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 profile-optimizergit 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/profile-optimizer)<a href="https://agentmods.dev/skills/charlie947/social-media-skills/profile-optimizer"><img src="https://agentmods.dev/badge/skills/charlie947/social-media-skills/profile-optimizer/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/profile-optimizer"><img src="https://agentmods.dev/badge/skills/charlie947/social-media-skills/profile-optimizer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Memory Poisoning · line 255 Skill attempts to fill the context window with filler content, displacing legitimate instructions and safety constraints. This can degrade agent performance or bypass safety boundaries.Fix: Implement context-window management that detects and rejects padding or stuffing attempts. Prioritize system instructions over user-injected content.
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 | $0.00114 | $0.02299 |
| Opus 5 | $0.00057 | $0.01149 |
| Sonnet 5 | $0.00023 | $0.00460 |
| Haiku 4.5 | $0.00011 | $0.00230 |
Grade A, and why
profile-optimizer 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:
- profile-optimizer — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 264 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Profile Optimizer
CRITICAL: Auto-start on load
When this skill triggers, go straight to Step 1. Do not summarise. Do not explain what you will produce. Start input gathering immediately.
Step 1. Gather inputs
Check the project for about-me.md. If it exists, pre-fill name, audience, topics, and POV from it. Skip those questions and tell the user what you pulled.
Call AskUserQuestion in two batches.
Batch 1
[
{
"question": "What is the primary goal of your LinkedIn presence?",
"header": "Goal",
"multiSelect": false,
"options": [
{"label": "Booked calls", "description": "Drive discovery calls or demos"},
{"label": "Inbound leads", "description": "Attract prospects who reach out to you"},
{"label": "Newsletter subscribers", "description": "Grow your email list from LinkedIn"},
{"label": "Job opportunities", "description": "Get recruiters and hiring managers to reach out"}
]
},
{
"question": "What is your main offer or service?",
"header": "Offer",
"multiSelect": false,
"options": [
{"label": "Coaching", "description": "1-on-1 or group coaching"},
{"label": "Consulting", "description": "Advisory or strategy work"},
{"label": "Agency services", "description": "Done-for-you services for clients"},
{"label": "Freelance", "description": "Project-based or contract work"}
]
},
{
"question": "Do you have brand colours (hex codes)?",
"header": "Colours",
"multiSelect": false,
"options": [
{"label": "No, suggest for me", "description": "Pick colours based on my positioning"},
{"label": "Yes, I will paste them", "description": "I have specific hex codes to use"}
]
},
{
"question": "Any social proof you want highlighted?",
"header": "Proof",
"multiSelect": false,
"options": [
{"label": "Years of experience", "description": "e.g. 10+ years in marketing"},
{"label": "Client results", "description": "e.g. Helped 200+ clients"},
{"label": "Media features", "description": "e.g. Featured in Forbes"},
{"label": "I will type my own", "description": "Let me paste specific proof points"}
]
}
]
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 · 264 lines · 114 tokens per session scan A 60df83fae4ac
profile-optimizer is a skill published in the GitHub repository charlie947/social-media-skills (3,385 stars, last pushed 13d ago), licensed MIT. It adds 114 tokens to every session and 2,299 once invoked, about $0.0006 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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