Model optimization (mini-first fallback, is_search_capable_model) belongs
in PR #67. This PR stays focused on endpoint/API fixes only.
Also fixes pre-existing test bug where test asserted gpt-4o was first in
MODEL_FALLBACK_ORDER when it was actually gpt-4.1.
- Instagram: migrate /v1/ to /v2/ ScrapeCreators endpoint (v1 deprecated Feb 2026)
- OpenAI: switch fallback chain to [gpt-5-mini, gpt-4.1-mini, gpt-4.1] (8x cheaper,
gpt-5-mini is the first mini model supporting web_search with filters.allowed_domains)
- xAI: use explicit grok-4-1-fast-non-reasoning (bare name aliases to reasoning variant)
- xAI: pass from_date/to_date natively to x_search tool config instead of prompt-only
- Polymarket: correct rate limit comment (15K/10s, not 350/10s)
Mastodon-compatible API at truthsocial.com/api/v2/search.
Opt-in via TRUTHSOCIAL_TOKEN env var (bearer token from browser).
Silent when unconfigured. Full pipeline: search, parse, normalize,
score, dedupe, render across all 10 pipeline files.
27 new tests, 440 total passing.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
searchPosts endpoint now returns 403 for unauthenticated requests.
Add session auth via createSession, gate on BSKY_HANDLE + BSKY_APP_PASSWORD
env vars. When unconfigured, Bluesky is completely invisible (no error).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Free, no-auth-required search via public.api.bsky.app.
Always-on like HN and Polymarket (no API key needed).
- New scripts/lib/bluesky.py: search + parse via AT Protocol
- BlueskyItem schema, normalization, scoring, deduplication
- Wired into orchestrator ThreadPoolExecutor with timeout config
- Rendering in compact, full, and JSON output modes
- 14 unit tests covering parsing, dates, relevance, edge cases
- --search=bluesky / --search=bsky for bluesky-only mode
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
One SCRAPECREATORS_API_KEY now covers Reddit, TikTok, Instagram, AND X.
Priority: Bird (free) > xAI API > ScrapeCreators (shared key).
New module scrapecreators_x.py follows the same pattern as tiktok.py.
Updated env.py source routing and last30days.py orchestrator dispatch.
Includes 20 unit tests.
Fixes#55.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Add per-project configuration via .claude/last30days.env, discovered by
walking up from cwd. Uses the same .env format as the existing global
config — no new parsers or formats.
Priority (highest wins):
1. Environment variables
2. .claude/last30days.env (per-project)
3. ~/.config/last30days/.env (global)
Also adds file permission checking — warns to stderr if config files
are readable by other users (should be chmod 600).
Includes tests for discovery, precedence, source tracking, and
permission warnings.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Xiaohongshu search via local MCP service (opt-in, zero impact if service not running)
- Reddit public JSON fallback (works with zero API keys)
- Reddit priority: ScrapeCreators -> OpenAI -> public fallback
- Updated env.py: Reddit always available via public fallback
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Resolve conflicts between ScrapeCreators Reddit (main) and
public Reddit fallback (PR #48). Priority: ScrapeCreators ->
OpenAI -> public Reddit fallback.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Add --save-dir flag to last30days.py that saves raw research output
during the existing script run. Remove entire "Save Research to
Documents" section from SKILL.md (~45 lines). No more extra tool
calls, no (No output), no multi-minute cogitation after invitation.
Tested: --mock confirms file creation and duplicate date suffixing.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- New scripts/lib/reddit.py: multi-query expansion, global search,
subreddit discovery, targeted subreddit search, comment enrichment
- 68 results in 17s vs ~15 results in 60-90s (OpenAI)
- Cost: ~$0.02/search vs $0.03-0.10 (15-50x cheaper)
- Real engagement data (score, comments, dates) from API
- No more 429 rate limits on comment enrichment
- Falls back to OpenAI if SCRAPECREATORS_API_KEY missing
- Registered as last30daysbeta for parallel local testing
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- add xiaohongshu/xhs source path via xiaohongshu-mcp HTTP API\n- add Reddit public JSON fallback when OpenAI auth is unavailable\n- update diagnostics/UI rendering for new source availability states\n- harden Xiaohongshu availability probe to reduce false negatives\n- include source status reporting for Xiaohongshu
Add Instagram Reels as the 8th research source via ScrapeCreators API.
