Agent skill

Content Moat Calculator

by Affitor in Affitor/affiliate-skills

Estimate pages needed for topical authority. An agent skill from Affitor/affiliate-skills.

MITAuto-check passedProduct & Project Management

Install Content Moat Calculator

skills CLI
$ npx skills add Affitor/affiliate-skills --skill content-moat-calculator -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install Affitor/affiliate-skills content-moat-calculator --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/Affitor/affiliate-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/blog/content-moat-calculator .claude/skills/content-moat-calculator && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
content-moat-calculator
GitHub stars
700
Token cost
~2.2k tokens
SKILL.md length
692 words
Files
1
Skills in repo
50
Repo updated
First seen
Licence
MIT

At a glance

Estimate pages needed for topical authority. An agent skill from Affitor/affiliate-skills.

  • Works in 6 steps: Analyze Top Competitors → Calculate Moat → Feasibility Assessment → …
  • : how much content do I need
  • SKILL.md covers Stage, When to Use, Input Schema and Workflow, plus 7 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Content Moat Calculator is an agent skill from Affitor/affiliate-skills. 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".

Its SKILL.md is about 2.2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts. Compatibility notes: Claude Code, ChatGPT, Gemini CLI, Cursor, Windsurf, OpenClaw, any AI agent

It sits in Product & Project Management, covering Feature launches and release readiness. The repository describes itself as: 50 AI agent skills for affiliate marketing. Research trending content, write data-backed posts, generate infographics, build landing pages, deploy — full flywheel with social… The licence is MIT.

When your agent uses it

  • : how much content do I need
  • Topical authority estimate
  • How many articles
  • Content gap analysis

Example prompts

  • “how much content do I need”
  • “topical authority estimate”
  • “content moat”
  • “/content-moat-calculator”

Requirements

  • Compatibility (from SKILL.md): Claude Code, ChatGPT, Gemini CLI, Cursor, Windsurf, OpenClaw, any AI agent

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. Analyze Top Competitors
  2. Calculate Moat
  3. Feasibility Assessment
  4. Competitive Advantage Analysis
  5. Timeline and Roadmap
  6. Self-Validation

What it can do on your machine

Read from SKILL.md and the folder at commit e43bfae. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are yaml).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    Claude Code, ChatGPT, Gemini CLI, Cursor, Windsurf, OpenClaw, any AI agent

    From compatibility in the SKILL.md frontmatter.

Context cost

Content Moat Calculator loads about 2.2k tokens when it runs. Until then it costs about 132 tokens; SKILL.md has 692 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~132
When it runs · the whole SKILL.md, loaded when a task matches
~2.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from Affitor/affiliate-skills at commit e43bfae, republished under its MIT licence (© Affitor). 692 words, ~2,237 tokens.

Download SKILL.mdSave it as .claude/skills/content-moat-calculator/SKILL.md (or your agent's skills folder).
name
content-moat-calculator
description
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".
compatibility
Claude Code, ChatGPT, Gemini CLI, Cursor, Windsurf, OpenClaw, any AI agent
license
MIT
version
1.0.0
tags
affiliate-marketing, blogging, seo, content-writing, content-moat, authority
metadata.author
affitor
metadata.version
1.0
metadata.stage
S3-Blog

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: string   # OPTIONAL — "1/week" | "2/week" | "3/week" | "5/week"
                              # Default: "2/week"

Chaining from S3 keyword-cluster-architect: Use keyword_clusters.total_clusters and keyword_clusters.hub.keyword.

Workflow

Step 1: Analyze Top Competitors

Read shared/references/seo-strategy.md for moat calculation methodology.

  1. web_search for [hub_keyword] or main niche keyword
  2. Identify top 5 ranking sites (exclude giants like Wikipedia, Reddit)
  3. For each competitor:
    • web_search: site:[competitor.com] [niche topic] — count pages on this topic
    • Note: content depth (word count), content freshness (publish dates), content types (blog, comparison, tutorial)
Step 2: Calculate Moat
Average competitor pages = sum(competitor_pages) / number_of_competitors
Your moat target = Average × 1.5 (need MORE than average to break through)
Content gap = Moat target - your_current_pages
Step 3: Feasibility Assessment

Based on moat target and publishing capacity:

