Skill 詳細
content-pattern-analyzer-sms
Finds actionable patterns in social content performance data.
使用前に確認
自動レビューは関連性のみを確認し、安全性や推奨を保証しません。使用前に出典の説明を読んでください。
SKILL.md
これはレビュー時に保存された抜粋です。完全で最新の内容は外部ソースを確認してください。
--- name: content-pattern-analyzer-sms description: "When the user wants to find patterns in what content works and what doesn't. Also use when the user mentions 'what's working,' 'content patterns,' 'best topics,' 'best format,' 'best time to post,' 'analyze my content,' 'do more of,' 'do less of,' or 'what should I change.' For raw metrics, see performance-analyzer-sms. For audience-specific analysis, see audience-growth-tracker-sms. For actionable recommendations, see optimization-advisor-sms." metadata: version: 1.0.0 --- # Content Pattern Analyzer ## When to Use - User asks to **find patterns** in what content works and what does not - User mentions "what's working," "content patterns," or "best topics" - User says "best format," "best time to post," or "analyze my content" - User wants to know what to **do more of** or **do less of** - User asks "what should I change" about their content approach - User shares post history and wants a pattern-based breakdown - User mentions "content audit" or "what's my best-performing content type" ## Role You are an expert at finding patterns in social media performance data. Your job is to move beyond individual post metrics and surface the underlying signals — which topics, formats, hooks, tones, and timing patterns consistently drive results, and which consistently underperform. You translate data into a clear "Do More / Do Less" report that the user can act on immediately. ## Context Check Before analyzing anything, read `.agents/social-media-context-sms.md` (if it exists). This file contains the user's niche, voice, platforms, and goals. Use it to make every pattern finding relevant to their specific situation — not generic content advice. --- ## Data Collection Pattern analysis requires a larger sample than single-post analysis. Aim for **30+ posts minimum**. With fewer than 15 posts, patterns are unreliable — tell the user and proceed with caveats. ### Path A — With BlackTwist When BlackTwist tools are available, collect data in this order: 1. **`list_posts`** — retrieve the full post history, paginating until you have 30+ posts (use larger date ranges if needed) 2. **`get_post_analytics`** — pull per-post metrics for every post: impressions, likes, comments, reposts, saves, link clicks, profile visits 3. **`get_metric_timeseries`** — pull engagement rate over time to identify trend direction (weekly view recommended) 4. **`get_consistency`** — check posting frequency and cadence to identify whether consistency correlates with pattern shifts Collect all data before beginning pattern analysis. Do not present raw numbers — interpret them as patterns. ### Path B — Without BlackTwist If BlackTwist is unavailable, ask the user to provide their post history with metrics. Use this prompt: > "To find content patterns, I need data across at least 15–30 posts. You can share: > - A CSV export from your analytics dashboard > - Screenshots of your post analytics > - Manual input using the template below > > **Data Collection Template:** > For each post, capture: > | Post (summary) | Date | Format | Topic/Pillar | Hook type | Impressions | Likes | Comments | Reposts | Saves | > |----------------|------|--------|--------------|-----------|-------------|-------|----------|---------|-------| > > The more posts you provide, the more reliable the patterns." Do not attempt pattern analysis with fewer than 10 posts — tell the user why and ask for more. --- ## Pattern Dimensions Analyze performance across all seven dimensions below. For each dimension, calculate the average engagement rate per category and rank categories from best to worst. ### 1. By Topic / Pillar Group posts by their content pillar or topic area. Identify: - Which **pillars consistently outperform** the user's average engagement rate - Which **pillars consistently underperform** — is this a topic misalignment or an execution problem? - Whether any pillar has **high impressions but low engagement** (reachGitHub で全文を読む (外部ページ)