
Content Planner
- 161 installs
- 194 repo stars
- Updated January 23, 2026
- bradautomates/head-of-content
Plan editorial calendars, pillar topics, channel mix, and production timelines aligned to audience goals and measurable growth KPIs.
About
content-planner skill from bradautomates/head-of-content helps operators design a strategic content program: audience-aligned topic clusters, channel calendars, repurposing workflows, KPI targets, and production checkpoints for consistent organic growth.
- Builds editorial calendars with themes and deadlines
- Maps content pillars to funnel stages and CTAs
- Balances formats across blog, social, email, and video
- Ties topics to SEO intent and distribution channels
Content Planner by the numbers
- 161 all-time installs (skills.sh)
- Ranked #1,025 of 1,879 Marketing & SEO skills by installs in the Skillselion catalog
- Data as of Aug 5, 2026 (Skillselion catalog sync)
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| Installs | 161 |
|---|---|
| repo stars | ★ 194 |
| Last updated | January 23, 2026 |
| Repository | bradautomates/head-of-content ↗ |
What it does
Plan editorial calendars, pillar topics, channel mix, and production timelines aligned to audience goals and measurable growth KPIs.
Files
Content Planner
Orchestrate parallel research across X, Instagram, YouTube, and TikTok, then aggregate findings into content ideas and platform-specific playbooks.
Prerequisites
Same as individual research skills:
APIFY_TOKENfor X, Instagram, and TikTok researchTUBELAB_API_KEYfor YouTube researchGEMINI_API_KEYfor video analysis- Accounts configured in
.claude/context/for each platform
CRITICAL - Subagent Environment Setup: Each subagent must load environment variables from the .env file in the head-of-marketing working directory before executing any API calls:
export $(cat .env | grep -v '^#' | xargs)Workflow
1. Read User Context
Read all files in .claude/context/ to understand the user's niche, target audience, and accounts to research. Pass this context to each subagent.
2. Create Master Run Folder
RUN_FOLDER="content-plans/$(date +%Y-%m-%d_%H%M%S)" && mkdir -p "$RUN_FOLDER" && echo "$RUN_FOLDER"3. Launch Research Subagents in Parallel
Use the Task tool to launch 4 subagents simultaneously:
Subagent 1 - X Research:
Execute the x-research skill:
1. Create run folder in x-research/
2. Fetch tweets (30 days, 100 max per account)
3. Analyze for outliers
4. Run video analysis if video content found
5. Generate report
Return: The run folder path and a JSON summary with:
- run_folder: path to the run folder
- total_posts: number analyzed
- outlier_count: outliers found
- top_topics: top 5 hashtags/keywordsSubagent 2 - Instagram Research:
Execute the instagram-research skill:
1. Create run folder in instagram-research/
2. Fetch reels (30 days, 50 per account)
3. Analyze for outliers
4. Run video analysis on top 5
5. Generate report
Return: The run folder path and a JSON summary with:
- run_folder: path to the run folder
- total_posts: number analyzed
- outlier_count: outliers found
- top_topics: top 5 hashtags/keywordsSubagent 3 - YouTube Research:
Execute the youtube-research skill:
1. Read channel context from .claude/context/youtube-channel.md
2. Analyze channel for keywords
3. Search for outliers
4. Filter to top 3 relevant videos
5. Run video analysis
6. Generate report
Return: The run folder path and a JSON summary with:
- run_folder: path to the run folder
- total_videos: number analyzed
- outlier_count: outliers found
- top_topics: top 5 keywordsSubagent 4 - TikTok Research:
Execute the tiktok-research skill:
1. Create run folder in tiktok-research/
2. Fetch videos (30 days, 50 per account)
3. Analyze for outliers
4. Run video analysis on top 5
5. Generate report
Return: The run folder path and a JSON summary with:
- run_folder: path to the run folder
- total_videos: number analyzed
- outlier_count: outliers found
- top_topics: top 5 hashtags/sounds/keywords4. Collect Research Results
After all subagents complete, read from each platform's latest run folder:
x-research/{latest}/
├── outliers.json
└── video-analysis.json (if exists)
instagram-research/{latest}/
├── outliers.json
└── video-analysis.json
youtube-research/{latest}/
├── outliers.json
└── video-analysis.json
tiktok-research/{latest}/
├── outliers.json
└── video-analysis.json5. Generate Content Ideas
Read references/content-ideas-template.md for the full template structure.
