diegosouzapw AI Daily Digest Skill
Generate comprehensive daily AI news digest with technical, business, and engineering coverage.
Arguments
Parse from $ARGUMENTS:
--focus [technical|business|engineering|leadership|all]— Default: all
State Files
Last Run Date
Track last run date in:
./findings/ai-daily-digest/.last-run
Format: YYYY-MM-DD
Previous Stories (Deduplication)
Track previously covered stories in:
./findings/ai-daily-digest/.covered-stories
Format: Each story on one line with pipe-separated fields:
{date}|{story_id}|{url}
Where:
date— Date story was covered (YYYY-MM-DD)story_id— Normalized identifier: lowercase, no spaces, key terms only (e.g.,falcon-h1r-7b-release,xai-20b-funding,openai-gpt5-launch)url— Source URL
Example:
2026-01-28|deepseek-r1-release|https://api-docs.deepseek.com/news/news250120
2026-01-29|falcon-h1r-7b-release|https://falcon-lm.github.io/blog/falcon-h1r-7b/
2026-01-29|xai-20b-funding|https://news.crunchbase.com/venture/biggest-funding-rounds
Keep last 300 entries (trim oldest when exceeding).
Purpose: Prevents duplicate stories across days. Web searches return same popular stories regardless of date filters. Story ID enables fuzzy matching across different URLs covering same event.
Friday Weekly Recap Mode
When running on Friday, automatically enable broader research:
- Extended date range: Cover full week (7 days) regardless of last run
- More search queries: Add "this week in AI", "AI weekly roundup" patterns
- Lower-tier sources: Include more community sources (Reddit, Twitter)
- Catch-up section: Add "📅 Stories You Might Have Missed" section
- Digest title: Use "Weekly Recap" instead of "Daily Digest"
- Blog discovery: Search for new indie bloggers (see below)
Blog Discovery (Friday)
Search for new interesting smaller blogs:
"AI blog" OR "ML blog" interesting {date_range}
site:substack.com AI machine learning
site:medium.com AI LLM practical (filter by quality)
site:dev.to AI machine learning tutorial
HN "Show HN" AI blog
When finding new quality blogs:
- Add to "🆕 New Blogs Discovered" section in digest
- Suggest adding to
sources.mdif consistently good
Quality signals:
- Original content (not aggregation)
- Technical depth
- Practical examples
- Active (posted in last 3 months)
Workflow
Phase 1: Setup
- Read
sources.mdfor search patterns and URLs - Read
output-template.mdfor digest format - Parse arguments for focus area
- Read
.last-runfile:- If exists: set date range from last run date to today
- If missing: default to past 7 days (first run)
- Calculate days since last run for digest header
- Read
.covered-storiesfile (CRITICAL):- Parse each line:
{date}|{story_id}|{url} - Build two lookup sets:
covered_ids— Set of all story_idscovered_urls— Set of all URLs
- If file missing or old format (URLs only): migrate by extracting story_ids, or start fresh
- Parse each line:
- Friday check: If today is Friday, enable weekly recap mode
Phase 2: Technical Research
Skip if focus excludes technical
Search patterns:
AI LLM breakthrough OR release site:arxiv.org {date_range}AI model release OR launch {date_range}LLM framework tool release {date_range}site:huggingface.co blog {date_range}site:openai.com blog {date_range}site:anthropic.com news {date_range}
Collect:
- New model releases (GPT, Claude, Gemini, Llama, etc.)
- Research paper highlights
- Framework/tool updates (LangChain, LlamaIndex, vLLM, etc.)
