- Remove duplicate detect_query_type from query.py (divergent 5-type version);
canonical 7-type version lives in query_type.py
- Fix reddit.py import to use query_type.detect_query_type
- Clean unused STOPWORDS/SYNONYMS/tokenize imports from youtube_yt, instagram,
tiktok, scrapecreators_x, bird_x after relevance consolidation
- Fix _relevance_filter default from 0.7 to 0.0 (items without relevance
should not silently pass the filter)
- Remove --dateafter from yt-dlp (returns 0 results for evergreen topics)
- Remove restrictSearchableAttributes from HN search (misses Ask/Show HN)
- Lower HN points filter from >5 to >2 (avoids filtering niche posts)
- Add error logging to select_openai_model HTTP failures
- Remove mise.toml and internal planning doc from repo
- Update module docstrings to describe current purpose, not migration history
- Update tests to import from canonical relevance module
- hackernews: use extract_core_subject instead of raw topic, add
points>5 filter and restrictSearchableAttributes=title to reduce
noise from URL-match and low-signal posts
- youtube: add --dateafter parameter to yt-dlp for server-side date
filtering (Python soft filter still handles fallback)
- reddit: skip opinion/review query variant for how_to/comparison
queries where it adds noise
- bird_x: add OR-group retry with compound terms before falling back
to word-dropping (uses X OR operator for multi-concept queries)
- query.py: add detect_query_type() and extract_compound_terms()
- bird_x: parse_bird_response now accepts query param and computes
token_overlap_relevance against tweet text
- reddit: _normalize_post computes relevance from query vs title+selftext
- hackernews: blends 60% Algolia rank + 40% token overlap + engagement
This makes the 45%-weight relevance factor in score.py actually
differentiate results instead of being a constant.
Replace duplicated _extract_core_subject() in bird_x, reddit, youtube_yt,
tiktok, instagram, bluesky, and scrapecreators_x with thin wrappers that
delegate to query.extract_core_subject() with platform-specific noise sets.
Each module preserves its current behavior exactly:
- bird_x: max_words=5, strip_suffixes=True, full noise set
- youtube_yt: keeps tips/tricks/tutorial/guide/review (content types)
- reddit: preserves original smaller noise set
- tiktok/instagram: same small noise set
- bluesky/scrapecreators_x: minimal noise set
Existing tests pass without modification since _extract_core_subject()
still exists as a callable on each module.
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>
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>
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>
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>
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>
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>
1. Add _extract_core_subject() to strip noise words before X search
- X search is literal keyword matching, not semantic
- "best open claw usecases" → "open claw" (27 results vs 0)
2. Fix ISO date detection bug
- Was: if "T" in created_at (matched "Tue" in "Tue Feb 03...")
- Now: if created_at[10] == "T" (proper ISO separator check)
- Dates now parse correctly: (2026-02-03) instead of (date unknown)
Co-Authored-By: Claude Opus 4.5 <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>
Bird CLI doesn't support --since as a CLI flag.
Use X's search syntax: 'topic since:YYYY-MM-DD'
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- is_bird_installed() checks if bird command is in PATH
- is_bird_authenticated() runs bird whoami to verify auth
- check_npm_available() checks if npm can install bird
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Jeffrey Sperling