Reorganize the changelog to match the real story: smarter scoring,
cross-source linking, and handle resolution as one "dramatically
better results" narrative first, then HN, then handle resolution
details. Moves blinded comparison right after the results section
as proof.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Handle resolution was only triggering for "person/brand" topics. Products
and tools like "Nano Banana Pro" or "Seedance" can also have X accounts
(@nanobanana, @seedanceai) but were being skipped.
Changes:
- Broadened trigger: people, brands, products, tools, companies, communities
- Added parody/fan account verification guidance
- Added site:x.com to WebSearch query for better results
- Updated both SKILL.md and OpenClaw variant
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The resolved handle dedup was wrong: if entity_extract found @thedorbrothers
(from @mentions in Phase 1 results), the resolved handle search was skipped
entirely. But entity-extracted handles are searched WITH topic keywords
(from:handle topic), while resolved handles need UNFILTERED search
(from:handle) to find posts that don't mention the topic string.
Example: Dor Brothers' viral tweet (5.5K likes) says "We made a $300M movie
starring @LoganPaul" - no mention of "dor brothers" anywhere. The topic-
filtered entity search missed it. The unfiltered resolved search finds it.
Before: 30 X posts, 161+ likes (entity search only)
After: 40 X posts, 5549+ likes (resolved handle adds viral tweet)
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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>
Ran 15-way blinded comparison (5 topics x 3 versions). CROSS won all 5 topics
(4.74/5.0 avg vs HN 4.10, Base 3.73). Then improved CROSS further:
- dedupe.py: hybrid similarity (token+trigram Jaccard) at 0.40 threshold,
cross-source links went from 3 to 13 items across 5 topics
- render.py: [xref: HN5, HN4] -> [also on: HN, Reddit] for human-readable tags
- youtube_yt.py: SYNONYMS dict so "hip hop" matches "rap" (0.33 -> 0.71 score)
- SKILL.md: instruction #7 tells Claude to lead with cross-platform signals
Validation: improved CROSS scores 4.38/5.0 vs original 3.98 (+0.40), wins 4/5
topics. Biggest gains in specificity (+0.8) and format compliance (+1.0).
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>
Reddit and X are the star of the show. In Claude Code (non-TTY),
suppress ⏳ start messages for HN and YouTube so Reddit/X are the
first visible lines. HN/YouTube still show ✓ completion messages.
Also suppress [HN] debug logs in non-TTY to reduce output clutter.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
HN was appearing before YouTube in the stats block, sort tiebreaker,
and source status. Now consistently: Reddit > X > YouTube > HN > Web.
Also restored emoji + box-drawing chars in test skill SKILL.md.
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>
The Reddit search uses OpenAI's Responses API with web_search, which
frequently returns 429 rate limit errors. The previous retry logic used
linear backoff (1s, 2s, 3s) which is too aggressive for OpenAI's rate
limiter (often needs 10-60s waits).
Changes:
- Increase max retries from 3 to 5
- Switch from linear to exponential backoff (2s, 5s, 9s, 17s, 33s)
- Parse and respect Retry-After header from OpenAI 429 responses
- Fall back to cheaper models (gpt-4.1 → gpt-4o) on 429s, not just
on 400/403 access errors
- Remove gpt-4o-mini from fallback chain — it doesn't support
web_search with the filters parameter
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Add CHANGELOG.md (Keep a Changelog format) and release-notes.md
for the v2.1.0 GitHub Release. Also includes queued copy updates:
plugin.json version bump to 2.1.0, YouTube added to descriptions,
SKILL.md security/permissions section and ClawdBot metadata,
updated watchlist examples, and v2.1 launch post refinements.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Watchlist schedules are metadata only — nothing triggers runs
automatically. Updated README to be honest that cron/launchd or an
always-on bot like Open Claw is required for automated scheduling.
Local Claude Code users can still use run-one and run-all manually.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
When X posts return engagement: null, dict.get("engagement", {})
returns None (key exists with null value), causing AttributeError.
Use `or {}` idiom to coalesce None to empty dict.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Replace all em dashes with hyphens
- "Claude Code skill" -> "skill" in intro
- Ralph Wiggum -> Seedance 2.0 / Nano Banana Pro
- tweet/Tweet -> post/Post throughout
- "signal of a tweet" -> "signal of a single post"
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>
The `from . import bird_x` in __init__.py caused ImportError for all
other module imports (youtube_yt, render, etc.) when bird_x had issues,
crashing the entire script in Codex. Making it a bare package marker
lets Python resolve `from lib import X` normally.
Added scripts/sync.sh to deploy to all three skill locations
(~/.claude, ~/.agents, ~/.codex) with import verification.