- Benchmark results
Phase 3: Business Research
Skip if focus excludes business
Search patterns:
AI startup funding OR acquisition {date_range}AI company valuation OR investment {date_range}site:techcrunch.com AI {date_range}site:venturebeat.com AI {date_range}OpenAI OR Anthropic OR Google AI business {date_range}
Collect:
- Funding rounds
- Acquisitions/mergers
- Product launches
- Partnership announcements
- Market analysis
Phase 4: Engineering Impact Research
Skip if focus excludes engineering
Search patterns:
AI coding assistant OR developer tools {date_range}AI engineering workflow productivity {date_range}AI job market developer skills {date_range}site:news.ycombinator.com AI OR LLM {date_range}site:reddit.com/r/MachineLearning {date_range}site:reddit.com/r/LocalLLaMA {date_range}
Collect:
- New dev tools and integrations
- Workflow automation updates
- Job market trends
- Community discussions and sentiment
Phase 5: Leadership Research
Skip if focus excludes leadership
Search patterns:
AI leadership engineering management {date_range}AI team strategy CTO VP engineering {date_range}site:hbr.org AI leadership managementsite:mckinsey.com AI leadershipAI transformation organizational change {date_range}engineering leadership AI adoption {date_range}
Collect:
- AI strategy for engineering orgs
- Team structure changes due to AI
- Leadership perspectives on AI adoption
- Org transformation case studies
- Skills and competencies for AI era
Phase 6: GitHub Trending AI
Discover trending AI/ML repositories and tools:
Direct fetch:
- Fetch
https://github.com/trending?since=daily&spoken_language_code=enfor overall trending - Fetch
https://github.com/trending/python?since=daily(most AI repos) - Fetch
https://github.com/trending/jupyter-notebook?since=daily(ML notebooks)
Search patterns:
site:github.com "stars" AI LLM new {date_range}site:github.com trending machine learning {date_range}github AI tool "just released" OR "new release" {date_range}site:news.ycombinator.com "Show HN" github AI {date_range}
Collect:
- New AI/ML repos gaining traction (100+ stars recently)
- Framework releases and major updates
- Interesting tools/demos with code
- Open-source model implementations
Quality signals:
- Stars growth rate (not just total)
- Active development (recent commits)
- Good documentation/README
- Practical utility for engineers
Dedup note: Same repo may appear across days — use {repo-owner}-{repo-name} as story_id.
IMPORTANT: Include interesting/valuable GitHub repos even if not brand new (e.g., trending for past week, recent major updates, or popular repos not yet covered). Check against .covered-stories - if repo not already covered, include it regardless of age. Value and utility matter more than recency for GitHub content.
Phase 7: AI Tools for Professionals
Discover new AI apps/tools for specific professional domains:
Software Engineers:
Search patterns:
AI developer tools new release {date_range}AI coding assistant launch {date_range}AI code review tool {date_range}AI debugging assistant {date_range}"AI for developers" tool app {date_range}site:producthunt.com AI developer coding {date_range}AI IDE plugin extension {date_range}AI terminal CLI tool {date_range}
Collect:
- New AI coding assistants (beyond Copilot/Cursor)
- AI-powered dev tools (testing, debugging, docs)
- CLI tools with AI features
- IDE plugins and extensions
- Code review and analysis tools
- AI for DevOps/infrastructure
Photographers & Videographers:
Search patterns:
AI photo editing tool new {date_range}AI video editing software {date_range}AI image generation photography {date_range}AI video upscaling enhancement {date_range}"AI for photographers" tool app {date_range}"AI for videographers" tool app {date_range}site:producthunt.com AI photo video {date_range}AI color grading tool {date_range}AI background removal tool {date_range}AI video stabilization {date_range}
Collect:
- Photo editing AI tools (retouching, enhancement)
- Video editing assistants
- AI color grading/correction
- Background removal/replacement
- Image upscaling and restoration
- AI-powered camera apps
- Video generation and editing
- Motion tracking and VFX tools
Writers & Content Creators:
Search patterns:
AI writing tool new {date_range}AI content generation platform {date_range}"AI for writers" OR "AI writing assistant" {date_range}site:producthunt.com AI writing content {date_range}AI copywriting tool {date_range}AI blog post generator {date_range}AI script writing tool {date_range}
Collect:
- AI writing assistants (beyond ChatGPT)
- Content generation platforms
- SEO-optimized content tools
- Script and screenplay tools
- Long-form content tools
- AI editing and proofreading
