Social fetch
AI agent skills for the personal operator's craft — decisions, research, second-brain, content rotation, scenario modeling, and meta-skills to author more. Works with Claude Code, Codex, Cursor.
npx -y skills add coreyhaines31/makerskills --skill social-fetchAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
What its author says it does
Copied from the file, not written here
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).
SKILL.md
7.3 KB, as published. Nobody here has run it
/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.com/in/<handle> (profile, recent activity) | linkedin-profile |
instagram.com/p/<id> or instagram.com/reel/<id> | |
tiktok.com/@<user>/video/<id> | tiktok |
bsky.app/profile/<handle>/post/<rkey> | bluesky |
reddit.com/r/<sub>/comments/<id>/... | |
<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 intoraw/with thetweet-/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
$SCRAPECREATORS_API_KEYor$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/--threadskip 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;
--mediadownloads 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.