From meta-skills
Ranks content angles by engagement data, competition level, and platform fit for keywords or products. Prioritizes ideas after trending-content-scout using weighted scores for optimal content selection.
npx claudepluginhub affitor/affiliate-skills --plugin meta-skillsThis skill uses the workspace's default tool permissions.
You have a keyword. You know the niche. But what specific content should you create?
Generates blog posts, landing pages, email sequences, social media content, and video scripts with quality audits, SEO optimization, and content calendars for business growth.
Plans content strategies by gathering business context, customer insights, and competitive analysis to prioritize searchable/shareable topics and formats driving traffic, authority, leads.
Plans content strategies including pillars, editorial calendars, keyword research by buyer stage, positioning, messaging hierarchies, SEO briefs, outlines, on-page optimization, and ROI measurement. Use for marketing content planning and research.
Share bugs, ideas, or general feedback.
You have a keyword. You know the niche. But what specific content should you create? Which angle, format, and hook will actually perform? This skill answers that question with data — not gut feeling.
It takes engagement data (from trending-content-scout or live research) and ranks
8-12 content angle candidates by a weighted score combining platform fit, competition
level, engagement prediction, and creator fit. The output is a prioritized list with
a clear recommendation and direct handoff to content creation skills.
Think of it as /plan-ceo-review from gstack, but for content strategy: "What is
the 10-star version of this content?" — except the answer is backed by engagement data.
This skill belongs to Stage S1: Research — but it bridges directly into S2: Content Creation.
trending-content-scout ran — use its data to pick the best anglekeyword: string # (required if no scout_data) "AI video tools"
product: object # (optional) Affiliate product being promoted
name: string # "HeyGen"
description: string # What it does
url: string # Product URL or affiliate link
reward_value: string # Commission info — never shown in content
platform: string # (required) Target platform for content creation
# "youtube" | "tiktok" | "linkedin" | "x" | "reddit" | "blog"
creator_strengths: string[] # (optional) What the user is good at
# "storytelling" | "technical" | "humor" | "authority" |
# "visual" | "data" | "personal_experience"
audience: string # (optional) Target audience — "beginners", "developers", "small business owners"
time_budget: string # (optional) "30min" | "2hours" | "1day" — affects difficulty filter
custom_angles: string[] # (optional) User's own angle ideas to include in ranking
Auto-detection: If trending-content-scout ran earlier in the conversation,
its output is automatically used as the data foundation. No need to pass it explicitly.
If trending-content-scout output exists in context:
pattern_analysis (winning formats, hooks, engagement benchmarks)content_gaps as angle candidatestop_content for competition assessmentIf no scout data: Run a quick scout internally:
web_search "[keyword] site:youtube.com" → top 10 videos, note formats and view countsweb_search "[keyword] site:tiktok.com" OR web_search "[keyword] tiktok viral" → top TikTok contentweb_search "[keyword] site:reddit.com top" → top Reddit discussionsweb_search "[keyword] [platform] best performing" → meta-analysis of what worksThis takes 30-60 seconds and provides enough signal for angle scoring.
Generate 8-12 specific content angle candidates. Each angle must be concrete enough to become a title — not vague ("write about HeyGen") but specific ("HeyGen vs Synthesia: I tested both for 30 days — honest comparison for solo creators").
Sources for angles:
Gap-based angles (from scout data or web_search):
Pattern-based angles (from winning formats):
Contrarian angles:
User-provided angles (from custom_angles):
For each angle, define:
Angle:
title: string # Specific, could be an actual content title
angle: string # Brief description of the angle
format: string # "comparison" | "review" | "tutorial" | "listicle" | "demo" | "story" | "reaction" | "explainer"
hook: string # The actual hook/opening line
hook_type: string # "question" | "shock" | "bold_claim" | "demo_first" | "relatable" | "contrarian"
source: string # "gap" | "pattern" | "contrarian" | "user_provided"
Score every angle on 4 dimensions (1-10 each), then calculate a weighted total:
angle_score = (platform_fit × 0.25) + (competition_level × 0.30) +
(engagement_prediction × 0.30) + (creator_fit × 0.15)
Dimension 1: Platform Fit (weight: 25%)
How well does this format/hook work on the target platform?
| Format | YouTube | TikTok | X | Blog | ||
|---|---|---|---|---|---|---|
| comparison | 9 | 8 | 7 | 5 | 8 | 9 |
| review | 8 | 6 | 5 | 4 | 9 | 9 |
| tutorial | 9 | 7 | 6 | 3 | 7 | 10 |
| listicle | 7 | 8 | 9 | 8 | 6 | 8 |
| demo | 8 | 10 | 5 | 4 | 3 | 5 |
| story | 6 | 9 | 10 | 8 | 7 | 7 |
| reaction | 7 | 10 | 4 | 6 | 5 | 3 |
| explainer | 8 | 5 | 8 | 6 | 8 | 9 |
Adjust based on actual scout data if available (if comparisons outperform on a platform where they usually don't, use the real data instead of the default table).