Weeks to moat = Content gap / publishing_capacity_per_week
Moat TargetAssessmentRecommendation
< 20 pagesGREEN — AchievableGo for it. 2-3 months at 2/week.
20-50 pagesYELLOW — SignificantCommit or don't. 3-6 months at 2/week.
50-100 pagesORANGE — Major investmentConsider narrowing niche. 6-12 months.
100+ pagesRED — Very high barrierFind a sub-niche or different angle.
Step 4: Competitive Advantage Analysis

Identify ways to build moat FASTER:

  1. Quality over quantity: Can you beat thin content with fewer, deeper pages?
  2. Unique data: Can you add proprietary data competitors don't have? (→ proprietary-data-generator)
  3. Format advantage: Can you use formats competitors don't? (video, interactive, tools)
  4. Update velocity: Can you refresh content faster than competitors?
Step 5: Timeline and Roadmap

Create realistic timeline:

  • Phase 1: Foundation content (hub + core spokes)
  • Phase 2: Supporting content (additional spokes, long-tail)
  • Phase 3: Authority content (original research, data, comprehensive guides)
  • Phase 4: Maintenance (refresh, update, expand)
Step 6: Self-Validation
  • Competitor analysis uses real data (not estimates)
  • Moat calculation is transparent and logical
  • Feasibility assessment is honest (not overly optimistic)
  • Competitive advantages are realistic
  • Timeline accounts for quality, not just quantity

Output Schema

yaml
output_schema_version: "1.0.0"
content_moat:
  niche: string
  hub_keyword: string
  competitors_analyzed: number
  average_competitor_pages: number
  moat_target: number
  your_current_pages: number
  content_gap: number
  feasibility: string          # "green" | "yellow" | "orange" | "red"
  weeks_to_moat: number
  assessment: string           # Go/no-go summary

  competitors:
    - domain: string
      pages_on_topic: number
      content_quality: string  # "thin" | "average" | "deep"
      freshness: string        # "stale" | "recent" | "actively updated"

  authority_gaps: string[]     # What competitors have that you don't

  competitive_advantages: string[] # Ways to build moat faster

chain_metadata:
  skill_slug: "content-moat-calculator"
  stage: "blog"
  timestamp: string
  suggested_next:
    - "affiliate-blog-builder"
    - "keyword-cluster-architect"
    - "proprietary-data-generator"
    - "content-decay-detector"

Output Format

## Content Moat Analysis: [Niche]

### Competitor Landscape

| Competitor | Pages on Topic | Quality | Freshness |
|---|---|---|---|
| [domain] | XX | [thin/average/deep] | [stale/recent/active] |

### Moat Calculation
- **Average competitor pages:** XX
- **Your moat target (1.5x):** XX pages
- **Your current pages:** XX
- **Content gap:** XX pages
- **At [X]/week:** XX weeks to moat

### Feasibility: [GREEN/YELLOW/ORANGE/RED]

[Assessment paragraph — honest, actionable]

### Competitive Advantages
1. [How to build moat faster]
2. [What competitors are missing]

### Timeline
| Phase | Content | Pages | Weeks |
|---|---|---|---|
| Foundation | Hub + core spokes | XX | X |
| Supporting | Long-tail, tutorials | XX | X |
| Authority | Original research, data | XX | X |
| **Total** | | **XX** | **X** |

### Recommendation
[Clear go/no-go with reasoning]
Show full SKILL.md (301 more words)Show less

Error Handling

  • Can't find competitors: Broaden the search. If still no competitors → great sign (blue ocean), estimate moat at 15-20 pages.
  • Niche too broad: "This niche has too many competitors to analyze meaningfully. Narrow down — run monopoly-niche-finder first."
  • User has significant existing content: Factor in existing pages. May already be at moat → focus on gaps and freshness.
  • All competitors are massive sites: Recommend niching down. You can't outproduce Forbes — but you can out-specialize them.

Examples

Example 1: "How much content do I need to dominate AI video tools?" → Analyze top 5 sites ranking for "best AI video tools". Average 35 pages. Moat = 53 pages. At 2/week = 27 weeks. YELLOW — significant but doable.

Example 2: "Can I compete in email marketing?" → Analyze competitors. Average 200+ pages. Moat = 300 pages. RED — too broad. Suggest: "email marketing for Shopify stores" (moat = 25 pages, GREEN).

Example 3: "Content moat for my keyword clusters" (after keyword-cluster-architect) → Use cluster data to estimate pages needed per cluster. Compare against competitors per cluster. Identify which clusters are GREEN vs RED.