Designers:
Search patterns:
AI design tool new {date_range}AI Figma plugin {date_range}"AI for designers" tool app {date_range}site:producthunt.com AI design {date_range}AI logo generator OR brand design {date_range}AI UI UX design tool {date_range}generative design AI {date_range}
Collect:
- AI design tools and platforms
- Figma/Sketch AI plugins
- Logo and brand design generators
- UI/UX design assistants
- Generative design tools
- Design system automation
Researchers & Academics:
Search patterns:
AI research tool new {date_range}AI literature review OR research assistant {date_range}"AI for researchers" OR "AI for academics" {date_range}AI paper summarization tool {date_range}AI citation management {date_range}AI data analysis research {date_range}
Collect:
- Literature review tools
- Paper summarization services
- Research assistants
- Data analysis platforms
- Citation management tools
- Lab automation software
Educators & Teachers:
Search patterns:
AI education tool new {date_range}AI tutoring platform OR adaptive learning {date_range}"AI for teachers" OR "AI for educators" {date_range}site:producthunt.com AI education learning {date_range}AI lesson planning tool {date_range}AI grading assessment {date_range}
Collect:
- AI tutoring platforms
- Adaptive learning systems
- Lesson planning assistants
- Assessment and grading tools
- Curriculum design tools
- Student engagement platforms
Healthcare Professionals:
Search patterns:
AI healthcare tool new {date_range}AI medical imaging OR diagnostics {date_range}"AI for doctors" OR "AI for clinicians" {date_range}AI clinical decision support {date_range}AI EHR electronic health records {date_range}AI medical scribing documentation {date_range}
Collect:
- Medical imaging AI tools
- Diagnostic assistance
- Clinical decision support
- Medical documentation/scribing
- EHR integration tools
- Patient care optimization
Legal Professionals:
Search patterns:
AI legal tool new {date_range}AI contract review OR analysis {date_range}"AI for lawyers" OR "legal tech AI" {date_range}AI legal research platform {date_range}AI document automation legal {date_range}AI compliance tool {date_range}
Collect:
- Contract review and analysis
- Legal research platforms
- Document automation
- Compliance tools
- Case law analysis
- E-discovery tools
Finance & Accounting:
Search patterns:
AI finance tool new {date_range}AI accounting automation {date_range}"AI for finance" OR "AI for accounting" {date_range}site:producthunt.com AI finance fintech {date_range}AI fraud detection financial {date_range}AI forecasting financial {date_range}
Collect:
- Accounting automation
- Financial forecasting tools
- Fraud detection systems
- Tax preparation AI
- Audit assistance
- Investment analysis tools
Quality signals (all domains):
- Actually useful (not just demos)
- Accessible pricing or free tier
- Active development
- Good reviews/community reception
- Clear value proposition for target profession
Phase 8: AI Application Domains
Discover AI applications across specific domains:
AI in Education:
Search patterns:
AI education platform OR edtech {date_range}adaptive learning AI personalized education {date_range}AI tutoring breakthrough {date_range}AI assessment education {date_range}
Collect:
- New educational AI platforms
- Adaptive learning breakthroughs
- AI tutoring innovations
- Assessment technology
- Educational AI research
AI in Healthcare & Biotech:
Search patterns:
AI drug discovery OR biotech {date_range}AI diagnostics medical breakthrough {date_range}AI clinical trials healthcare {date_range}AI protein folding OR molecular {date_range}AI radiology pathology imaging {date_range}
Collect:
- Drug discovery AI advances
- Diagnostic breakthroughs
- Clinical trial innovations
- Molecular biology AI
- Medical imaging advances
- Precision medicine tools
AI in Creative Industries:
Search patterns:
AI music generation OR composition {date_range}AI game development OR procedural generation {date_range}AI art generation breakthrough {date_range}AI film production OR VFX {date_range}AI voice cloning OR synthesis {date_range}
Collect:
- Music generation tools
- Game development AI
- Art generation advances
- Film/VFX innovations
- Voice synthesis breakthroughs
- Creative AI tools
AI in Robotics & Hardware:
Search patterns:
AI robotics OR humanoid robot {date_range}embodied AI OR physical AI {date_range}robot learning OR manipulation {date_range}autonomous vehicle OR robotaxi {date_range}drone AI OR aerial robotics {date_range}
Collect:
- Humanoid robot developments
- Embodied AI research
- Robot learning breakthroughs
- Autonomous vehicle advances
- Industrial robotics AI
- Consumer robotics
