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 h4vzz/awesome-ai-agent-skills --skill social-media-postinggit clone --depth 1 https://github.com/h4vzz/awesome-ai-agent-skillsWrote 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/h4vzz/awesome-ai-agent-skills/social-media-posting)<a href="https://agentmods.dev/skills/h4vzz/awesome-ai-agent-skills/social-media-posting"><img src="https://agentmods.dev/badge/skills/h4vzz/awesome-ai-agent-skills/social-media-posting/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/h4vzz/awesome-ai-agent-skills/social-media-posting"><img src="https://agentmods.dev/badge/skills/h4vzz/awesome-ai-agent-skills/social-media-posting.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00029 | $0.02086 |
| Opus 5.5 | $0.00012 | $0.00834 |
| Sonnet 5.5 | $0.00006 | $0.00417 |
| Haiku 4.5 | $0.00003 | $0.00209 |
Grade A, and why
social-media-posting 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 1mo 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.
This is a copy
95% identical to social-media-posting — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 129 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Social Media Posting
This skill enables an AI agent to create and manage social media content across major platforms — Twitter/X, LinkedIn, Instagram, and Facebook. The agent adapts messaging to each platform's unique format constraints, audience expectations, and algorithmic preferences. It handles copy writing, hashtag strategy, scheduling, and content calendar creation to maintain a consistent and engaging social media presence.
Workflow
-
Define the campaign objective and audience. Clarify the goal for the social content: brand awareness, engagement, lead generation, event promotion, or product launch. Identify the target audience segment and which platforms they are most active on. A B2B product launch prioritizes LinkedIn and Twitter/X, while a D2C brand focuses on Instagram and Facebook.
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Draft platform-adapted copy. Write distinct versions of each message tailored to platform constraints and norms. Twitter/X posts use concise hooks within 280 characters with 1–3 hashtags. LinkedIn posts can run 1,300+ characters with paragraph breaks, professional tone, and no more than 3–5 hashtags. Instagram captions support up to 2,200 characters and rely heavily on hashtags (up to 30) and emoji for discoverability. Facebook posts perform best at 40–80 words with a direct question or call-to-action.
-
Craft engagement hooks and CTAs. Open every post with an attention-grabbing first line — a surprising statistic, a bold claim, or a direct question. The first line is the only part visible before "see more" on most platforms. End with a clear call-to-action: comment, share, click link, or tag someone. Use line breaks and whitespace to improve readability on mobile.
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Build a hashtag and mention strategy. Research trending and niche hashtags relevant to the content topic. On Twitter/X, use 1–3 targeted hashtags inline. On LinkedIn, place 3–5 hashtags at the end of the post. On Instagram, use a mix of high-volume (>500K posts), medium (50K–500K), and niche (<50K) hashtags for maximum reach. Tag relevant accounts, partners, or influencers to extend organic visibility.
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.
- 1mo ago First seen · 129 lines · 29 tokens per session scan A db6e24de5eff
social-media-posting is a skill published in the GitHub repository h4vzz/awesome-ai-agent-skills (36 stars, last pushed 22d ago), licensed MIT. It adds 29 tokens to every session and 2,086 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 95% identical to social-media-posting, differing in 2 lines, and is treated as a copy.
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