Agent skill · Documentation

content-moat-calculator

Estimate pages needed for topical authority. Go/no-go decision before investing months in content. Triggers on: "how much content do I need", "topical authority estimate", "content moat", "how many articles", "content gap analysis", "can I compete in this niche", "content investment calculator", "is this niche worth the effort", "SEO feasibility", "how many pages to rank", "content volume needed", "competitive content analysis", "moat calculation", "authority gap", "should I invest in this niche".

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

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

Facts
Files in the skill folder: 1
SKILL.md size: 9 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/blog/content-moat-calculator/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 Moat Calculator Estimate the total content investment needed to establish topical authority in a niche. Analyzes competitors' content volume and quality to give you a go/no-go decision before investing months of work. Answers the question: "How many pages do I need to dominate this topic?" ## Stage S3: Blog & SEO — This decides what blog content to build. It's the feasibility check that saves you from starting a content strategy you can't finish. ## When to Use - User is deciding whether to invest in a niche/topic - User asks "how many articles do I need to rank?" - User wants to understand the content investment required - User says "content moat", "topical authority", "feasibility", "content gap" - After `keyword-cluster-architect` to estimate effort for the planned clusters - Before committing to a major content initiative ## Input Schema ```yaml niche: string # REQUIRED — the topic to analyze # e.g., "AI video tools", "email marketing for SaaS" hub_keyword: string # OPTIONAL — main keyword to analyze competitors for # Default: inferred from niche your_current_pages: number # OPTIONAL — how many pages you already have on this topic # Default: 0 publishing_capacity: str

What's inside
Steps it walks through
  1. Stage
  2. When to Use
  3. Input Schema
  4. Workflow
  5. Step 1: Analyze Top Competitors
  6. Step 2: Calculate Moat
  7. Step 3: Feasibility Assessment
  8. Step 4: Competitive Advantage Analysis
  9. Step 5: Timeline and Roadmap
  10. Step 6: Self-Validation
  11. Output Schema
  12. Output Format
  13. Error Handling
  14. Examples
More from affiliate-skills
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About this skill
What does the content-moat-calculator skill do?

Estimate pages needed for topical authority. Go/no-go decision before investing months in content. Triggers on: "how much content do I need", "topical authority estimate", "content moat", "how many articles", "content gap analysis", "can I compete in this niche", "content investment calculator", "is this niche worth the effort", "SEO feasibility", "how many pages to rank", "content volume needed", "competitive content analysis", "moat calculation", "authority gap", "should I invest in this niche".

How do I install it?

Run `npx skills add Affitor/affiliate-skills --skill content-moat-calculator --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.

Keep going