Key aggregation tasks: 1. Extract topics from each platform's outliers 2. Cross-reference to find topics appearing on multiple platforms 3. Identify X-sourced emerging ideas (high X engagement, low presence elsewhere) 4. Calculate opportunity scores for X ideas:
opportunity_score = (x_engagement × 1.5) / (instagram_saturation + youtube_saturation + tiktok_saturation + 1)instagram_saturation: 0 (not present), 0.5 (low), 1 (medium), 1.5 (high)youtube_saturation: same scaletiktok_saturation: same scale
5. Generate 2-week calendar with platform-specific content suggestions
Write to: {RUN_FOLDER}/content-ideas.md
6. Generate Platform Playbooks
For each platform, read references/playbook-template.md and generate:
{RUN_FOLDER}/x-playbook.md{RUN_FOLDER}/instagram-playbook.md{RUN_FOLDER}/youtube-playbook.md{RUN_FOLDER}/tiktok-playbook.md
Each playbook extracts from the platform's research:
- Winning hooks with replicable formulas (from video-analysis.json)
- Format analysis and content patterns
- Content structure breakdowns
- CTA strategies
- Trending topics and hashtags
- Top 15 outliers with analysis
- Actionable takeaways
7. Present Summary
Output to user:
- Total content analyzed across all platforms
- Number of outliers identified per platform
- Key cross-platform insights (2-3 bullets)
- Top 3 emerging ideas from X
- Links to all generated files
Output Structure
content-plans/
└── {YYYY-MM-DD_HHMMSS}/
├── content-ideas.md # Cross-platform ideas (X-primary)
├── x-playbook.md # X/Twitter intelligence playbook
├── instagram-playbook.md # Instagram intelligence playbook
├── youtube-playbook.md # YouTube intelligence playbook
└── tiktok-playbook.md # TikTok intelligence playbookCross-Platform Topic Matching
To identify cross-platform winners:
1. Extract keywords/hashtags from each platform's outliers 2. Normalize terms (lowercase, remove # and @) 3. Find intersection of high-frequency terms 4. Score by combined engagement across platforms
Quick Reference
Full orchestration: 1. Create master run folder 2. Launch 4 research subagents in parallel (Task tool with 4 invocations) 3. Wait for all subagents to complete 4. Read all outliers.json and video-analysis.json files 5. Generate content-ideas.md using cross-platform analysis 6. Generate 4 platform playbooks 7. Present summary to user
Content Ideas Template
Use this template structure when generating content-ideas.md.
# Content Ideas
Generated: {date}
Research window: Last 30 days
## Executive Summary
- **Total posts analyzed**: {sum across platforms}
- **Total outliers identified**: {sum}
- **Platforms covered**: X, Instagram, YouTube
---
## Top Content Ideas
### Priority Tier 1: Emerging Ideas (X-sourced)
Ideas from X that show high engagement but haven't saturated other platforms yet.
| Idea/Topic | X Engagement | Instagram Presence | YouTube Presence | Opportunity Score |
|------------|--------------|-------------------|------------------|-------------------|
| {topic} | {score} | Low/Medium/High | Low/Medium/High | {calculated} |
#### 1. {Topic Title}
- **Source Tweet**: @{username} - "{tweet excerpt}"
- **Why it's working**: {analysis}
- **Engagement proof**: {likes}L / {RTs}RT / {replies}R
- **Cross-platform potential**: {assessment}
- **Suggested angles**:
- {angle 1}
- {angle 2}
- {angle 3}
[Repeat for top 10 X-sourced ideas]
---
### Priority Tier 2: Cross-Platform Winners
Ideas performing well across multiple platforms (validated at scale).
| Topic | X Performance | IG Performance | YT Performance |
|-------|--------------|----------------|----------------|
| {topic} | {outlier?} | {outlier?} | {outlier?} |
#### 1. {Topic Title}
- **Platforms validated**: X, Instagram, YouTube
- **Best performing format per platform**:
- X: {format/style}
- IG: {format/style}
- YT: {format/style}
- **Combined engagement**: {total}
- **Why it resonates**: {analysis}
[Repeat for top 5 cross-platform ideas]
---
### Priority Tier 3: Platform-Specific Hits
Strong performers that work best on one platform.
#### Instagram-Native Ideas
[List top 3 with context]
#### YouTube-Native Ideas
[List top 3 with context]
---
## Trending Topics & Hashtags
### Cross-Platform Trending
| Topic | X Rank | IG Rank | YT Rank |
|-------|--------|---------|---------|
[Merged from all platforms]
### Platform-Specific Trends
#### X/Twitter
{Top hashtags and keywords from outliers}
#### Instagram
{Top hashtags and keywords from outliers}
#### YouTube
{Top keywords and topics from outliers}
---
## Content Calendar Suggestions
Based on identified topics, here's a suggested 2-week content calendar:
| Day | Platform | Content Idea | Format | Hook Formula |
|-----|----------|--------------|--------|--------------|
| Mon | X | {idea} | Thread | {hook} |
| Tue | IG Reels | {idea} | Tutorial | {hook} |
| Wed | YouTube | {idea} | Short | {hook} |
[Continue for 2 weeks]
---
## Data Sources
- X Research: {run_folder} ({outlier_count} outliers from {total} posts)
- Instagram Research: {run_folder} ({outlier_count} outliers from {total} posts)
- YouTube Research: {run_folder} ({outlier_count} outliers from {total} videos)Opportunity Score Calculation
For X-sourced ideas:
opportunity_score = (x_engagement × 1.5) / (instagram_saturation + youtube_saturation + 1)Where:
x_engagement= normalized engagement rate on X (0-10 scale based on outlier percentile)instagram_saturation:- 0 = not present in Instagram outliers
- 0.5 = low (mentioned in 1-2 outliers)
- 1.0 = medium (3-5 outliers)
- 1.5 = high (6+ outliers)
youtube_saturation= same scale
Higher score = more opportunity (high engagement, low saturation elsewhere).