AI in Gaming:
Search patterns:
AI gaming NPC OR game AI {date_range}procedural generation AI game {date_range}AI game testing OR QA {date_range}AI esports OR competitive gaming {date_range}
Collect:
- AI-powered NPCs
- Procedural generation tools
- Game testing automation
- AI in esports
- Game design AI
AI in Scientific Research:
Search patterns:
AI scientific discovery OR research {date_range}AI lab automation OR experiment {date_range}AI hypothesis generation {date_range}AI materials science OR chemistry {date_range}AI climate modeling OR simulation {date_range}
Collect:
- Scientific discovery AI
- Lab automation advances
- Hypothesis generation tools
- Materials science AI
- Climate modeling breakthroughs
- Research acceleration tools
Consumer AI Products:
Search patterns:
AI consumer app launch {date_range}AI smartphone feature OR mobile {date_range}site:producthunt.com AI consumer {date_range}AI home automation OR smart home {date_range}AI personal assistant device {date_range}
Collect:
- Consumer AI apps
- AI smartphone features
- Smart home innovations
- Personal AI assistants
- AI wearables
- Entertainment AI
Phase 9: AI Safety & Ethics
Search patterns:
AI safety research OR alignment {date_range}AI ethics guidelines OR framework {date_range}AI regulation OR policy {date_range}site:anthropic.com alignment OR safety {date_range}AI incident OR failure {date_range}interpretability OR explainable AI {date_range}AI bias fairness {date_range}
Collect:
- AI safety research updates
- Alignment breakthroughs
- Policy and regulation developments
- AI ethics frameworks
- Incident reports and lessons
- Interpretability advances
- Bias and fairness research
- Safety organization updates (Anthropic, OpenAI, DeepMind safety teams)
Phase 10: Open Source AI Ecosystem
Search patterns:
open source AI model release {date_range}open weights OR open source LLM {date_range}site:huggingface.co open source {date_range}AI dataset release OR open data {date_range}democratizing AI OR AI democratization {date_range}EleutherAI OR LAION OR BigScience {date_range}
Collect:
- Open source model releases
- Open weight models (Apache 2.0, MIT, etc.)
- New open datasets
- Community-driven projects
- Democratization initiatives
- Open source AI tools/infrastructure
- Collaborative research efforts
Phase 11: AI Infrastructure & Hardware
Search patterns:
AI chip OR AI accelerator {date_range}GPU OR TPU OR AI compute {date_range}Groq OR Cerebras OR AI hardware {date_range}AI training infrastructure {date_range}model serving OR inference optimization {date_range}edge AI OR on-device AI {date_range}AI datacenter OR compute cluster {date_range}
Collect:
- AI chip announcements
- Custom silicon developments
- Training infrastructure innovations
- Model serving platforms
- Inference optimization tools
- Edge AI hardware
- Datacenter AI architecture
- Compute efficiency breakthroughs
Phase 12: Regional AI Developments
Search patterns:
European AI OR EU AI regulation {date_range}China AI OR Chinese AI development {date_range}Japan AI OR Japanese AI {date_range}Korea AI OR Korean AI {date_range}India AI development {date_range}AI policy Europe OR Asia {date_range}Mistral OR French AI {date_range}
Collect:
- European AI developments (Mistral, regulation, research)
- Chinese AI advances (DeepSeek, ByteDance, etc.)
- Japanese AI initiatives
- Korean AI developments
- Indian AI ecosystem
- Regional policy differences
- Non-US AI companies
- Regional AI research
Phase 13: YouTube AI Videos
Discover new interesting AI-related YouTube content:
Search patterns:
AI tutorial OR explanation site:youtube.com {date_range}LLM OR "large language model" site:youtube.com {date_range}AI news OR update site:youtube.com {date_range}machine learning explained site:youtube.com {date_range}AI coding assistant demo site:youtube.com {date_range}"AI paper" review OR breakdown site:youtube.com {date_range}
Priority channels (check for recent uploads):
- 3Blue1Brown (math/ML visualizations)
- Andrej Karpathy (neural nets, AI education)
- Yannic Kilcher (paper reviews)
- Two Minute Papers (research highlights)
- AI Explained (news, analysis)
- Fireship (dev-focused AI content)
- Matt Wolfe (AI tools, news)
- The AI Advantage (practical tutorials)
- AI Jason (tutorials, tools)
- Prompt Engineering (practical LLM use)
Collect:
- Paper breakdowns and explanations
- AI tool demos and tutorials
- News roundups and analysis
- Technical deep dives
- Practical how-to videos
Quality signals:
- Educational value (not just hype)
- Technical accuracy
- Good production quality
- Useful for engineers
- Recent uploads (within date range)
Dedup note: Use youtube-{channel}-{video-slug} as story_id.
