Tech News Digest

Evidence-led tech digest with unified collection and one editorial selection shared across formats. Follow references/digest-prompt.md as the authoritative mode policy.

Editorial Contract

• Daily preserves original sections: 2–4 sentence overview; configured topics (normally LLM, AI Agent, Crypto, Frontier Tech; aim for 3–5 qualified items each); KOL viewpoints ≤3; releases ≤3 repositories; project discovery ≤3; blog picks ≤3; ≤30 unique items overall. News/blog explanations normally contain 2–3 concise sentences of change, evidence and implication. Retain empty headings with a coverage note, never filler. Optimize content within sections: a request to shorten GitHub releases must not become a whole-report redesign or one-message digest.
• Weekly ≤35 unique items: overview; configured topic sections in configured order (normally LLM, AI Agent, Crypto, Frontier Tech), with 2–4 substantial syntheses per topic as an advisory aim. Each synthesis uses 2–4 concise sentences joining week progress, evidence and implications, not concatenated headlines. Retain empty topic, key-release, project and viewpoint/reading headings with honest non-bullet coverage notes. Key releases ≤5 repositories (Chinese explanation ≤80 characters); projects ≤3; viewpoints/deep reading ≤4; optional next-week watch ≤3 pending releases, fixes or uncertainties. Do not force experiments; factual watch claims need citations, clearly proposed/not-performed experiments retain the narrow citation exemption.
• Caps are not quotas. Count evidence events inside syntheses and standalone watch items. Preserve topic sections in both modes; no global three-theme constraint. Body limits: daily ≤6500 characters, weekly ≤10000, excluding URL targets; never fill to the limit.
• Mandatory security coverage: follow the primary-alert/search and pre-delivery checks in references/digest-prompt.md. Preserve existing topics; use optional 🛡️ 安全警报 after the overview only for credible urgent incidents in either mode; weekly may also use an optional dedicated security/risk section for consequential nonurgent risks. Omit when empty and count/deduplicate within existing caps. Log checks and decisions; failed collection is not evidence of no incidents.
• Relevance, impact and evidence before internal scores. Exceptional claims need original technical evidence and independent assessment where possible, otherwise exclude/downgrade. No public scores, social metrics or operational statistics. Daily keeps substantive, nonduplicative KOL viewpoints. A material coverage gap may receive one concise caveat without raw counts; details stay in the final operational log.
• Deduplicate events and canonical URLs across the whole report. Daily repeats require incremental developments; weekly may synthesize daily coverage. Daily keeps blog picks; weekly viewpoints/deep reading may include original opinions, papers, docs, postmortems or essays.
• Project discovery is not verified trending; no lifetime-derived growth or repeated mature repos without meaningful changes. Preserve the prompt's consequential-release rules, exact versions and official links.
• Plain bullets with bold titles; concise inline Discord links [来源](<URL>). Section-aware chunks ≤1700 characters including numbering. Apply the requested language, including Simplified Chinese explanations when configured.
• Validate the canonical archive with python3 scripts/validate-digest.py --input FILE --mode daily or --mode weekly before delivery; fix all errors. Weekly production runs append one --topic-heading 'EXACT LOCALIZED HEADING' per configured topic in order; without these flags the gate cannot infer custom headings. Missing/failing validation blocks delivery. Manually verify unique-event counts inside syntheses, required non-topic headings/overview, security placement, evidence/coverage honesty and cross-format parity too.
• Discord, Markdown, email and PDF use identical selections/judgments. Operational stats/runtime attribution belong in the final log, not content.
• Legacy ITEMS_PER_SECTION, BLOG_PICKS_COUNT and EXTRA_SECTIONS are advisory parameters superseded by mode policy: ignore their counts/extra sections, especially duplicate weekly trends.

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/tech-news-digest-sources.json
   cp config/defaults/topics.json workspace/config/tech-news-digest-topics.json
   

2. Environment Variables:

   • TWITTERAPI_IO_KEY - twitterapi.io API key (optional, preferred)
   • X_BEARER_TOKEN - Twitter/X official API bearer token (optional, fallback)
   • TAVILY_API_KEY - Tavily Search API key, alternative to Brave (optional)
   • WEB_SEARCH_BACKEND - Web search backend: auto|brave|tavily (optional, default: auto)
   • BRAVE_API_KEYS - Brave Search API keys, comma-separated for rotation (optional)
   • BRAVE_API_KEY - Single Brave key fallback (optional)
   • GITHUB_TOKEN - GitHub personal access token (optional, improves rate limits)

3. Generate Digest:

   # Unified pipeline (recommended) — runs all 6 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. Select and Validate: Follow references/digest-prompt.md; validate the canonical Markdown before rendering the same selections to Discord, email and PDF.

