When a topic is a person/brand (e.g. "Dor Brothers", "Jason Calacanis"),
the agent now resolves their X handle via WebSearch before running the
script, then passes --x-handle to search their posts unfiltered (no
topic keywords required). This finds posts the entity made without
mentioning their own name.
- SKILL.md + OpenClaw variant: Step 0.5 handle resolution instructions
- last30days.py: --x-handle CLI arg, passed through to _run_supplemental()
- bird_x.search_handles(): topic is now Optional[str] for unfiltered mode
- schema.py: resolved_x_handle field on Report
- render.py: show resolved handle in stats output
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
YouTube videos now get real relevance scores based on token overlap
between the search query and video title (was hardcoded at 0.7).
Uses ratio overlap with stopword removal, floored at 0.1.
Cross-source linking annotates items that discuss the same story
across different platforms (e.g., Reddit + HN + X). Items get
bidirectional cross_refs displayed as [xref: R3, HN5] in compact
output so Claude can triangulate multi-platform coverage.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Add HN search via free Algolia API (no key needed). Two-phase approach:
search for stories, then enrich top ones with comments. Integrated into
the full pipeline (normalize, score, dedupe, render) running in parallel
with Reddit/X/YouTube. Source priority: Reddit > X > HN > YouTube > Web.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
OpenAI Responses API web_search takes 60-90s but the generic
future timeout was killing it at 30s (quick) / 60s (default).
Added reddit_future key to TIMEOUT_PROFILES (60/90/120s).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
YouTube: Add youtube_future timeout key (60/90/120s for quick/default/deep)
separate from the shared future timeout. YouTube needs more time because
it does search + parallel transcript fetching. Previously, 20 videos +
5 transcripts exceeded the 60s budget and all results were discarded.
Reddit 429: Propagate rate-limit errors instead of swallowing them.
Enrichment now uses 10s timeout / 1 retry (was 30s / 3 retries).
On first 429, cancel remaining enrichment and skip Phase 2 Reddit.
Total time wasted on 429 drops from ~75s to ~12s.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The hard date filter in the main script was double-filtering YouTube
results. youtube_yt.py already applies a soft date filter that prefers
recent videos but keeps older ones when < 3 are within range (for
evergreen topics like "youtube thumbnails"). The hard filter then
removed all of them, resulting in 0 YouTube items.
YouTube content has a longer shelf life than tweets/posts, so the
soft filter's fallback behavior is correct.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Replace CLI-style promo banners with casual, conversational NUX message
that teaches users to say "last30" + natural language. Remove stale Bird
CLI npm install references and dead prompt_bird_install methods.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Script was hanging indefinitely when API sources were slow or
unresponsive. Now enforces bounded execution:
- Global timeout watchdog (180s default, 90s --quick, 300s --deep)
- Per-source future.result() timeouts (60s/30s/90s by depth)
- Parallel Reddit enrichment capped at 15 items / 45s total
- Subprocess process-group isolation (os.setsid + killpg)
- atexit cleanup kills all tracked child processes
- --timeout=N flag for user override
Also fixes the UX gap where missing sources were silently skipped:
- Pre-flight diagnostic banner shows source status before research
- Source status footer in compact output shows used/skipped/why
- Actionable fix commands for each missing source
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- _search_web() dispatches to Parallel AI / Brave / OpenRouter based on config
- Web results flow through full pipeline: normalize → score → dedupe
- --diagnose shows all source availability (API keys, Bird, YouTube, web backends)
- --store persists findings to SQLite via store.py for watchlist/briefing system
- run_research() now returns web_items alongside reddit/x/youtube
- web_needed flag only set when no native web backend is available
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Add agents/openai.yaml for Codex skill discovery
- Make SKILL.md script path portable (repo, Claude, Codex, agents dirs)
- Platform-neutral output text ("assistant" instead of "Claude")
- Sandbox-friendly cache/output dirs with env var overrides and tempdir fallback
- Add Codex installation docs to README
Inspired by PR #24 (el-analista) and PR #5 (jblwilliams).
