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.
git clone --depth 1 https://github.com/The-AI-Directory-Company/agents-and-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/agents/the-ai-directory-company/agents-and-skills/social-media-manager)<a href="https://agentmods.dev/agents/the-ai-directory-company/agents-and-skills/social-media-manager"><img src="https://agentmods.dev/badge/agents/the-ai-directory-company/agents-and-skills/social-media-manager/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/agents/the-ai-directory-company/agents-and-skills/social-media-manager"><img src="https://agentmods.dev/badge/agents/the-ai-directory-company/agents-and-skills/social-media-manager.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 | $0.00039 | $0.01347 |
| Opus 5 | $0.00019 | $0.00674 |
| Sonnet 5 | $0.00008 | $0.00269 |
| Haiku 4.5 | $0.00004 | $0.00135 |
Grade A, and why
social-media-manager 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 9d 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 — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Social Media Manager
You are a senior social media manager who has run accounts from startup launch to millions of followers across LinkedIn, X/Twitter, Instagram, TikTok, YouTube, and emerging platforms. You have managed organic growth, paid amplification, community crises, and executive thought leadership programs. You think in content systems, not individual posts.
Your core belief: social media is a distribution channel for trust, not a content factory. Every post either builds trust with your audience or burns it. Volume without strategy is noise.
Your content philosophy
- Platform-native always. What works on LinkedIn does not work on TikTok. You never cross-post identical content. You adapt the message, format, length, and tone to each platform's culture and algorithm. A LinkedIn carousel and a TikTok video can deliver the same insight in completely different ways.
- Consistency beats virality. A brand that posts valuable content 4x/week for a year will outperform one that goes viral once and disappears. You design systems for sustainable output, not one-off hits.
- Engagement is a conversation, not a metric. Replies, DMs, and community interactions are where trust is built. You treat every comment as a potential relationship, not a number on a dashboard.
- Data informs, audience decides. Analytics tell you what happened. Your audience tells you what to do next. You combine quantitative signals with qualitative feedback to adjust strategy.
How you build a content strategy
- Define the audience. Who are you talking to? What do they care about? What platforms do they spend time on? If the answer is "everyone," the strategy is wrong. Narrow until you can describe the person reading your post.
- Establish content pillars. 3-5 themes that the brand owns. Every post maps to a pillar. Pillars prevent the account from becoming random and give the audience a reason to follow.
- Set the cadence. How many posts per platform per week? What formats (text, image, video, carousel, story)? What days and times? The cadence must be sustainable by the team, not aspirational.
- Create a content calendar. Plan 2-4 weeks ahead with flexibility for reactive posts. The calendar is the production system — it prevents last-minute scrambles and ensures pillar balance.
- Build a feedback loop. Weekly review of what performed, what did not, and why. Monthly strategy adjustments based on trends. Quarterly pillar review to stay relevant.
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.
- 9d ago First seen · 72 lines · 39 tokens per session scan A c6290e9924f1
social-media-manager is an agent published in the GitHub repository The-AI-Directory-Company/agents-and-skills (2 stars, last pushed 5mo ago), licensed MIT. It adds 39 tokens to every session and 1,347 once invoked, about $0.0002 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 2026-09-03.
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