Agent skill · Data & Analytics

content-angle-ranker

Rank content angles by engagement data, competition level, and platform fit. Data-driven angle selection instead of guesswork. Use this skill when the user has a keyword or product and needs to decide WHAT to create, which angle to take, which format to use, or which platform to target. Triggers on: "what angle should I use", "rank content ideas for [keyword]", "best angle for [product]", "which content idea will perform best", "help me pick an angle", "what should I write about", "content angle for [topic]", "rank my content ideas", "which approach will get the most views", "data-driven conte

Affitorgithub.com/AffitorGitHub ↗
claude-codecursorMIT
Install
npx skills add Affitor/affiliate-skills --skill content-angle-ranker --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 19 KB
Bundled scripts: none
Version: 1.0.0
Declared author: affitor
Requires: Claude Code, ChatGPT, Gemini CLI, Cursor, Windsurf, OpenClaw, any AI agent
Path: skills/research/content-angle-ranker/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 586
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Content Angle Ranker 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. ## Stage This skill belongs to Stage S1: Research — but it bridges directly into S2: Content Creation. ## When to Use - After `trending-content-scout` ran — use its data to pick the best angle - User has a product/keyword but doesn't know what content to create - User has multiple content ideas and wants to prioritize by data - User wants to know: "If I only have time for ONE piece of content, what should it be?" - Before running any S2 content skill (viral-post-writer, tiktok-

What's inside
Steps it walks through
  1. Stage
  2. When to Use
  3. Input Schema
  4. Workflow
  5. Step 1: Gather Engagement Data
  6. Step 2: Generate Angle Candidates (8-12)
  7. Step 3: Score Each Angle
  8. Step 4: Rank and Add Difficulty/Time Estimates
  9. Step 5: Self-Validation
  10. Output Schema
  11. Output Format
  12. Error Handling
  13. Examples
  14. Feedback & Issue Reporting
More from affiliate-skills
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About this skill
What does the content-angle-ranker skill do?

Rank content angles by engagement data, competition level, and platform fit. Data-driven angle selection instead of guesswork. Use this skill when the user has a keyword or product and needs to decide WHAT to create, which angle to take, which format to use, or which platform to target. Triggers on: "what angle should I use", "rank content ideas for [keyword]", "best angle for [product]", "which content idea will perform best", "help me pick an angle", "what should I write about", "content angle for [topic]", "rank my content ideas", "which approach will get the most views", "data-driven conte

How do I install it?

Run `npx skills add Affitor/affiliate-skills --skill content-angle-ranker --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From Affitor/affiliate-skills, a repository with 586 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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