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 mfwarren/entrepreneur-claude-skills --skill social-mediagit clone --depth 1 https://github.com/mfwarren/entrepreneur-claude-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/mfwarren/entrepreneur-claude-skills/social-media)<a href="https://agentmods.dev/skills/mfwarren/entrepreneur-claude-skills/social-media"><img src="https://agentmods.dev/badge/skills/mfwarren/entrepreneur-claude-skills/social-media/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/mfwarren/entrepreneur-claude-skills/social-media"><img src="https://agentmods.dev/badge/skills/mfwarren/entrepreneur-claude-skills/social-media.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 | $0.00002 | $0.00572 |
| Opus 5 | $0.00001 | $0.00286 |
| Sonnet 5 | $0.00000 | $0.00114 |
| Haiku 4.5 | $0.00000 | $0.00057 |
Grade A, and why
social-media 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 12d 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.
What it actually says
Social Media
Platform-native content for Twitter/X, LinkedIn, and Instagram. Each platform gets its own format, tone, and structure.
Purpose
Create platform-specific social content that gets engagement — not cross-posted generic content that feels wrong everywhere.
Workflow
Step 1: Gather Context
- Platform(s): Twitter/X, LinkedIn, Instagram
- Topic or core message
- Goal: awareness, engagement, traffic, leads
- Voice: personal, professional, provocative, educational
- Any link to include
Step 2: Platform-Specific Creation
Twitter/X:
- Single tweets: Under 280 chars, punchy, one idea
- Threads: 5-10 tweets, hook → body → CTA, numbered
- Hook tweet must stop the scroll — contrarian, specific, surprising
- End with a CTA (follow, retweet, reply, link)
LinkedIn:
- Hook line (appears above "see more")
- Short paragraphs, 1-2 sentences each
- Personal story or specific example
- End with question or CTA
- 150-300 words optimal
Instagram:
- Caption: Hook → story → CTA, under 150 words
- Hashtag strategy: 5-10 relevant, mix of sizes
- Call to action: save, share, comment, link in bio
Step 3: Variants
Generate 3 variants per platform:
- Direct/educational
- Story-driven/personal
- Contrarian/provocative
Step 4: Content Calendar (if requested)
Weekly or monthly grid with topics, platforms, and post types.
Output Format
## Social Content: [Topic]
### Twitter/X
**Tweet 1 (standalone):** [text]
**Thread:**
1/ [hook]
2/ [body]
...
### LinkedIn
[full post]
### Instagram
**Caption:** [text]
**Hashtags:** [tags]
Constraints
- Never cross-post identical content across platforms
- Respect character limits per platform
- Don't use hashtags on Twitter unless genuinely relevant
- No engagement bait ("Like if you agree!")
- Always sound like a human, not a brand account
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.
- 12d ago First seen · 93 lines · 2 tokens per session scan A fa20ce209819
social-media is a skill published in the GitHub repository mfwarren/entrepreneur-claude-skills (67 stars, last pushed 7mo ago), licensed MIT. It adds 2 tokens to every session and 572 once invoked, about $0.0000 per session on Opus 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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