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social-fetch

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업데이트2026년 7월 6일 17:10

When you or another skill needs to fetch the content of a social media post by URL — tweet, X thread, LinkedIn post, Instagram post, TikTok video, Bluesky post, Reddit thread, Mastodon status, Threads post, Hacker News thread. Returns normalized structured data (author, posted_at, text, engagement counts, media URLs, replies if requested) regardless of platform. Tries strategies in order: direct API (Bluesky, Mastodon, HN, Reddit), agent-browser with modal dismissal (LinkedIn, X preview), Wayback Machine (older posts), paid APIs (ScrapeCreators / Apify — only if env keys present). Triggers on "/social-fetch <url>," "fetch this tweet," "fetch this post," "what does this LinkedIn say," "read this thread," "pull this post." Used by deep-research (citing specific posts), jab-hook (inspiration account analysis), business-brainstorm (competitor / operator commentary).

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coreyhaines31

coreyhaines31/makerskills

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소프트웨어 개발자컴퓨터 및 수학직·SOC 15-1252

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name	social-fetch
description	When you or another skill needs to fetch the content of a social media post by URL — tweet, X thread, LinkedIn post, Instagram post, TikTok video, Bluesky post, Reddit thread, Mastodon status, Threads post, Hacker News thread. Returns normalized structured data (author, posted_at, text, engagement counts, media URLs, replies if requested) regardless of platform. Tries strategies in order: direct API (Bluesky, Mastodon, HN, Reddit), agent-browser with modal dismissal (LinkedIn, X preview), Wayback Machine (older posts), paid APIs (ScrapeCreators / Apify — only if env keys present). Triggers on "/social-fetch <url>," "fetch this tweet," "fetch this post," "what does this LinkedIn say," "read this thread," "pull this post." Used by deep-research (citing specific posts), jab-hook (inspiration account analysis), business-brainstorm (competitor / operator commentary).
metadata	{"version":"0.1.1"}

/social-fetch — Pull any social post by URL

Normalized fetcher for social posts across platforms. Detects platform from URL, tries strategies in order, returns the same JSON shape regardless of source.

Step 1 — Detect platform

URL pattern	Platform
`x.com/<user>/status/<id>` or `twitter.com/<user>/status/<id>`	x (Twitter)
`linkedin.com/posts/<slug>` or `linkedin.com/feed/update/urn:li:activity:<id>`	linkedin
`linkedin.com/in/<handle>` (profile, recent activity)	linkedin-profile
`instagram.com/p/<id>` or `instagram.com/reel/<id>`	instagram
`tiktok.com/@<user>/video/<id>`	tiktok
`bsky.app/profile/<handle>/post/<rkey>`	bluesky
`reddit.com/r/<sub>/comments/<id>/...`	reddit
`<mastodon-instance>/@<user>/<id>` (e.g. mastodon.social, hachyderm.io)	mastodon
`threads.net/@<user>/post/<id>`	threads
`news.ycombinator.com/item?id=<id>`	hn
`youtube.com/watch?v=<id>` or `youtu.be/<id>`	→ defer to `watch-video`

If the URL doesn't match any pattern, ask the user what platform it is.

Step 2 — Pick strategy chain

Read references/strategies.md for the per-platform strategy chain. Each platform has 2–5 strategies tried in order.

Key principles:

Free strategies first (direct APIs, agent-browser)
Paid only as fallback (ScrapeCreators / Apify) — and only if the env key is set
Bluesky / Mastodon / HN / Reddit are free + reliable (public APIs)
X / LinkedIn / Instagram / TikTok / Threads need paid or scraping fallback for full data

Step 3 — Execute strategy

For each strategy in the chain:

Try it
If success: parse → normalize → return
If failure (404, 402, auth wall, empty response): note the failure and try the next strategy

After exhausting the chain, return a clear error: which strategies were tried, why each failed, and what's needed to unlock (e.g., "Add $SCRAPECREATORS_API_KEY for X — see references/auth-keys.md").