Phase 14: Cool & Thought-Provoking Research
Search for surprising, mind-bending, or philosophical AI content:
Search patterns:
AI "mind-blowing" OR "incredible" demo {date_range}AI art OR creative unexpected {date_range}AI philosophical implications {date_range}site:twitter.com AI demo viral {date_range}site:reddit.com/r/singularity {date_range}AI "you won't believe" OR "wait what" {date_range}AI ethics dilemma OR thought experiment {date_range}
Collect:
- Viral demos showing unexpected capabilities
- Creative/artistic AI applications
- Philosophical thought experiments
- "Wait, that's possible now?" moments
- Unusual cross-domain applications
- Dystopian/utopian implications worth pondering
Quality filter: Must genuinely provoke thought, not just clickbait.
Phase 15: Newsletter & Blog Aggregation
IMPORTANT: Always search BOTH specific known sources AND broader platforms. Don't limit to listed authors—actively discover new quality content.
Specific Known Sources
Check these high-quality sources:
- Simon Willison's blog (simonwillison.net)
- Latent Space blog (latent.space)
- The Batch (deeplearning.ai/the-batch)
- Ben's Bites (bensbites.com)
Indie bloggers (check for recent posts):
- Lilian Weng, Jay Alammar, Eugene Yan
- Chip Huyen, Vicki Boykis, Hamel Husain
- Sebastian Ruder, swyx, François Chollet
Search pattern: site:{blog_url} {date_range} OR site:{blog_url} 2026-02 (flexible date format)
Broader Platform Searches (REQUIRED)
Always search these platforms for AI content:
Substack AI Content:
site:substack.com AI OR LLM {date_range}site:substack.com machine learning February 2026- Look for: Technical analysis, AI engineering insights, research breakdowns
Medium AI Articles:
site:medium.com AI machine learning {date_range}site:medium.com "last week in AI" OR "AI trends"- Look for: Industry analysis, practical tutorials, trend pieces
DEV.to AI Content:
site:dev.to AI tutorial OR insights {date_range}site:dev.to machine learning OR LLM- Look for: Developer tutorials, tool reviews, practical guides
General AI Blog Search:
AI blog post {date_range} analysis insights"AI engineering" OR "ML engineering" blog post this weekAI research blog post analysis {date_range}
Newsletter Discovery:
"AI newsletter" OR "ML newsletter" latest issue 2026AI weekly newsletter {date_range}- Look for: Curated news, research roundups, industry updates
Quality Signals for New Sources:
- Original analysis (not just aggregation)
- Technical depth appropriate for engineers
- Recent activity (last 3 months)
- Clear expertise/credibility
- Practical insights
When finding new quality blogs:
- Note in digest under "🆕 New Blogs & Sources Discovered" section
- Include: Blog name, URL, focus area, why interesting
- Consider suggesting addition to sources.md if consistently high quality
Phase 16: Synthesis (CRITICAL - Dedup BEFORE Digest Generation)
⚠️ CRITICAL: All deduplication MUST happen in this phase BEFORE generating digest in Phase 17.
Step 1: Generate story IDs for all collected items
For each story found, generate a normalized story_id:
- Lowercase, hyphen-separated
- Include: company/product name + action + key detail
- Examples:
- "Falcon-H1R 7B release" →
falcon-h1r-7b-release - "xAI raises $20B" →
xai-20b-funding - "OpenAI launches GPT-5" →
openai-gpt5-launch - "Simon Willison on sandboxes" →
simonwillison-sandboxes-post - "CEO AI anxiety survey" →
wef-ceo-ai-anxiety-survey
- "Falcon-H1R 7B release" →
Step 2: Deduplicate within session
Remove duplicate stories across sources (same event, different URLs).