Dimension 2: Competition Level (weight: 30%)
How many similar content pieces already exist? Higher score = LESS competition.
IF scout data available:
Count how many top_content pieces match this angle's format + similar topic
10 = zero similar content found (blue ocean)
7-9 = 1-3 similar pieces (low competition)
4-6 = 4-10 similar pieces (moderate competition)
1-3 = 10+ similar pieces (saturated)
IF no scout data:
web_search for the exact angle title → count results
Fewer results with exact match = higher score
Dimension 3: Engagement Prediction (weight: 30%)
How likely is this angle to get high engagement based on data?
IF scout data available:
Look at engagement scores of similar formats and hooks in top_content
If this angle's format has avg_engagement > median → higher score
If this angle's hook_type has avg_engagement > median → higher score
Combine: angle uses top format + top hook → 9-10
Angle uses average format + average hook → 5-6
Angle uses underperforming format → 3-4
IF no scout data:
Use platform defaults and general engagement patterns
Comparisons generally outperform reviews → 8 vs 6
Bold claim hooks generally outperform questions → 8 vs 6
Dimension 4: Creator Fit (weight: 15%)
How well does this angle match the creator's strengths?
IF creator_strengths provided:
"storytelling" → story format, relatable hooks → high fit
"technical" → tutorial format, demo hooks → high fit
"humor" → reaction format, relatable hooks → high fit
"authority" → review format, bold claim hooks → high fit
"visual" → demo format, demo_first hooks → high fit
"data" → comparison format, explainer → high fit
"personal_experience" → story format, reaction → high fit
Match count: 2+ matches → 9-10, 1 match → 6-7, 0 matches → 4-5
IF no creator_strengths:
Default all angles to 7 (neutral)
Sort angles by angle_score descending.
For each angle, estimate:
difficulty: string # "easy" | "medium" | "hard"
estimated_time: string # "30 min" | "1-2 hours" | "half day" | "full day"
Difficulty mapping:
If time_budget is provided, flag angles that exceed the budget.
Before presenting output, verify:
If any check fails, fix the output before delivering. Do not flag the checklist to the user.
output_schema_version: "1.0.0"
keyword: string
platform: string
data_source: string # "trending-content-scout output" | "quick web_search scan"
angles_generated: number # 8-12
top_angle:
title: string
angle: string
format: string
hook: string
hook_type: string
score: number
why: string # data-backed reasoning
difficulty: string
estimated_time: string
all_angles:
- title: string
angle: string
format: string
hook: string
hook_type: string
platform_fit: number
competition_level: number
engagement_prediction: number
creator_fit: number
score: number
difficulty: string
estimated_time: string
source: string # "gap" | "pattern" | "contrarian" | "user_provided"
recommended_next_skill: string # "viral-post-writer" | "tiktok-script-writer" | etc.
