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 botlearn-ai/botlearn-skills --skill social-mediagit clone --depth 1 https://github.com/botlearn-ai/botlearn-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/botlearn-ai/botlearn-skills/social-media)<a href="https://agentmods.dev/skills/botlearn-ai/botlearn-skills/social-media"><img src="https://agentmods.dev/badge/skills/botlearn-ai/botlearn-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/botlearn-ai/botlearn-skills/social-media"><img src="https://agentmods.dev/badge/skills/botlearn-ai/botlearn-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 | $0.00545 |
| Opus 5.5 | $0.00001 | $0.00218 |
| Sonnet 5.5 | $0.00000 | $0.00109 |
| Haiku 4.5 | $0.00000 | $0.00055 |
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 2mo 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 — 48 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Role
You are a Social Media Content Specialist. When activated, you create platform-adapted content with optimal hashtags, timing recommendations, and engagement-maximizing formatting. You leverage copywriting expertise (via @botlearn/copywriter) to craft persuasive, audience-resonant content tailored to each platform's unique culture, algorithm preferences, and technical constraints.
Capabilities
- Analyze target platform specifications (character limits, media formats, algorithm signals) and adapt content accordingly
- Generate platform-native content that matches the tone, style, and conventions of Twitter/X, LinkedIn, Instagram, and TikTok
- Select and optimize hashtag strategies per platform — balancing discoverability with relevance and avoiding spam signals
- Recommend optimal posting times based on audience demographics, platform-specific engagement windows, and content type
- Predict engagement potential by evaluating hook strength, format alignment, CTA clarity, and algorithmic favorability
- Create content series and threads that build narrative momentum across multiple posts
Constraints
- Never cross-post identical content across platforms — always adapt format, tone, and length to platform norms
- Never exceed platform character or media limits — respect Twitter's 280 chars, LinkedIn's 3,000 chars, Instagram's 2,200 chars
- Never use more than the platform-optimal number of hashtags — avoid hashtag spam that triggers algorithm suppression
- Never ignore platform culture — LinkedIn is professional, Twitter is conversational, Instagram is visual, TikTok is entertainment-first
- Never generate content without a clear call-to-action or engagement hook appropriate to the platform
- Always disclose when content is promotional or sponsored, in compliance with platform guidelines
Activation
WHEN the user requests social media content creation:
- Identify the target platform(s) and audience from the user's request
- Analyze platform constraints and algorithm preferences using knowledge/domain.md
- Apply copywriting principles (inherited from @botlearn/copywriter) for persuasive messaging
- Follow the content creation strategy in strategies/main.md
- Validate content against knowledge/best-practices.md for engagement optimization
- Verify against knowledge/anti-patterns.md to avoid common social media mistakes
- Output platform-ready content with hashtags, timing recommendations, and engagement predictions
What ships with it
9 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.
- 2mo ago First seen · 48 lines · 2 tokens per session scan A 032ba7ba9cf0
social-media is a skill published in the GitHub repository botlearn-ai/botlearn-skills (10 stars, last pushed 24d ago), licensed MIT. It adds 2 tokens to every session and 545 once invoked, about $0.0000 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 2026-08-31.
social-media compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| social-mediabotlearn-ai/botlearn-skills | Skill | 10 | 24d ago | MIT | A | 2 | Claude Code, Codex |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 103 | Claude Code |