Step 3: Deduplicate against history (STRICT - USE IN-MEMORY DATA FROM PHASE 1)
⚠️ Use the .covered-stories data loaded in Phase 1 (in-memory covered_ids and covered_urls sets).
DO NOT re-read the file. DO NOT update the file yet.
Filter out ANY story where:
- Exact story_id match in
covered_ids→ SKIP (e.g.,falcon-h1r-7b-releasealready covered) - Similar story_id in
covered_ids→ SKIP (fuzzy: same product/company + same action) - Exact URL match in
covered_urls→ SKIP - Same announcement, different angle → SKIP
Examples of stories to SKIP:
- Falcon-H1R 7B covered yesterday → skip even if new benchmark article
- Simon Willison blog post covered → skip even if different site quotes it
- xAI $20B funding covered → skip follow-up analysis articles
- CEO AI survey covered → skip reposts on different sites
Stories to INCLUDE:
- Genuinely new announcements (story_id NOT in
covered_ids, URL NOT incovered_urls) - New developments on previously covered topics (e.g., acquisition CLOSED vs announced)
- Different products from same company
Step 4: Keep only filtered stories
Store the filtered list. These are the ONLY stories that will appear in the digest.
Step 5: Rank remaining stories
Score by:
- Source credibility (tier 1: arxiv, official blogs; tier 2: tech news; tier 3: social)
- Engagement signals
- Relevance to engineering work
Step 6: Categorize
Assign to template sections.
Step 7: Top 5
Select most impactful stories from NEW filtered content only.
Phase 17: Generate Digest
⚠️ Only use the filtered stories from Phase 16 Step 4. Do NOT include any stories that were filtered out.
- Load
output-template.md - Fill sections with filtered items from Phase 16
- Format:
- Each item:
- [ ] **[Title]** — [1-line summary] [Source: URL] - Checkbox prefix
- [ ]on ALL story items with source URLs (renders as clickable task in Notion) - NO checkbox on: Top 5 summary, prose bullets (Workflow Changes, Job Market, Org Transformation), Action Items, Things to Explore, Connections, Sources section
- Include source URLs
- Add personal takeaways section
- Each item:
- If fewer than 5 stories after filtering, note "Light news day" in digest
Phase 18: Save Digest Files (DO NOT Update .covered-stories Yet)
⚠️ CRITICAL: Do NOT update .covered-stories in this phase. That happens in Phase 20 AFTER verification.
Step 1: Create directories if needed
mkdir -p ./findings/ai-daily-digest
Step 2: 🔴 SAVE TO NOTION WORKSPACE (REQUIRED - DO NOT SKIP)
⚠️ CRITICAL: This step is MANDATORY. The digest MUST be saved to Notion.
Step 2a: Load Notion MCP tool
Notion tools are deferred and must be loaded first using ToolSearch:
select:mcp__notion__notion-create-pages
Step 2b: Read digest content
Read the digest file just created to get the full content.
Step 2c: Create Notion page
Use mcp__notion__notion-create-pages to create page under parent "🤖 AI Digests":
- Parent page ID:
3035f40a-a0f4-81ea-8033-fc823dd8eb92 - Title property:
🤖 AI Digest {YYYY-MM-DD} - Content: Full digest markdown (excluding the H1 title line, which goes in properties)
Example call:
{
"parent": {"page_id": "3035f40a-a0f4-81ea-8033-fc823dd8eb92"},
"pages": [{
"properties": {"title": "🤖 AI Digest 2026-02-16"},
"content": "**Focus:** All\n**Coverage:** ...\n\n## 🔬 Technical Advances\n..."
}]
}
Verification: Confirm Notion page created successfully (returns page URL) before continuing.
Step 3: Write archive copy
./findings/ai-daily-digest/ai-digest-{YYYY-MM-DD}.md
Step 4: Update last run date ONLY
./findings/ai-daily-digest/.last-run
Use Write tool to save today's date in YYYY-MM-DD format (e.g., 2026-01-28).
File contains only the date string, nothing else.