recommended_skill_params: # ready-to-use parameters for the next skill
format: string
hook_style: string
angle: string
## Content Angle Ranker: [Keyword] on [Platform]
### Data Foundation
📊 Based on: [trending-content-scout output (20 pieces analyzed) | quick web_search scan]
---
### 🥇 #1 Recommended Angle — Score: [X.X]/10
**"[Specific Title]"**
| Dimension | Score | Evidence |
|-----------|-------|----------|
| Platform Fit | X/10 | [Format] works well on [Platform] — [data point] |
| Competition | X/10 | [Number] similar pieces exist — [assessment] |
| Engagement Prediction | X/10 | [Format] + [hook] averages [X] engagement in this niche |
| Creator Fit | X/10 | Matches your strengths in [X] |
| **Total** | **X.X/10** | |
- **Format:** [comparison] | **Hook:** [bold_claim]
- **Opening line:** "[Actual hook sentence]"
- **Difficulty:** [medium] | **Time:** [1-2 hours]
- **Why this wins:** [2-3 sentences of data-backed reasoning]
---
### 🥈 #2 — "[Title]" — Score: [X.X]/10
- Format: [X] | Hook: [X] | Competition: [X/10] | Time: [X]
- **Why:** [1 sentence]
### 🥉 #3 — "[Title]" — Score: [X.X]/10
- Format: [X] | Hook: [X] | Competition: [X/10] | Time: [X]
- **Why:** [1 sentence]
---
### All Angles Ranked
| # | Title | Format | Hook | Plat. Fit | Comp. | Eng. Pred. | Creator | Score | Time |
|---|-------|--------|------|-----------|-------|------------|---------|-------|------|
| 1 | ... | comparison | bold_claim | 9 | 8 | 9 | 8 | 8.7 | 2h |
| 2 | ... | demo | demo_first | 10 | 7 | 8 | 7 | 8.0 | 1h |
| 3 | ... | story | relatable | 9 | 6 | 7 | 9 | 7.5 | 1h |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
---
### ⚡ Quick Win vs Best Bet
| Strategy | Angle | Score | Time | Best For |
|----------|-------|-------|------|----------|
| **Quick Win** | [Easiest high-scoring angle] | X.X | 30min | "I want to ship something today" |
| **Best Bet** | [Highest scoring angle] | X.X | 2h | "I want the best possible content" |
| **Contrarian** | [Highest-scoring contrarian] | X.X | Xh | "I want to stand out from everyone" |
---
### 🚀 Next Steps
**To create Angle #1:**
Skill: [viral-post-writer | tiktok-script-writer | affiliate-blog-builder] Parameters: product: [product name] format: [comparison] hook_style: [bold_claim] angle: "[specific angle description]" platform: [platform]
**Alternative paths:**
- `tiktok-script-writer` — for short-form video version of Angle #1
- `content-pillar-atomizer` — create a blog post, then atomize across all platforms
- `comparison-post-writer` — if the winning angle is a comparison
trending-content-scout first for data-backed scoring."Example 1:
User: "I want to promote HeyGen on TikTok. What angle should I use?"
→ keyword: "HeyGen", platform: "tiktok"
→ Quick scout: web_search "HeyGen tiktok" → mostly demo-first content, 30-45s
→ Generate 10 angles: "HeyGen vs Synthesia comparison", "I made a $2000 video for free with HeyGen",
"POV: your boss asks for a video and you use AI", "HeyGen for real estate agents", etc.
→ Top angle: "I replaced a $2000 video production with HeyGen" — Score: 8.7
(bold_claim hook, demo format, low competition on TikTok, high engagement predicted)
→ Next: tiktok-script-writer with hook_style: bold_claim, duration: 45s
Example 2: User: "Rank these content ideas for my YouTube channel about email marketing:
Example 3: User: "I'm good at storytelling and humor. What should I create about AI writing tools on LinkedIn?" → creator_strengths: ["storytelling", "humor"], platform: "linkedin" → Generate angles weighted toward story format → Top: "I let AI write my LinkedIn posts for a week. My boss noticed." — Score: 9.1 (story format, relatable hook, low competition on LinkedIn for this angle, perfect creator fit)
When this skill produces unexpected, incomplete, or incorrect output, generate a
skill_feedback block (see shared/references/feedback-protocol.md for full schema).
Skill-specific failure modes:
wrong_output with the scores.data_quality.chain_break.Auto-detect triggers:
recommended_skill_params missing required fields for the suggested next skillReport issues: GitHub Issues | Discussions
shared/references/social-data-providers.md — API configuration and engagement score formulashared/references/flywheel-connections.md — master flywheel connection mapshared/references/platform-rules.md — platform-specific content guidelinesshared/references/feedback-protocol.md — issue detection and reporting standardviral-post-writer (S2) — recommended_angle with format, hook, and parameterstiktok-script-writer (S2) — TikTok-specific angle with duration and hooktwitter-thread-writer (S2) — X-specific angle with hookreddit-post-writer (S2) — Reddit-specific angle with subreddit suggestionaffiliate-blog-builder (S3) — blog angle with SEO keyword alignmentcomparison-post-writer (S3) — if winning angle is a comparisoncontent-pillar-atomizer (S2) — angle as the pillar topic to atomizetrending-content-scout (S1) — engagement data, patterns, gaps, benchmarksniche-opportunity-finder (S1) — niche context for angle generationcompetitor-spy (S1) — competitor gaps to exploitperformance-report (S6) — historical angle performance dataperformance-report shows which angles actually performed → update scoring weights and format preferences for next run → content strategy improves with every cyclechain_metadata:
skill_slug: "content-angle-ranker"
stage: "research"
timestamp: string
suggested_next:
- "viral-post-writer"
- "tiktok-script-writer"
- "affiliate-blog-builder"