feat: add x_get_likes (GraphQL) and x_discover_likes with human-like deep reads#21
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feat: add x_get_likes (GraphQL) and x_discover_likes with human-like deep reads#21nj-io wants to merge 4 commits into
nj-io wants to merge 4 commits into
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Replace DOM-based thread scraping with direct GraphQL API calls. X doesn't render self-reply threads as article elements in the DOM, causing empty results — especially for high-engagement tweets. The new approach: - Calls TweetDetail GraphQL API from the page context using session cookies - Gets full_text (no truncation, no "Show more" needed) - note_tweet support for long-form posts - Filters to self-reply chain only (author replying to themselves) - Chronological sorting Also introduces shared helpers for future use by scrapePost: - fetchTweetDetail() — GraphQL API caller - parseTweetResult() — rich data extraction (text, media, article, card, external URLs, engagement stats) - parseThreadFromEntries() — thread chain detection - extractEntries(), unwrapResult(), getScreenName() Fixes: - screen_name moved from user.legacy to user.core in X's GraphQL schema - Self-replies missing from API response for viral tweets (2000+ replies) now handled gracefully (returns available tweets) Supersedes nirholas#12 which patches the DOM approach — this replaces it entirely. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- Replace uniform randomDelay (1-3s) with log-normal distribution (2-7s base + 8% distraction spikes of 8-20s) - Add checkAuth() guard after page navigation — fails fast on expired cookies - Add randomDelay before each fetchTweetDetail API call to simulate human browsing between tweet reads
New scrapePost() function and x_read_post MCP tool that reads any tweet URL with full rich data and recursive quote tweet resolution. Features: - Single tweets or threads (auto-detected via self-reply chain) - Rich data per tweet: text, media (images + best-quality video URL), X Articles (title + cover image + URL), cards (link previews), external URLs (Substack, GitHub, etc.), engagement stats - Recursive quote tweet resolution — if a quoted tweet is itself a thread, or contains its own quote tweet, those are fetched too (up to 5 levels deep) - Human-like delays between API calls (inherited from fetchTweetDetail) - Auth check on navigation (inherited from shared helpers) Depends on: nirholas#17 (scrapeThread GraphQL rewrite with shared helpers) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
…likes Two new scrapers and MCP tools: scrapeLikedTweets — GraphQL-based likes scraper: - Cursor pagination via Likes API (50 tweets in 14s, 200 in 49s) - JSONL output to ~/.xactions/exports/ - from/to timestamp filtering with early exit - Rich data via parseTweetResult discoverLikes — interleaved fetch + deep read: - Fetches likes via API, deep-reads each via scrapePost - Human-like pacing: 3-8s between pages, 2-5s before reads, 5-15s after - Produces two JSONL files: likes index + deep reads - ~38s per tweet average (5 likes = 190s) Both remove x_get_likes from xeepyTools and delete the old DOM handler. Depends on: nirholas#17 (shared helpers), nirholas#18 (scrapePost) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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Superseded — resubmitting as clean PRs from current codebase. |
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Summary
Two new tools for scraping and deeply reading liked tweets.
x_get_likes — fast GraphQL-based likes index
Replaces the DOM-based handler with the Likes GraphQL API:
~/.xactions/exports/from/totimestamp filtering with early exitparseTweetResultx_discover_likes — interleaved fetch + deep read
Fetches likes and deep-reads each one with human-like pacing:
scrapePostArchitecture
scrapeLikedTweets()anddiscoverLikes()insrc/scrapers/twitter/index.jsparseTweetResult,checkAuth,randomDelay,fetchTweetDetail)_scrapePostRecursivefrom feat: add x_read_post tool for full rich tweet reading with recursive quote tweets #18 for deep readsx_get_likesfromxeepyTools, deletes old DOM handlerDepends on
Test plan
x_get_likes— 50 tweets in 14s, 200 in 49sx_get_likeswithfrom/tofiltersx_discover_likes— 5 likes with deep reads in 190s, all threads/QTs resolved🤖 Generated with Claude Code