⚠️ DO NOT update .covered-stories yet. Wait for verification in Phase 19.
Verification: Confirm files written successfully (Notion page + 1 archive file + 1 last-run file) before proceeding to Phase 19.
Phase 19: Duplicate Verification (Spawn Agent)
⚠️ NOTE: .covered-stories has NOT been updated yet with today's stories. This is intentional.
Spawn a separate verification agent to check for duplicates as a sanity check.
Agent task:
Verify AI digest for duplicate stories against recent history.
Files to read:
1. Today's digest: ./findings/ai-daily-digest/ai-digest-{YYYY-MM-DD}.md
2. Last 3 digests from ./findings/ai-daily-digest/ (by date, excluding today)
3. Covered stories: ./findings/ai-daily-digest/.covered-stories (should NOT include today's stories yet)
Check for:
1. **Exact duplicates** — Same story_id in today's digest and .covered-stories (before today)
2. **Near duplicates** — Same company/product + similar action within 7 days
3. **URL duplicates** — Same URL appeared in previous digests
4. **Topic fatigue** — Same topic (e.g., "GPT-5 rumors") covered 3+ times in past week
For each potential duplicate found:
- Story title from today's digest
- Matching story from history (date, story_id, URL)
- Duplicate type (exact/near/url/fatigue)
- Recommendation: REMOVE or KEEP (with justification)
Output format:
## Duplicate Check Results
### ❌ Duplicates Found (Remove)
- **{Story}** — matches {history_story} from {date} [{type}]
### ⚠️ Borderline (Review)
- **{Story}** — similar to {history_story} [{type}] — {why borderline}
### ✅ All Clear
{count} stories verified as unique
If duplicates found, list specific line numbers in today's digest to remove.
Agent type: general-purpose
On duplicate detection:
If agent finds duplicates marked REMOVE:
- Read the duplicate report
- Edit both digest files (Obsidian + archive) to remove flagged stories
- Log removed stories
- DO NOT proceed to Phase 20 until duplicates are removed
If only borderline items:
- Keep stories but note in digest footer:
*Verification: {N} borderline items retained* - Proceed to Phase 20
- Keep stories but note in digest footer:
If all clear:
- Proceed to Phase 20
Output Requirements
- Use emojis for section headers (per Notion conventions)
- Bullet points over paragraphs
- Include wikilinks to existing workspace pages where relevant
- All items must have source URLs
- Top 5 stories section required
- Personal takeaways with actionable items
- Show coverage period in header (e.g., "Coverage: Jan 25 - Jan 28 (3 days)")
Error Handling
- If WebSearch fails for a source, log and continue with others
- Minimum viable digest: at least 5 items total across categories
- If < 5 items found, expand date range by 1 day and retry
- Only update
.last-runon successful digest generation
Example Invocations
# Full digest since last run
/ai-digest
# Technical focus only
/ai-digest --focus technical
# Business news only
/ai-digest --focus business
Phase 20: Update Covered Stories (FINAL STEP)
⚠️ Only execute this phase AFTER Phase 19 verification passes (or duplicates are removed).
Append to covered stories:
./findings/ai-daily-digest/.covered-stories
For each story in today's FINAL digest (after any removals from Phase 19), append line in format:
{date}|{story_id}|{url}
Example entries:
2026-01-30|nvidia-isaac-groot-n16|https://nvidianews.nvidia.com/news/nvidia-releases-new-physical-ai-models
2026-01-30|apple-qai-acquisition|https://techstartups.com/2026/01/29/apple-acquires-israeli-ai-startup
2026-01-30|simonwillison-sprites-dev|https://simonwillison.net/2026/Jan/9/sprites-dev/
Implementation:
Use Bash with heredoc to append all stories at once.
Cleanup: Keep file under 300 lines — if over, trim oldest entries from top.
Final verification: Confirm file updated successfully. Digest generation complete.
📬 Newsletter Integration
Story items use - [ ] checkbox format for newsletter curation:
- Unchecked
- [ ]= not selected - Checked
- [x]= selected for weekly newsletter
User checks stories in Notion → /ai-newsletter extracts checked items into curated weekly newsletter. See ai-newsletter skill for details.