Flywheel Connections

Feeds Into
  • affiliate-blog-builder (S3) — how many articles and what type to write
  • grand-slam-offer (S4) — authority gaps inform what to emphasize in offers
  • proprietary-data-generator (S7) — identifies data moat opportunities
Fed By
  • keyword-cluster-architect (S3) — cluster count informs moat estimation
  • seo-audit (S6) — current content performance data
  • performance-report (S6) — content performance metrics
Feedback Loop
  • performance-report (S6) tracks progress toward moat target → celebrate milestones, adjust strategy if falling behind

Quality Gate

Before delivering output, verify:

  1. Would I share this on MY personal social?
  2. Contains specific, surprising detail? (not generic)
  3. Respects reader's intelligence?
  4. Remarkable enough to share? (Purple Cow test)
  5. Irresistible offer framing? (assessment feels actionable)

Any NO → rewrite before delivering.

References

  • shared/references/seo-strategy.md — Topical authority model, moat calculation formula
  • shared/references/case-studies.md — Real content strategy examples
  • shared/references/flywheel-connections.md — Master connection map

© Affitor, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/blog/content-moat-calculator of Affitor/affiliate-skills.

Open the folder on GitHubat commit e43bfae

Compare with similar skills

Content Moat Calculator next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Content Moat Calculator compared with similar skills
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Content Moat Calculator this skillAffitor/affiliate-skills700—~2.2kAutomated safety check: PassMIT
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Sealeap Amazon New Product Launch Planxjli360/sealeap-amazon-skills247—~548Automated safety check: PassMIT
.NET MAUI Release Readinessdotnet/maui23k—~15kAutomated safety check: PassMIT
Release ValidationMesh-LLM/mesh-llm3.5k—~2.6kAutomated safety check: PassApache-2.0

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Questions about Content Moat Calculator

What does Content Moat Calculator do?

Estimate pages needed for topical authority. An agent skill from Affitor/affiliate-skills. Content Moat Calculator is an agent skill from Affitor/affiliate-skills. Estimate pages needed for topical authority.

When should I use Content Moat Calculator?

Content Moat Calculator fits situations like: : how much content do I need; topical authority estimate; how many articles; content gap analysis.

How do I install Content Moat Calculator in Claude Code?

Run `npx skills add Affitor/affiliate-skills --skill content-moat-calculator -a claude-code`. Or copy the skill folder (skills/blog/content-moat-calculator in Affitor/affiliate-skills) into .claude/skills/content-moat-calculator in your project. Claude Code loads it when a task matches its description.

How do I install Content Moat Calculator in Codex?

Run `npx skills add Affitor/affiliate-skills --skill content-moat-calculator -a codex`. Or copy the skill folder (skills/blog/content-moat-calculator in Affitor/affiliate-skills) into .agents/skills/content-moat-calculator in your project. Codex loads it when a task matches its description.

Can I use Content Moat Calculator in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Affitor/affiliate-skills --skill content-moat-calculator -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/content-moat-calculator, .gemini/skills/content-moat-calculator, .github/skills/content-moat-calculator and .opencode/skills/content-moat-calculator in your project.

What does Content Moat Calculator need to run?

SKILL.md names no scripts, command-line tools or credentials: Content Moat Calculator is instructions for the agent only. Compatibility (from SKILL.md): Claude Code, ChatGPT, Gemini CLI, Cursor, Windsurf, OpenClaw, any AI agent.

Does Content Moat Calculator access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Content Moat Calculator safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Content Moat Calculator use?

Content Moat Calculator is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Content Moat Calculator use?

About 2.2k tokens (SKILL.md is roughly 8.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Content Moat Calculator?

Skills that share tags, products or a category with Content Moat Calculator: Ads Validate (AgriciDaniel/claude-ads, 9.8k stars), Feature Launch Playbook (rampstackco/claude-skills, 941 stars), Sealeap Amazon New Product Launch Plan (xjli360/sealeap-amazon-skills, 247 stars) and .NET MAUI Release Readiness (dotnet/maui, 23k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Content Moat Calculator?

Affitor (a GitHub organization) maintains it in Affitor/affiliate-skills, which has 700 GitHub stars. The repository holds 50 skills in this directory. The repository was last updated on September 15, 2026.

Source: Affitor/affiliate-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.