• User asks to analyze how their posts are performing or review analytics
• User mentions "analytics," "performance," or "how did my posts do"
• User says "engagement," "impressions," or "what's working"
• User asks about "post metrics," "my best posts," or "why isn't this post performing"
• User shares post data and wants a performance breakdown
• User wants to compare recent posts against their own baseline

1. list_posts

   — retrieve recent posts to establish the analysis window (default: last 30 days or last 20 posts, whichever is larger)

2. get_post_analytics

   — pull per-post metrics: impressions, likes, comments, reposts, saves, link clicks, profile visits

3. get_live_metrics

   — check current real-time performance for any posts still gaining traction

4. get_metric_timeseries

   — pull engagement rate and impressions over time to identify trends (weekly view recommended)

5. get_daily_recap

   — surface any anomaly days (unusually high or low performance)

6. get_consistency

   — check posting frequency and whether consistency correlates with performance shifts

"To analyze your performance, I need your post metrics. You can share:

• A screenshot of your analytics dashboard
• A CSV export from your platform
• Manual input using the template below

Data Collection Template: For each post (last 14–30 days), collect:

Post	Date	Impressions	Likes	Comments	Reposts	Saves	Link Clicks	Profile Visits

The minimum needed for a useful analysis: impressions + likes + comments for at least 5 posts."

• Impressions — total times the post appeared in feeds (includes repeats)
• Reach — unique accounts who saw the post
• Profile visits from post — how many viewers clicked through to learn more

• Likes — passive positive signal
• Comments — active engagement; higher weight than likes
• Reposts / shares — distribution signal; the most valuable organic action
• Saves — intent to return; strong indicator of lasting value
• Engagement rate — calculate as:

  (likes + comments + reposts + saves) / impressions × 100

• Link clicks — traffic signal; only relevant when a link is present
• DMs from post — often untracked but worth asking the user about
• Follows from post — net new audience directly attributable to the content

• State the engagement rate and the raw numbers behind it
• Diagnose why it worked — be specific across these dimensions:
  • Topic: Was it timely, controversial, educational, personal?
  • Format: Thread, single post, list, story, data-driven?
  • Hook: What did the first line do? Which hook pattern?
  • Timing: Day of week, time of day — any pattern?
  • Call to action: Did it invite a specific response?

Post: "7 writing habits that doubled my output" (March 12, 9:14 AM)
ER: 8.4% (vs. 2.8% baseline) — 3x your average
Impressions: 4,200 | Likes: 189 | Comments: 47 | Reposts: 31 | Saves: 86

Why it worked:
- Hook: List preview pattern ("7 habits...") — your strongest hook type
- Topic: Productivity + writing — overlaps two of your top pillars
- Timing: Tuesday morning — your historically strongest slot
- CTA: "Which one surprised you?" — drove 47 comments

• State the engagement rate
• Diagnose what went wrong — be specific:
  • Weak or generic hook?
  • Topic misaligned with audience interest?
  • Posted at an off-peak time?
  • Format mismatch for the platform?
  • Too promotional or self-serving?

• Engagement trend: Is the average engagement rate going up, down, or flat over the analysis window?
• Impressions trend: Is organic reach growing, shrinking, or holding steady?
• Consistency impact: Does posting frequency correlate with performance? (More posts = more reach, or does quality drop when volume increases?)
• Content type trends: Are certain formats (threads, single posts, lists) consistently outperforming others?

Trend Summary (March 1–31):
- Engagement rate: 2.8% avg (down 22% from February's 3.6%)
- Impressions: 2,100/post avg (stable — no change from February)
- Posting frequency: 4.2x/week (up from 3.1x/week in February)
- Diagnosis: Increased volume diluted quality. Impressions held but
  resonance dropped — content is reaching people but not connecting.

• Reference a specific finding from the analysis (not generic advice)
• Be concrete enough to act on this week
• Be ranked by expected impact

1. Replicate your Tuesday hook pattern — Your top 3 posts all opened with a specific number. Write your next 5 hooks using the statistic/data pattern.
2. Stop posting on Fridays — Your Friday posts average 1.8% ER vs. 5.2% on other days. Shift that content to Wednesday.
3. Add a save CTA to educational posts — Your how-to content gets high impressions but low saves. End with "Save this for later" and retest.

• Average engagement rate across all posts
• Average impressions per post
• Average comments per post

• Does not track follower growth or audience demographics — see audience-growth-tracker-sms for growth analysis
• Does not detect cross-post content patterns — see content-pattern-analyzer-sms for pattern detection across many posts
• Does not generate a prioritized action plan — see optimization-advisor-sms for concrete next steps
• Does not write or draft content — see post-writer-sms for content creation
• Does not execute code or access external APIs unless BlackTwist MCP is connected
• Does not cite industry benchmarks unless explicitly requested — all comparisons use the user's own averages

• social-media-context-sms — establish niche, voice, and goals before analyzing
• content-pattern-analyzer-sms — go deeper on what content patterns drive performance
• optimization-advisor-sms — translate analysis findings into a concrete improvement plan