One API key (SCRAPECREATORS_API_KEY) now covers both TikTok and Instagram.
- Add scripts/lib/instagram.py: keyword search, transcript extraction,
relevance scoring, engagement metrics (views, likes, comments)
- Add InstagramItem to schema, normalization, scoring, dedup, rendering
- Add Instagram to orchestrator pipeline, watchlist, and UI spinners
- Update SKILL.md: stats template, citation priority, item format,
URL-to-name extraction rules, anti-Sources instruction
- Update README and CHANGELOG for v2.8
- Fix: Instagram/TikTok not running in --search= web-only path
- Fix: web stats line showing full URLs instead of domain names
- Replace APIFY_API_TOKEN with SCRAPECREATORS_API_KEY throughout
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Root cause of empty TikTok results: Apify required monthly subscription.
ScrapeCreators is PAYG with 100 free credits and no subscription.
Key fix: ScrapeCreators nests items under aweme_info wrapper
(search_item_list[].aweme_info.{fields}), which the previous
implementation missed, causing all fields to be empty.
Changes:
- Rewrite tiktok.py to use ScrapeCreators REST API
- Add aweme_info unwrapping for correct field extraction
- Add transcript fetching via /video/transcript endpoint
- Add SCRAPECREATORS_API_KEY to env.py config
- Update last30days.py to use env.get_tiktok_token()
- Delete apify_client_wrapper.py (no longer needed)
- Update tests for new date field format (create_time)
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Remove double quotes around $ARGUMENTS in SKILL.md so bash word-splits
the expansion, and change argparse topic from nargs="?" to nargs="*"
so multi-word topics still work. Also document --store, --include-web,
--diagnose, and --timeout flags in the Options section.
Closes#36
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Only print debug log lines when running in an interactive terminal.
In Claude Code (non-TTY), the spinner system handles progress display,
so these raw log lines just add noise.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Pass logger=None to Apify .call() to prevent the SDK from streaming
raw actor run logs (status messages, crawler stats, warnings) that
drown out the clean spinner UI in Claude Code.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Remove quiet=True from YouTube and TikTok spinners so they display
the same colored emoji progress lines as Reddit and X in non-TTY mode.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
When running in Claude Code, the assistant has a built-in WebSearch tool
that's free and higher quality than Parallel AI/Brave/OpenRouter. Adding
--no-native-web to the SKILL.md invocation defers web search to the
assistant, saving API credits. OpenClaw invocations don't pass this flag,
so they continue using native web backends.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The websearch module import was dropped when the tiktok import was added,
causing the script to crash during the rendering phase after all data
was successfully collected.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Add TikTok search, scoring, and rendering using the Apify platform
(clockworks/tiktok-scraper actor). Users bring their own APIFY_API_TOKEN
($5/month free credits, no CC required). The shared apify_client_wrapper
module is designed for reuse by future Facebook/Instagram sources.
- New modules: tiktok.py (search + caption extraction), apify_client_wrapper.py
- Schema: TikTokItem dataclass, shares field on Engagement, Report.tiktok
- Pipeline: normalize → filter → score → sort → dedupe → cross-link → render
- Scoring: 0.50*log1p(views) + 0.30*log1p(likes) + 0.20*log1p(comments)
- SKILL.md bumped to v2.7 with TikTok stats, citations, and security docs
- 26 unit tests covering relevance, normalize, score, dedupe, render, round-trip
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Inspired by PR #26 (wkbaran), whose early work on HN/YouTube sources helped
shape what we built in v2.5. Cherry-picks the source-filtering concept as a
clean implementation against our existing architecture.