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>
- Remove 2>&1 from SKILL.md so stderr doesn't pollute model input
- Run script in foreground (not background) with 5min timeout
- Add explicit YouTube synthesis instruction for Claude
- Remove --flat-playlist which broke date filtering (all dates were None)
- Move date filtering to Python with soft fallback for evergreen topics
- Keep 'tips', 'tutorial', 'review', 'guide' in YouTube search queries
- Increase yt-dlp timeout from 60s to 120s for full metadata fetch
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>
- Split V2.1 blurb into two clear bullets (YouTube + X search)
- Better X auth section with browser-specific notes and verify command
- Updated intro/tagline to mention YouTube as 4th source
- Added social post drafts and updated issue #19 response with YouTube
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>
Vendor Bird's Twitter GraphQL search client directly into /last30days,
eliminating the dependency on `npm install -g @steipete/bird`. X search
now works out of the box with just Node.js 22+ and browser cookies.
- Add vendored bird-search.mjs wrapper (search-only subset of Bird v0.8.0)
- Vendor @steipete/sweet-cookie for browser cookie extraction
- Update bird_x.py to call vendored Node.js module instead of `bird` binary
- Update README.md and SKILL.md for v2.1 (remove Bird CLI install steps)
- Include Bird's MIT LICENSE in vendor directory
The fallback chain is: vendored search -> xAI API key -> web-only mode.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Honest about 2-8 min research time vs V1's speed. Points users
to @mvanhorn / @slashlast30days for quick mode feedback.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
"Research typically takes 2-8 minutes (niche topics take longer)."
Shown right after parsed intent, before research starts.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Demonstrates /last30days researching a tool that launched 2 days ago —
before blog roundups existed. Real-time X/Reddit reactions from
@Hartdrawss, @rezkhere, @Totinhiiio plus honest Chase Jarvis review.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Real V2 output: 33 X posts (9.3K likes), @dekreationz viral post,
WSJ apology arc, BULLY album, Bianca Vanity Fair — demonstrates
/last30days as a news/culture research tool, not just prompting.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
New example uses fresh V2 research output showing JSON prompting
dominance, @handle citations, and the full research-to-prompt flow.
Removed the old iOS App Mockup example which used the same SwimMom
prompt/image but with stale V1 data.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Replace generic "[topic]" and --days=7 with concrete examples that
show the range: prompting, news, recommendations.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Lead with dramatically better X/Reddit search quality (smarter query
construction + Phase 2 supplemental), Bird CLI as secondary headline,
community contributions in their own section.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Three bugs in _extract_core_subject():
1. Multi-word noise phrases ("what are", "how to") never matched
because code compared individual words against multi-word strings.
"what are people saying about DeepSeek R1" became "what are people
saying" — losing the entire topic.
2. Missing meta words — "prompt", "techniques", "tips" weren't
filtered (only "prompting" was). "vibe motion best prompt
techniques" kept 4 keywords instead of 2.
3. No retry on 0 results — Reddit retries with simplified queries
but X accepted 0 and moved on.
Fix: Two-phase extraction (strip multi-word prefixes/suffixes first,
then individual noise words), expanded noise set, max 3 words (was 4),
and automatic retry with first 2 words when Bird returns 0 results.
Before → After:
- "vibe motion best prompt techniques" → "vibe motion" (was 4 words, 0 results)
- "what are people saying about DeepSeek R1" → "deepseek r1" (was "what are people saying")
- "nano banana pro prompts for gemini" → "nano banana pro" (was 4 words)
Tested: vibe motion (12 X posts, was 0), DeepSeek R1 (12 posts),
kanye west (12 posts, no regression).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Add V2 to title
- Document Bird CLI installation (free X search)
- Add --days=N to options table
- Update Requirements to show Bird CLI as recommended free option
- Replace How It Works with two-phase search architecture
- Add What's New in V2 section with all new features
- Credit community contributors (@JosephOIbrahim, @levineam, @jonthebeef)
- Bump http.py USER_AGENT from 1.0 to 2.0
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Every invitation now includes 2-3 specific examples based on what the
research actually found. PROMPTING mode explicitly offers to write prompts
with creative examples. NEWS suggests follow-up questions about the
biggest stories. GENERAL suggests specific deep-dives and applications.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
GENERAL mode said "write a prompt for it" which sounds weird for people/topics
("write a prompt for Kanye West"). Changed to "describe what you're working on
and I'll help." Added "I'm now an expert on {TOPIC}" prefix to all 4 modes.
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>
- Invitation adapts to QUERY_TYPE: NEWS gets "ask me anything",
PROMPTING gets "share your vision", RECOMMENDATIONS gets "compare options"
- Follow-up handler reads intent: questions get answers, not forced prompts
- Restored V1's "if they ask a question, answer it" context memory line
- URL formatting rule: "per Rolling Stone" not raw URLs
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Matt Van Horn