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Get Started Free →blacktwist/optimization-advisor-sms
When the user wants concrete recommendations on how to improve their social media performance. Also use when the user mentions 'what should I do next,' 'how do I improve,' 'optimize my social media,' 'recommendations,' 'suggestions,' 'next steps,' 'what's my biggest opportunity,' or 'help me grow.' Synthesizes insights from performance, audience, and pattern analysis into prioritized actions. For raw analytics, see performance-analyzer-sms. For growth tracking, see audience-growth-tracker-sms. F
Passed 18 of 21 test cases with the skill, and 9 of 21 without it.
and 14 more in the full report
10 fixed9 passed either way3 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 10 test cases the skill fixed. Same model, same prompt, with and without the skill.
My data shows that asking a question at the end of LinkedIn posts increases comments from 4 to 18 per post across my last 12 updates. Write a single quick-win action plan item for this.
| Checked | Without skill | With skill |
|---|---|---|
| Includes the action, data evidence, expected impact, and measurement approach for the recommendation. | Missed | Passed |
| Specifies a metric and time window in the measurement section. | Missed | Passed |
The instructions your model reads when the skill loads.
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.
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.
If the user has already completed one or more of the following, build on those findings:
Pull these together into a unified picture. Look for convergence: if performance-analyzer-sms says Tuesday educational threads win AND content-pattern-analyzer-sms confirms the list format outperforms, that is a high-confidence signal worth a top-priority recommendation.
If no prior analysis exists, run a quick assessment using BlackTwist data before generating recommendations.
Pull in this order:
test cases passed, vs 9 / 21 without
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