--search=SOURCES accepts comma-separated: reddit, x, hn, youtube, polymarket, web
Example: --search reddit,hn (run only Reddit + Hacker News)
Also:
- bird_x: add noise words (trending, viral, plugin, skills) + last-chance retry
- render: show xAI tip for reddit-only mode regardless of missing_keys value
- tests: new test_bird_x.py (5 tests)
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Cherry-picked from PR #24 (el-analista). Adds trending/viral/plugin/skill/tool
noise words to _extract_core_subject, and a last-chance retry that falls back
to the longest non-noise token when 2-word retry also returns 0 results.
cache.py and render.py env overrides were already on main.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* chore: fix YAML error in argument-hint
* add codex auth support to responses API
* Use gpt-5.1-codex-mini as default model for Codex auth
Add CODEX_FALLBACK_MODELS chain (gpt-5.1-codex-mini → gpt-5.2) for
Codex endpoint which doesn't support standard OpenAI models like
gpt-4o-mini. Adds model fallback retry on 400 errors in the Codex
search path. Also adds test_codex_auth.py with 22 unit tests covering
JWT decoding, auth resolution, SSE parsing, and payload building.
* Pass .env credentials to Bird Node subprocesses for X auth
On platforms without browser cookie access (e.g. WSL2), Bird's
vendored Node.js module cannot read AUTH_TOKEN/CT0 from Firefox
or Chrome cookie stores. The .env config file already supports
these values, but they were only loaded into the Python config
dict — never exported to the environment of Node subprocesses.
- Add AUTH_TOKEN/CT0 to env.py config key loading
- Add set_credentials()/\_subprocess_env() to bird_x.py to inject
credentials into the env dict passed to subprocess.run/Popen
- Call set_credentials() in main() before Bird auth detection
---------
Co-authored-by: Justin Williams <jblwilliams@gmail.com>
The Gamma API only searches event titles/slugs, missing markets where the
topic is an outcome (e.g., "Arizona" in NCAA Tournament Winner). This adds:
- All-word query expansion (not just first word): "Arizona Basketball" now
searches "Arizona", "Basketball" independently
- Tag-based domain expansion: extracts category tags (e.g., "NCAA") from
first-pass results and searches those as a second pass
- Neg-risk binary market synthesis: shows team names from market questions
instead of generic Yes/No outcomes
- Question shortening: extracts "Arizona" from "Will Arizona win the NCAA
Tournament?" for clean display
- Increased depth (3 pages) and result caps (15) for more coverage
Live results: "Arizona Basketball" now finds NCAA Tournament Winner (12%),
#1 Seed (88%), Big 12 Champion (69%). "Iran War" returns 15 markets (up
from 9) with no regression.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Add CROSS to sync targets with sed-patched name/version/description
- Switch cp to rsync to handle identical file edge case on APFS
- CROSS SKILL.md gets last30daysCROSS skill root injected into search path
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- _compute_text_similarity() now checks outcome names with bidirectional
substring matching (0.85) and token overlap (0.7), not just event titles
- Collect outcomes from ALL active markets per event, filter to >1% price
- Reorder outcome_prices to surface topic-matching outcome before top-3 truncation
- Add SKILL.md "Prediction Markets" synthesis section with structural/long-term
market preference, domain examples, citation format, and narrative weaving
- Add Polymarket to citation priority list between HN and Web
- Update stats box template to show up to 5 market odds
- Fix render.py "vol24h" label to "volume"
- Add NCAA seed fixture event for outcome-only matching tests
- 82 polymarket tests pass (14 new)
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Polymarket results now rank by text similarity, volume, liquidity, price
movement, and competitive score instead of API return position. Also fixes
pagination (DEPTH_CONFIG now controls page count, not a no-op limit param)
and caps results after re-ranking.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Search Polymarket's free Gamma API for relevant prediction markets on any
topic. Uses smart multi-query expansion to cast a wider net (e.g., "Arizona
Basketball" also searches "Arizona"), merges and dedupes by event ID, and
shows price movement context ("up 22.5% this week"). No API key required.
Also hides sources with zero results from the stats output (all sources).
54 new tests, all passing. Full pipeline integration with scoring, dedupe,
cross-source linking, and rendering.
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>
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>
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>
Jeffrey Sperling