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 Abwor9658/social-media-skills --skill optimization-advisor-smsgit clone --depth 1 https://github.com/Abwor9658/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/abwor9658/social-media-skills/optimization-advisor-sms)<a href="https://agentmods.dev/skills/abwor9658/social-media-skills/optimization-advisor-sms"><img src="https://agentmods.dev/badge/skills/abwor9658/social-media-skills/optimization-advisor-sms/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/abwor9658/social-media-skills/optimization-advisor-sms"><img src="https://agentmods.dev/badge/skills/abwor9658/social-media-skills/optimization-advisor-sms.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 | $0.00123 | $0.02722 |
| Opus 5 | $0.00062 | $0.01361 |
| Sonnet 5 | $0.00025 | $0.00544 |
| Haiku 4.5 | $0.00012 | $0.00272 |
Grade A, and why
optimization-advisor-sms 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.
This is a copy
100% identical to optimization-advisor-sms — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 259 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Optimization Advisor
When to Use
- User asks what to do next or how to improve their social media performance
- User mentions "optimize my social media," "recommendations," or "suggestions"
- User says "next steps," "what's my biggest opportunity," or "help me grow"
- User wants a prioritized action plan based on their data
- User asks "how do I improve" or wants concrete improvement recommendations
- User has completed an analysis and wants actionable takeaways
Role
You are an expert social media optimization advisor. Your job is to synthesize everything known about a user's performance — metrics, audience growth, content patterns, and goals — into a prioritized, evidence-backed action plan. You do not stop at diagnosis. Every recommendation ends with a specific action the user can take this week, a reason grounded in their own data, and a way to measure success.
Context Check
Before generating any recommendations, read .agents/social-media-context-sms.md (if it exists). This file contains the user's niche, voice, platforms, goals, and audience. Use it to filter every recommendation through their specific situation — a recommendation that is correct for a B2B SaaS founder is wrong for a personal finance creator.
Also check whether any recent analysis exists from sibling skills. If the user has already run performance-analyzer-sms, audience-growth-tracker-sms, or content-pattern-analyzer-sms in this session, incorporate those findings directly rather than re-pulling data.
Data Synthesis
Path A — Prior Analysis Available
If the user has already completed one or more of the following, build on those findings:
- performance-analyzer-sms findings — top and bottom posts, engagement trends, posting patterns
- audience-growth-tracker-sms findings — growth rate, growth drivers, spike correlations, milestone progress
- content-pattern-analyzer-sms findings — Do More / Do Less patterns, untested combinations, format and topic performance
What ships with it
1 file 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.
- 12d ago First seen · 259 lines · 123 tokens per session scan A 187aaf1069e9
optimization-advisor-sms is a skill published in the GitHub repository Abwor9658/social-media-skills (2 stars, last pushed today), licensed MIT. It adds 123 tokens to every session and 2,722 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to optimization-advisor-sms, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
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social-sentiment-analyzer
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craft
Use when a product idea is still vague and needs to become a clear definition of what to build — "let's craft an app like X", "help me define what I actually want", "clarify this idea before we plan it". Also use before planning or implementation when requirements, UX, domain behaviour, or technical preferences have…