Content Angle Ranker

What the source does

• FilesystemNone observedNo reads or writes in the source
• NetworkNone observedNo outbound calls in the source
• ShellNone observedNo commands run in the source
• DependenciesPinnedNothing floats
• SecretsNone foundNo keys in source

Five audit layers

Gates applied: no behavioural pass.

Audit 0.4.1 · source sha 2515ce9634da · 15 Oct 2026Report an issue or request a re-scan

• PublisherAffitor GitHub organizationOwner of the repository this skill is read from
• Source folderAffitor/affiliate-skills/skills/research/content-angle-rankerThe exact folder we audited
• LicenceMITAs the repository states it
• Commit pinned for this verdict2515ce9634daA new audit runs when the source changes
• Repository statusNot archivedLast push 2 days ago
• Sandboxed runNot runSkills are read, not executed; layer L4 is skipped

Its description: 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,…

---
name: content-angle-ranker
description: >
  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 content planning", "angle ranker", "content scoring", "which hook should I use",
  "compare these content ideas", "prioritize my content angles", "what video should I make".
license: MIT
version: "1.0.0"
tags: ["affiliate-marketing", "research", "content-creation", "data-driven", "ranking", "angle-selection"]
compatibility: "Claude Code, ChatGPT, Gemini CLI, Cursor, Windsurf, OpenClaw, any AI agent"
metadata:
  author: affitor
  version: "1.0"
  stage: S1-Research
---

# 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-script-writer, etc.)

## Input Schema

```yaml
keyword: 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.

## Workflow

### Step 1: Gather Engagement Data

**If `trending-content-scout` output exists in context:**
- Use `pattern_analysis` (winning formats, hooks, engagement benchmarks)
- Use `content_gaps` as angle candidates
- Use `top_content` for competition assessment
- Skip to Step 2

**If no scout data:**
Run a quick scout internally:
1. `web_search "[keyword] site:youtube.com"` → top 10 videos, note formats and view counts
2. `web_search "[keyword] site:tiktok.com"` OR `web_search "[keyword] tiktok viral"` → top TikTok content
3. `web_search "[keyword] site:reddit.com top"` → top Reddit discussions
4. `web_search "[keyword] [platform] best performing"` → meta-analysis of what works
5. Extract: dominant formats, popular hooks, view count ranges, gaps

This takes 30-60 seconds and provides enough signal for angle scoring.

### Step 2: Generate Angle Candidates (8-12)

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:**

1. **Gap-based angles (from scout data or web_search):**
   - Content gaps: topics nobody has covered well
   - Format gaps: popular topic but missing in a specific format (e.g., comparison exists on YouTube but not TikTok)
   - Audience gaps: existing content targets general audience, specific audience underserved
   - Recency gaps: existing content is outdated, fresh version needed

2. **Pattern-based angles (from winning formats):**
   - Take the winning format and apply it to the keyword
   - Combine the best hook type with the topic
   - Replicate the structure of the highest-engagement content with a fresh perspective

3. **Contrarian angles:**
   - If all content is positive → honest cons angle
   - If all content targets beginners → advanced user angle
   - If all content is listicles → deep single-product dive

4. **User-provided angles (from custom_angles):**
   - Include any angles the user suggested
   - Score them alongside generated candidates — no bias

For each angle, define:

```yaml
Angle:
  title: string               # Specific, could be an actual content title
  angle: string               # Brief description of the angle
  format: string              # "comparison" 

Excerpt, first 6,000 characters of SKILL.md, verbatim from the audited commit. It is text from someone else’s repository, quoted so you can judge it before your agent reads it.

1. 2026-10-15
   ✓SAFE B 89 / 100

   first audit · source 2515ce9634da

Questions about Content Angle Ranker

• github.com/Affitor/affiliate-skills/tree/main/skills/research/co — the audited source at commit 2515ce9634da and every finding aboveObserved · 15 Oct 2026

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