charlie947/social-media-skills is a collection of markdown instructions that gives AI agents specialized workflows for creating and managing social-media content. It supports a content system spanning LinkedIn, Instagram, Substack, X, and YouTube, with shared voice and context files guiding the individual skills.
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 charlie947/social-media-skills --skill pinned-commentgit clone --depth 1 https://github.com/charlie947/social-media-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/charlie947/social-media-skills/pinned-comment)<a href="https://agentmods.dev/skills/charlie947/social-media-skills/pinned-comment"><img src="https://agentmods.dev/badge/skills/charlie947/social-media-skills/pinned-comment/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/charlie947/social-media-skills/pinned-comment"><img src="https://agentmods.dev/badge/skills/charlie947/social-media-skills/pinned-comment.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector pass
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 | $0.00068 | $0.01545 |
| Opus 5 | $0.00034 | $0.00772 |
| Sonnet 5 | $0.00014 | $0.00309 |
| Haiku 4.5 | $0.00007 | $0.00154 |
Grade A, and why
pinned-comment 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 13d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- pinned-comment — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 147 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LinkedIn Pinned Comment + Image Prompt Skill
Why This Skill Exists
The post delivers value. The pinned comment builds personality, trust, and rewatch value. It is where Charlie drops the polished creator mask and talks like a real person.
Funny is subjective and easy to miss. This skill exists to make hilarious pinned comments REPEATABLE so anyone on the team (Smriti, Ansh, etc.) can produce them at Charlie's standard.
The Core Insight (read this first)
The image carries the joke. The comment captions the image.
If the comment makes sense without the image, the comment is doing too much work. If the image needs the comment to be funny, the image is too weak.
This is why image generation comes FIRST. Always.
THE PROCESS (follow in order)
Step 1. Find the admission
Every Charlie post hides one quiet confession. Examples:
- "Cowork does most of my actual job now"
- "I am embarrassingly dependent on Anthropic"
- "I gave away a 9-month product for free"
- "I am a sponsored creator who lost objectivity"
Write the admission as one sentence before doing anything else. If you cannot name the admission in one sentence, stop. The post is not pinned-comment material yet.
Step 2. Build the image first
Three rules for the image:
- One clear visual gag. The eye lands on it in under a second. Examples that worked: tie draped on a laptop keyboard, a shrine to Anthropic with a rose and candles, a banquet table where every other seat is a tech logo.
- Played completely straight. No winking. No thumbs up. No exaggerated faces. The humour comes from treating the absurd as normal.
- Charlie is the lower-status figure. Always. Claude wins. The logo wins. The mum wins. Charlie loses with quiet dignity.
Use the standard format:
"Using the person in the attached reference image, create a photorealistic image of [scene]. [One clear visual gag described in detail]. [Charlie's posture and expression, played straight]. [Lighting and framing notes]."
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.
- 13d ago First seen · 147 lines · 68 tokens per session scan A 6b8ce5659538
pinned-comment is a skill published in the GitHub repository charlie947/social-media-skills (3,385 stars, last pushed 13d ago), licensed MIT. It adds 68 tokens to every session and 1,545 once invoked, about $0.0003 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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