH_BACKEND="auto"# auto|brave|tavily (default: auto)export TAVILY_API_KEY="tvly-xxx"# Tavily Search API (free 1000/mo)# Brave Search (alternative)export BRAVE_API_KEYS="key1,key2,key3"# Multiple keys, comma-separated rotationexport BRAVE_API_KEY="key1"# Single key fallbackexport BRAVE_PLAN="free"# Override rate limit detection: free|pro# GitHub (optional, improves rate limits)export GITHUB_TOKEN="ghp_xxx"# PAT (simplest)export GH_APP_ID="12345"# Or use GitHub App for auto-tokenexport GH_APP_INSTALL_ID="67890"export GH_APP_KEY_FILE="/path/to/key.pem"
Twitter: TWITTERAPI_IO_KEY preferred ($3-5/mo); X_BEARER_TOKEN as fallback; auto mode tries twitterapiio first
Web Search: Tavily (preferred in auto mode) or Brave; optional, fallback to agent web_search if unavailable
GitHub: Auto-generates token from GitHub App if PAT not set; unauthenticated fallback (60 req/hr)
Reddit: No API key needed (uses public JSON API)
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
- ENRICH = true
- BLOG_PICKS_COUNT = 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 = 10-15
- ENRICH = true
- 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:
Replace DISCORD_CHANNEL_ID delivery with the target platform's delivery in the second job's prompt.
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 tech-news-digest-sources.json)
Twitter/X API (api.x.com or api.twitterapi.io)
Brave Search API (api.search.brave.com)
Tavily Search API (api.tavily.com)
GitHub API (api.github.com)
Reddit JSON API (reddit.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 send-email.py which constructs proper MIME multipart messages with HTML body + optional PDF attachment. Subject formats are hardcoded (Daily Tech Digest - YYYY-MM-DD). PDF generation uses generate-pdf.py via weasyprint. The prompt template explicitly prohibits interpolating untrusted content (article titles, tweet text, etc.) into shell arguments. Email addresses and subjects must be static placeholder values only.
File Access
Scripts read from config/ and write to workspace/archive/. No files outside the workspace are accessed.
Support & Troubleshooting
Common Issues
RSS feeds failing: Check network connectivity, use --verbose for details
Twitter rate limits: Reduce sources or increase interval
Configuration errors: Run validate-config.py for specific issues
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:
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)
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 uses send-email.py which builds MIME messages programmatically — no shell interpolation. PDF generation uses generate-pdf.py via weasyprint. Email subjects are static format strings only — never constructed from fetched data.
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:
$GITHUB_TOKEN env var (you control what to provide)
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)
gh auth token CLI (delegates to gh's own secure credential store)
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.
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, Brave Search API, and Tavily Search API. No inbound connections or listeners are created.
