---
name: blacktwist/content-pattern-analyzer-sms
source: https://app.decimal.ai/s/blacktwist-content-pattern-analyzer-sms@1/SKILL.md
source_sha256: 76469492cc34
---

# 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** (reach without resonance) vs. **low impressions but high engagement** (resonating with a smaller audience)
- Any **pillar gaps** — topics the audience likely cares about (based on context file) that the user hasn't posted on yet

**Example topic breakdown:**

```
Pillar: Productivity Tips
Posts: 12 | Avg ER: 6.1% (vs. 3.8% baseline)
Top post: "3 tools that cut my content time in half" (9.2% ER)
Signal: Consistently outperforms — do more

Pillar: Company Updates
Posts: 8 | Avg ER: 1.4%
Top post: "We just launched v2.0" (2.1% ER)
Signal: Consistently underperforms — reframe or reduce
```

### 2. By Format

Compare performance across post formats (single post, thread, list, question, poll, image, video, carousel). Identify:

- Which **format drives the highest engagement rate** on average
- Which format drives the most **saves** (lasting-value indicator) vs. **reposts** (distribution indicator)
- Whether certain formats work better for certain topics — look for **format × topic combinations** that consistently overperform
- Any formats the user hasn't tested that their audience typically responds to

### 3. By Posting Time

Group posts by day of week and time of day. Identify:

- The **best-performing day(s)** by average engagement rate
- The **best-performing time windows** (morning, midday, evening, night) — use the user's local timezone from the context file
- Whether there is a **recency bias** (posts that went up recently look worse because they haven't had time to accumulate engagement) — flag this explicitly when it affects the analysis
- Any **consistently dead zones** — days or times that reliably underperform

### 4. By Length

Group posts into buckets: short (1–3 sentences / under 280 chars), medium (4–8 sentences), long (9+ sentences or multi-post threads). Identify:

- The **engagement rate sweet spot** for length across the user's audience
- Whether length interacts with format — long threads vs. long single posts may perform very differently
- Whether **short posts punch above their weight** on reposts (shareability) while long posts drive more saves (depth)

### 5. By Hook Type

Classify each post's opening line into hook patterns: question, bold claim, specific number/stat, personal story opening, contrarian take, how-to opener, list preview ("X things..."), direct address. Identify:

- Which **hook patterns drive the most engagement** across the dataset
- Whether certain hook types work better for certain topics or formats
- The user's **most-used hook type** — if they default to one pattern, flag that variety may unlock more reach
- Any **hook types not yet tested** that tend to perform well in their niche

### 6. By Tone

Classify posts by tone: educational/instructional, personal/vulnerable, storytelling, motivational, contrarian/opinion, promotional, conversational/playful. Identify:

- Which **tone resonates most** with the user's audience by engagement rate
- Whether **comments vs. saves vs. reposts** differ by tone (educational → saves; personal → comments; contrarian → reposts)
- Whether the user's dominant tone aligns with what their audience responds to, or if there is a mismatch worth addressing

### 7. By Platform

If the user posts on multiple platforms (Threads, X/Twitter, LinkedIn, Instagram, etc.):

- Compare **engagement rate for equivalent content** across platforms — same post or same topic
- Identify which platform delivers **the highest return per post**
- Flag **format mismatches** — content designed for one platform that underperforms when cross-posted without adaptation
- Identify any **platform-specific patterns** (e.g., threads work better on X than Threads, educational posts outperform on LinkedIn)

---

## Cross-Platform Comparison

When the user posts across multiple platforms, run a dedicated cross-platform comparison after completing the dimension analysis:

1. Identify posts that were published on more than one platform
2. Compare engagement rate, save rate, and repost rate by platform for identical or near-identical content
3. Identify whether the user's **strongest platform aligns with their stated primary goal** (growth, engagement, conversion)
4. Flag if they are investing time in a platform that consistently underperforms relative to their other channels

---

## Content Gap Identification

After analyzing existing content, identify gaps — topics or formats the audience likely wants that the user has not tried:

- **Topic gaps**: Based on the context file (niche, audience, goals), are there obvious topics the user hasn't covered? Look for topics adjacent to their top-performing pillars.
- **Format gaps**: Are there formats the user hasn't tested (e.g., they only post threads but their audience saves image posts)? Check what performs in their niche generally.
- **Untested combinations**: High-performing pillar + high-performing format combinations the user hasn't tried (e.g., if "productivity tips" and "list format" each perform well but the user hasn't combined them)
- **Hook variety gaps**: If the user defaults to one hook type, flag 2–3 alternatives worth testing

Frame gaps as **experiments**, not failures. The user hasn't tested them yet — they are opportunities.

**Example content gap finding:**

```
Gap: "Productivity tips" (top pillar) + "carousel" (top format) = untested
Rationale: Your productivity content averages 6.1% ER and your carousels
average 5.8% ER — but you have never published a productivity carousel.
Experiment: Write 2 productivity carousels over the next 2 weeks and
compare ER against your baseline.
```

---

## Output: Do More / Do Less Report

Deliver findings in this structure. Do not bury patterns in data tables.

```
## Content Pattern Analysis — [Date Range]

**Posts analyzed:** [N]
**Your baseline engagement rate:** [X%]
**Analysis confidence:** [High / Medium / Low — based on sample size]

---

### Do More

[Top 3–5 patterns with specific evidence]

**Pattern:** [Name the pattern clearly — e.g., "Tuesday morning threads on productivity"]
**Evidence:** [Avg ER, number of posts, specific examples]
**Why it works:** [Your interpretation — be specific, not generic]

---

### Do Less

[Bottom 3–5 patterns with specific evidence]

**Pattern:** [Name the pattern — e.g., "Friday promotional posts"]
**Evidence:** [Avg ER, number of posts]
**Why it underperforms:** [Diagnosis — be direct but constructive]

---

### Experiment With

[2–4 untested combinations or gaps worth trying]

**Experiment:** [Specific combination to test]
**Rationale:** [Why this is likely to work, based on existing patterns]
**How to test:** [Specific suggestion — e.g., "Write 3 posts using X hook on Y topic and compare ER after 7 days"]

---

### Key Takeaway

[1–2 sentence summary of the single most important pattern shift the user should make]
```

Use **bold for key terms**. Write in active voice. Keep each pattern description under 4 sentences — specificity beats length.

---

## Boundaries

- Does not provide per-post metric breakdowns — see **performance-analyzer-sms** for individual post analysis
- Does not track follower growth or audience demographics — see **audience-growth-tracker-sms** for growth data
- Does not generate a prioritized action plan — see **optimization-advisor-sms** for concrete next steps
- Does not write or draft new content — see **post-writer-sms**, **thread-writer-sms**, or **carousel-writer-sms** for creation
- Does not execute code or access external APIs unless BlackTwist MCP is connected
- Does not work reliably with fewer than 10 posts — the skill requires a minimum sample size for pattern detection

## Related Skills

- **social-media-context-sms** — establish niche, voice, and goals before pattern analysis
- **performance-analyzer-sms** — get raw post metrics and individual post diagnoses
- **optimization-advisor-sms** — translate pattern findings into a concrete improvement plan