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 6 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, max 2 concurrent per host), retry with jittered backoff, feedparser + regex fallback
• Timeout: 30s per feed, ETag/Last-Modified caching in $TECH_NEWS_DIGEST_STATE_DIR

fetch-twitter.py - Twitter/X KOL Monitor

python3 scripts/fetch-twitter.py [--defaults DIR] [--config DIR] [--hours 48] [--output FILE] [--backend auto|official|twitterapiio]

• Backend auto-detection: uses twitterapi.io if TWITTERAPI_IO_KEY set, else official X API v2 if X_BEARER_TOKEN set
• Rate limit handling, engagement metrics, retry with backoff

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 → releases.atom
• Without a token (or on a 403/429 rate limit) it reads github.com/<repo>/releases.atom, which needs no auth, consumes no REST quota, and also surfaces tag-only repos such as torvalds/linux
• The Atom feed lists every tag, so entries are kept only when the tag carries a <major>.<minor> version (v2.13.0, v6.19-rc4). This drops CI tags such as PyTorch's trunk/<sha> and viable/strict/<epoch>, which would otherwise crowd out real releases

fetch-github.py --trending - Project Discovery (legacy flag)

python3 scripts/fetch-github.py --trending [--hours 48] [--output FILE] [--verbose]

• Searches GitHub API for discovery candidates; search results do not establish genuine trends.
• Neutral internal base score 5, not a growth signal. No daily_stars_est or lifetime-derived growth. Daily discovery ≤3, weekly ≤3; require a current reason to try the project.

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

enrich-articles.py - Article Full-Text Enrichment

python3 scripts/enrich-articles.py --input merged.json --output enriched.json [--min-score 10] [--max-articles 15] [--verbose]

• Fetches full article text for high-scoring articles
• Cloudflare Markdown for Agents (preferred) → HTML extraction (fallback) → Skip (paywalled/social)
• Blog domain whitelist with lower score threshold (≥3)
• Parallel fetching (5 workers, 10s timeout)

merge-sources.py - Quality Scoring & Deduplication

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

• Quality scoring, URL dedup (tracking params stripped, query preserved), title similarity dedup (75%), previous digest penalty
• Multi-source bonus: +5 per additional source type corroborating the same story
• Topic priority is derived from topics.json order; pass --defaults/--config to keep it in sync
• 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

generate-pdf.py - PDF Report Generator

python3 scripts/generate-pdf.py --input report.md --output digest.pdf [--verbose]

• Converts markdown digest to styled A4 PDF with Chinese typography (Noto Sans CJK SC)
• Emoji icons, page headers/footers, blue accent theme. Requires weasyprint.

sanitize-html.py - Safe HTML Email Converter

python3 scripts/sanitize-html.py --input report.md --output email.html [--verbose]

• Converts markdown to XSS-safe HTML email with inline CSS
• URL whitelist (http/https only), HTML-escaped text content

source-health.py - Source Health Monitor

python3 scripts/source-health.py --rss FILE --twitter FILE --github FILE --reddit FILE --web FILE [--verbose]

• Tracks per-source success/failure history over 7 days in $TECH_NEWS_DIGEST_STATE_DIR/source-health.json
• Reports unhealthy sources (>50% failure rate, minimum 2 samples)

summarize-merged.py - Merged Data Summary

python3 scripts/summarize-merged.py --input merged.json [--top N] [--topic TOPIC]

• Human-readable summary of merged data for LLM consumption
• Shows top articles per topic with scores and metrics

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/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"]
    }
  ]
}

Templates & Output

Canonical Markdown (references/templates/markdown.md)

• Daily/weekly structure governed by references/digest-prompt.md; one validated selection for all formats.

Discord Template (references/templates/discord.md)

• Plain bullets, bold titles, inline [来源](<URL>) links; section-aware chunks ≤1700 characters including numbering.

Email Template (references/templates/email.md)

• Convert validated Markdown with sanitize-html.py, send the HTML file with send-email.py.
• Same selections, no extra metadata sections or operational statistics.

PDF Template (references/templates/pdf.md)

• Same canonical report, A4 Chinese typography and page numbers.
• Generated via scripts/generate-pdf.py (requires weasyprint); no PDF-only content.

Default Sources (216 enabled)

• RSS Feeds (93): AI labs, arXiv, research blogs, tech news, crypto news, Chinese tech media, YouTube channels
• Twitter/X KOLs (76): AI researchers, model labs, crypto leaders, tech executives
• GitHub Repos (47): Major open-source projects (llama.cpp, vLLM, SGLang, LangGraph, MCP, etc.)
• Reddit (13, disabled by default): Reddit blocks datacenter IPs; set REDDIT_CLIENT_ID/REDDIT_CLIENT_SECRET and re-enable in your overlay
• Web Search (4 topics): LLM, AI Agent, Crypto, Frontier Tech

A further 7 RSS/GitHub defaults ship disabled because the upstream feed is dead; each carries a note saying why. 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:

# 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 rotation
export BRAVE_API_KEY="key1"                # Single key fallback
export BRAVE_PLAN="free"                   # Override rate limit detection: free|pro

# Reddit (required to enable the Reddit layer — it ships disabled)
export REDDIT_CLIENT_ID="xxx"              # Script-type app from reddit.com/prefs/apps
export REDDIT_CLIENT_SECRET="xxx"
export REDDIT_USERNAME="xxx"               # Optional, User-Agent string only

# GitHub (optional, unlocks richer release notes)
export GITHUB_TOKEN="ghp_xxx"              # PAT (simplest)
export GH_APP_ID="12345"                   # Or use GitHub App for auto-token
export 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: Disabled by default — Reddit returns 403 to datacenter IPs. Set REDDIT_CLIENT_ID/REDDIT_CLIENT_SECRET and re-enable the sources to use the OAuth 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.

Existing cron jobs may still pass ITEMS_PER_SECTION, BLOG_PICKS_COUNT and EXTRA_SECTIONS. Accept them for compatibility but ignore their quotas/extra sections; mode policy supersedes them. New examples omit them.

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
- ENRICH = true
- 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
- ENRICH = true
- 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 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

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 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:

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, Brave Search API, and Tavily Search API. No inbound connections or listeners are created.