Step 4 — Normalize output

Return this shape regardless of platform (see references/output-schema.md for the full spec + platform-specific examples):

{
  "platform": "x",
  "url": "https://x.com/example/status/1234567890",
  "fetched_at": "2026-06-17T14:35:00Z",
  "raw_source": "scrapecreators",
  "author": {
    "handle": "@example",
    "name": "the user Ganim",
    "verified": true
  },
  "posted_at": "2026-06-17T16:53:00Z",
  "text": "The 80/20 of a useful AI second brain: ...",
  "media": [],
  "engagement": {
    "likes": 51,
    "reposts": 13,
    "replies": 9,
    "bookmarks": 7,
    "views": 32700
  },
  "is_thread": true,
  "thread": [],
  "replies": []
}

Fields with no equivalent on a platform (e.g., bookmarks on Mastodon) get null, not 0. Missing data is different from zero data.

Step 5 — Optional enrichments

Based on flags / asks:

Flag	Behavior
`--with-replies`	Fetch top-level replies (1 hop). Costs extra API quota.
`--thread`	If the post is part of a thread by the same author, fetch the whole thread.
`--raw`	Include the raw API/scrape response in the output (for debugging)
`--media`	Download media files (images/videos) to `~/Documents/social-fetches/<platform>-<id>/`

Default: just the post itself, no replies, no media download (just URLs).

Step 6 — Cache (optional)

If ~/Documents/social-fetches/_cache/ exists, cache successful fetches there by {platform}-{id}.json for 24h. Saves API quota when the same post is referenced repeatedly across skills.

Skip cache if --no-cache flag is set or for --with-replies / --thread (likely-stale).

Composes with

deep-research — cite specific posts in research briefs. When research surfaces a relevant tweet/post URL, fetch and include in the brief.
jab-hook — pull recent posts from inspiration accounts for deeper format analysis (currently uses agent-browser inline; should call this skill instead).
business-brainstorm — pull competitor / operator commentary as evidence during scoring.
second-brain — capture a post into raw/ with the tweet- / bookmark- prefix; the structured output makes for cleaner raw files than a screenshot or copy-paste.
watch-video — for YouTube URLs (or any video — Loom, Vimeo, Riverside, MP4), route there instead.

Known limits

X: free strategies return tweet preview only (text, author, basic engagement). Full thread + replies need $SCRAPECREATORS_API_KEY or $APIFY_API_TOKEN.
LinkedIn: agent-browser works for profile recent-activity (after dismissing the modal). Specific post URLs (linkedin.com/posts/...) often need paid fallback.
Instagram / TikTok / Threads: heavy anti-bot. Paid fallback strongly recommended.
Bluesky / Mastodon / HN / Reddit: free + reliable.
Private / deleted posts: nothing helps. Try Wayback Machine for deleted content.

If a platform consistently fails on free strategies and the user uses it often, prompt to set up the paid key (see references/auth-keys.md).

Notes on quality

Strategy chain, not single-source. Every platform has a fallback ladder (native oEmbed → agent-browser → SCS API → Apify). If one step fails, degrade gracefully to the next. Never fail hard on the first attempt.
Structured output over screenshots. Downstream skills (jab-hook, deep-research, second-brain) need JSON with author + text + engagement fields, not an image. Even when the underlying strategy is a screenshot, extract text before returning.
Cache aggressively, invalidate honestly. 24h TTL on ~/Documents/social-fetches/_cache/ prevents API burn when the same post is referenced across multiple skills in a session. --with-replies / --thread skip cache because replies age fast.
Respect paid-key economics. ScrapeCreators / Apify calls cost real money. Prompt before hitting paid strategies if the user hasn't confirmed they want depth. Free strategies first, always.
Media download is opt-in. Default is post text only; --media downloads images/videos. Silent media downloads eat disk quickly.
Private / deleted content is a hard stop. No strategy chain rescues private accounts or deleted posts. Suggest Wayback Machine for deleted content and stop.
Rate-limits are per-platform. X free strategies hit rate limits fast; LinkedIn agent-browser burns session fingerprints. Space out calls in loops or the workflow degrades to worse-than-manual.