tech-news-digest
Automated tech news digest system with unified data source model, quality scoring pipeline, and template-based output generation.
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Install Skill
Run in your terminal
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installs
1
this week
55
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What it does
Collects from six sources in parallel: RSS feeds, Twitter/X KOLs, GitHub releases and trending repos, Reddit posts, and web search, with deduplication and quality scoring across all sources
Includes 151 pre-configured sources (62 RSS feeds, 48 Twitter accounts, 28 GitHub repos, 13 subreddits, plus web search) covering AI, crypto, and frontier tech topics
S
Installation Guide
How to use tech-news-digest on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your machine
- ›Node.js 16+ with npm — verify with
node --version - ›Active project directory where you want to add
tech-news-digest
Run the install command
Execute the skills CLI command in your project's root directory to begin installation:
Fetches tech-news-digest from draco-agent/tech-news-digest and configures it for Cursor.
Select Cursor when prompted
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate tech-news-digest. Access via /tech-news-digest in your agent's command palette.
Security Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Documentation
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: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 -
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)
-
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 -
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"
}
}
]
}
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_TOKENnot 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] [--backend auto|official|twitterapiio]
- Backend auto-detection: uses twitterapi.io if
TWITTERAPI_IO_KEYset, else official X API v2 ifX_BEARER_TOKENset - 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 →ghCLI → unauthenticated (60 req/hr)
fetch-github.py --trending - GitHub Trending Repos
python3 scripts/fetch-github.py --trending [--hours 48] [--output FILE] [--verbose]
- Searches GitHub API for trending repos across 4 topics (LLM, AI Agent, Crypto, Frontier Tech)
- Quality scoring: base 5 + daily_stars_est / 10, max 15
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, 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
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
- Reports unhealthy sources (>50% failure rate)
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
- Sources with same
Example Workspace Override
// workspace/config/tech-news-digest-sources.json
{
"sources": [
{
"id": "simonwillison-rss",
"enabled": false,
"note"List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Steps
- 1Install product management skill
- 2Start with user story generation for known feature
- 3Progress to competitive analysis: research 2-3 competitors
- 4Use for roadmap prioritization: apply RICE/ICE scoring
- 5Draft stakeholder communications and refine based on feedback
- 6Build template library for recurring PM tasks
- 7Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
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Reviews
- NNeel Diallo★★★★★Dec 20, 2024
We added tech-news-digest from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- IIshan Khanna★★★★★Dec 20, 2024
We added tech-news-digest from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- CCamila Ndlovu★★★★★Dec 4, 2024
tech-news-digest fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- OOmar Malhotra★★★★★Dec 4, 2024
tech-news-digest reduced setup friction for our internal harness; good balance of opinion and flexibility.
- LLuis Gupta★★★★★Nov 23, 2024
Registry listing for tech-news-digest matched our evaluation — installs cleanly and behaves as described in the markdown.
- OOmar Liu★★★★★Nov 23, 2024
We added tech-news-digest from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- DDiya Sanchez★★★★★Nov 11, 2024
tech-news-digest reduced setup friction for our internal harness; good balance of opinion and flexibility.
- MMia Smith★★★★★Nov 11, 2024
tech-news-digest reduced setup friction for our internal harness; good balance of opinion and flexibility.
- DDiya Ramirez★★★★★Nov 7, 2024
Solid pick for teams standardizing on skills: tech-news-digest is focused, and the summary matches what you get after install.
- DDiya Abbas★★★★★Oct 26, 2024
tech-news-digest has been reliable in day-to-day use. Documentation quality is above average for community skills.
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