YouTube search and transcript extraction runs automatically when yt-dlp
is installed. Searches for topic videos from the last N days, fetches
auto-generated transcripts for top results, and feeds them through the
same scoring pipeline (relevance + recency + engagement) as Reddit/X.
New files:
- youtube_yt.py: search, transcript extraction, VTT cleanup
Modified files:
- schema.py: YouTubeItem dataclass, updated Report
- normalize.py: normalize_youtube_items()
- score.py: YouTube engagement scoring (views-dominated)
- dedupe.py: YouTube deduplication
- render.py: YouTube section in compact output
- env.py: is_ytdlp_available() check
- ui.py: YouTube progress messages
- last30days.py: _search_youtube(), parallel execution with Reddit/X
- SKILL.md: YouTube in stats box, citation priority
- README.md: YouTube docs, yt-dlp requirement, Peter shoutout
Inspired by Peter Steinberger's yt-dlp + summarize toolchain approach.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Adds ⚠️ LIMITED RECENT DATA warning when:
- Fewer than 5 items are confirmed from the date range
- Tells Claude to be transparent with user about data freshness
Example output for obscure topic (June Oven):
"Only 4 item(s) confirmed from 2025-12-26 to 2026-01-25.
Results below may include older/evergreen content."
Popular topics (clawdbot, nano banana) don't show the warning.
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Skill now works without any API keys using WebSearch fallback
- Shows promo banner marketing Reddit/X data when keys are missing
- Partial mode (one key) shows shorter tip for the missing source
- Updated SKILL.md to document three modes: Full, Partial, Web-Only
- Added get_missing_keys() to env.py for promo logic
- Added show_promo(), start_web_only(), show_web_only_complete() to ui.py
- Updated render_compact() to include inline promo for web-only mode
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Add Claude's built-in WebSearch tool as a third research source for
/last30days. This enables the skill to work out of the box with zero
API keys while preserving Reddit/X as the primary sources.
Key changes:
- Add WebSearchItem schema for web results (no engagement metrics)
- Add score_websearch_items() with 55/45 relevance/recency weighting
- Apply -15pt source penalty so WebSearch ranks below Reddit/X
- Add --include-web CLI flag to opt-in to WebSearch
- Return 'web' mode when no API keys configured (zero-config)
- Update render.py with [WEB] source label formatting
When WebSearch is enabled, the script outputs instructions for Claude
to use its built-in WebSearch tool, then synthesize results together.
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Show "⚡ CACHED RESULTS (Xh old)" in compact output header
- Add "use --refresh for fresh data" hint
- Track from_cache and cache_age_hours in Report schema
- Update UI to show cache age in stderr message
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- SKILL.md: Move "What I learned" BEFORE "Research Complete" stats
- Add error tracking to Report schema (reddit_error, x_error fields)
- Wrap OpenAI API calls in try/catch with clear error messages
- Show explicit error or "no results" messages in compact output
- Fix false positive error detection for null error fields
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Research topics across Reddit + X from the last 30 days using
OpenAI and xAI APIs. Features:
- Auto model selection (GPT-5.x, Grok-3)
- Popularity-aware scoring (relevance + recency + engagement)
- Reddit thread enrichment with real metrics
- Near-duplicate detection
- Multiple emit modes (compact, json, context, path)
- 24h caching with --refresh bypass
- NUX for API key setup
- 87 passing unit tests
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Matt Van Horn