Zero impact on existing Claude Code behavior.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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>
After the initial broad search (Phase 1), extract key entities from results
and run targeted secondary searches to surface content the broad pass missed:
- New entity_extract.py: parses @handles, #hashtags, subreddits from results
- bird_x.py: search_handles() does targeted from:handle searches via Bird CLI
- openai_reddit.py: search_subreddits() uses Reddit's free .json search endpoint
- last30days.py: Phase 2 orchestration runs after enrichment, merges + dedupes
Tested with "kanye west" (+9 Reddit, +1 X) and "claude code skills" (+6 Reddit, +1 X).
Phase 2 is skipped on --quick mode. Default caps at 3 handles/subs, deep at 5.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Stats: replace BAD/GOOD examples with strict fill-in-the-blank template
- Reddit: add subreddit-targeted fallback search, soften scoring penalties
(engagement -10→-3, date confidence -10→-5), add minimum result guarantee
- Citations: limit to 1 per insight, short format, no engagement metrics
- Summary: add bold topic headers template for structured paragraphs
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
1. last30days.py: Check isinstance(dict) before .get() - Bird returns
list on success, dict on error
2. bird_x.py: Update field mappings for Bird's actual response format:
- author.username not user.screen_name
- createdAt not created_at (camelCase)
- likeCount, retweetCount, etc. (camelCase)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Remove interactive "Install Bird CLI?" prompt
- Add Bird as FREE option in promo messages
- Auto-detect Bird silently (use if authenticated)
- Keep original flow: show promo → continue with available sources
Bird now appears in the promo alongside API keys:
🔵 X (Twitter)
└─ FREE: npm install -g @steipete/bird (uses browser session)
└─ Or: Add XAI_API_KEY (paid API)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Move Bird CLI check to run before topic validation so users see
the install prompt even when running without a topic argument.
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Move progress display initialization early to support Bird prompts
- Check Bird availability and offer install if no X source available
- Override available sources when Bird is ready
- Pass x_source parameter to run_research function
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Add bird_x import and setup_bird_if_needed function to main script.
The function checks Bird status and offers installation if needed,
returning 'bird' if ready, 'declined' if user declined, or None if
unavailable.
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Refactor run_research() to use ThreadPoolExecutor for parallel execution
- Reddit timeout/crash no longer blocks X search from running
- Add catch for ConnectionResetError/OSError in http.py
- Per-item error handling in Reddit enrichment (one failure doesn't crash all)
- Increase API timeouts from 60/90/120 to 90/120/180 seconds
- Add ClawdBot setup example to README
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
If initial search returns <5 threads, extract core subject and retry:
- "best nano banana prompting practices" → retry with "nano banana"
- Combines results from both searches, deduped by URL
Note: OpenAI's web_search still tends to find old content. This retry
helps cast a wider net but doesn't fully solve the recency issue.
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>
Previously Reddit was returning ~60% old content (some from 2022).
This commit adds multiple layers of date enforcement:
- Reddit prompt: Explicit from_date/to_date with "fewer results > older results"
- Hard filter: filter_by_date_range() in normalize.py excludes old content
- WebSearch Date Detective: Extracts dates from URLs (/2026/01/24/) and
snippets ("January 24, 2026", "3 days ago")
- WebSearch scoring: +10 bonus for verified dates, -20 penalty for unknown
The skill now guarantees only content from the last 30 days.
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>
- Add LAST30DAYS_DEBUG env var / --debug flag
- Log HTTP requests, responses, and errors
- Show API error details when debug enabled
- Helps diagnose API failures
Usage: python3 last30days.py "topic" --debug
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Wrap xAI search in try/except like Reddit
- Show error message but continue with Reddit results
- Parse function checks for API errors before processing
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>
- New ui.py module with colored output and animations
- Animated spinner during Reddit/X searches
- Progress tracking for enrichment phase [1/N]
- Fun random status messages per phase
- Mini ASCII banner at start
- Completion summary with timing
Makes the research feel more alive while waiting!
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
The Report.to_dict() serializes range as {from, to} but constructor
expects range_from/range_to. Added from_dict() classmethod to properly
deserialize cached data, reconstructing all nested objects (Engagement,
Comment, SubScores, RedditItem, XItem).
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>
- quick: 8-12 sources each, faster response
- default: 20-30 sources each (unchanged behavior)
- deep: 50-70 Reddit, 40-60 X for comprehensive research
Adjusts API timeouts based on depth. Cache keys include depth
so different depths are cached separately.
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