Cross-Platform Topic Matching
1. Extract all keywords/hashtags from each platform's outliers 2. Normalize: lowercase, remove # and @, stem common variations 3. Find terms appearing in 2+ platforms 4. Rank by combined engagement across platforms
Platform Playbook Template
Use this template structure when generating {platform}-playbook.md.
# {Platform} Intelligence Playbook
Generated: {date}
Analysis period: Last 30 days
## Quick Stats
| Metric | Value |
|--------|-------|
| Posts analyzed | {total} |
| Outliers identified | {count} |
| Outlier rate | {percentage}% |
| Accounts tracked | {count} |
---
## Winning Hooks
Ranked by engagement. These formulas are proven to capture attention.
### Hook #1: {technique_name}
- **Creator**: @{username}
- **Opening line**: "{exact opening}"
- **Why it works**: {attention_grab analysis}
- **Replicable formula**: {template formula}
- **Engagement**: {metrics}
- **Link**: {url}
**How to use this hook:**
1. {Step 1}
2. {Step 2}
3. {Step 3}
**Variations to try:**
- "{variation 1}"
- "{variation 2}"
[Repeat for top 5-10 hooks]
---
## Content Formats That Win
### Format Distribution in Outliers
| Format | Count | % of Outliers | Avg Engagement |
|--------|-------|---------------|----------------|
| {format} | {n} | {%} | {avg} |
### Top Performing Formats
#### 1. {Format Name}
**What it is:** {description}
**Why it works:** {analysis}
**Best practices:**
- {tip 1}
- {tip 2}
- {tip 3}
**Example:** @{username} - {description}
**Engagement:** {metrics}
[Repeat for top 5 formats]
---
## Content Structure Patterns
### Pacing Breakdown
| Video/Post | Format | Pacing | Retention Techniques |
|------------|--------|--------|---------------------|
| @{username} | {format} | {pacing} | {techniques} |
### Successful Structures
#### Pattern 1: {Pattern Name}
[Opening: 0-3s] - {what happens} [Hook: 3-7s] - {what happens} [Value: 7-45s] - {what happens} [CTA: 45-60s] - {what happens}
**Used by:** @{username1}, @{username2}
**Success rate:** {x}% of outliers use this pattern
[Repeat for top 3 patterns]
---
## CTA Strategies
| Video | CTA Type | CTA Text | Placement | Result |
|-------|----------|----------|-----------|--------|
| @{username} | {type} | "{text}" | {placement} | {engagement} |
### Most Effective CTAs
1. **{CTA Type}** - "{example text}"
- Placement: {where}
- Why it works: {analysis}
[Repeat for top 5 CTA types]
---
## Trending Topics & Hashtags
### Top Hashtags
| Rank | Hashtag | Frequency | Avg Engagement |
|------|---------|-----------|----------------|
| 1 | #{tag} | {count} | {avg} |
### Top Keywords
| Rank | Keyword | Frequency | Context |
|------|---------|-----------|---------|
| 1 | {keyword} | {count} | {how used} |
{Platform-specific additions: sounds for TikTok, threads for X, etc.}
---
## Top Outlier Posts
### #1: @{username}
> {post content or title}
| Metric | Value |
|--------|-------|
| {metric1} | {value} |
| {metric2} | {value} |
| Engagement Rate | {rate}% |
| Engagement Score | {score} |
**Why it worked:** {analysis}
**Link:** {url}
[Repeat for top 15 outliers]
---
## Actionable Takeaways
Based on this analysis, here are specific actions to implement:
### Immediate Actions (This Week)
1. **{Action}**: {specific details}
2. **{Action}**: {specific details}
3. **{Action}**: {specific details}
### Content Strategy Adjustments
1. **{Strategy shift}**: {details}
2. **{Strategy shift}**: {details}
### Hooks to Test
1. "{Hook formula 1}"
2. "{Hook formula 2}"
3. "{Hook formula 3}"
---
## Accounts Analyzed
| Account | Follower Count | Posts Scraped | Outliers |
|---------|---------------|---------------|----------|
| @{username} | {followers} | {count} | {outliers} |
---
## Research Metadata
- **Run folder**: {path}
- **Outlier threshold**: {threshold} std dev
- **Days analyzed**: {days}
- **Video analysis**: {yes/no, count}Platform-Specific Sections
X/Twitter Additions
- Thread analysis (if applicable)
- Quote tweet patterns
- Media vs text-only breakdown
Instagram Additions
- Audio/sound trends (for Reels)
- Caption length analysis
- Carousel vs single post performance
YouTube Additions
- Thumbnail analysis notes
- Title formula patterns
- Video length correlation with performance