Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add coreyhaines31/makerskills --skill social-fetchgit clone --depth 1 https://github.com/coreyhaines31/makerskillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/coreyhaines31/makerskills/social-fetch)<a href="https://agentmods.dev/skills/coreyhaines31/makerskills/social-fetch"><img src="https://agentmods.dev/badge/skills/coreyhaines31/makerskills/social-fetch/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/coreyhaines31/makerskills/social-fetch"><img src="https://agentmods.dev/badge/skills/coreyhaines31/makerskills/social-fetch.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
- Socket pass
- Snyk warn
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00216 | $0.01913 |
| Opus 5.5 | $0.00086 | $0.00765 |
| Sonnet 5.5 | $0.00043 | $0.00383 |
| Haiku 4.5 | $0.00022 | $0.00191 |
Grade A, and why
social-fetch scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/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").
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago Changed · +11 tokens per session bc1ca7841802
- 19d ago Changed 061cabb08612
- 1mo ago First seen · 128 lines · 205 tokens per session scan A 99fd2b2d2591
social-fetch is a skill published in the GitHub repository coreyhaines31/makerskills (875 stars, last pushed yesterday), licensed MIT. It adds 216 tokens to every session and 1,913 once invoked, about $0.0009 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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