Niche Opportunity Finder logo

Niche Opportunity Finder

Organization
Affitor
niche-opportunity-finder

Find untapped affiliate niches with real earning potential. Use this skill when the user asks about picking a niche, finding a niche to start affiliate marketing, what niche to get into, niche research, niche ideas, beginner niche selection, low competition niches, profitable niches, or says "I don't know what to promote", "help me pick a niche", "what niche should I start with", "find me a niche with less competition", "niche ideas for affiliate", "is X a good niche for affiliate marketing", "best niches 2024", "untapped niches".

Overview

PublisherAffitor
Repositoryaffiliate-skills
Skill nameniche-opportunity-finder
Stars
705
Forks
209
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by Affitor on GitHub. Read the source before you install it.

Installation

Install the Niche Opportunity Finder AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/Affitor/affiliate-skills/tree/main/skills/research/niche-opportunity-finder
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Affitor/affiliate-skills.git /tmp/affiliate-skills
mkdir -p .claude/skills
cp -r /tmp/affiliate-skills/skills/research/niche-opportunity-finder .claude/skills/niche-opportunity-finder
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Niche Opportunity Finder in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Niche Opportunity Finder on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Niche Opportunity Finder is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Niche Opportunity Finder

Analyze search demand, competition, and available affiliate programs to surface untapped niches worth entering. Outputs a scored shortlist with clear reasoning so beginners can start promoting in under an hour.

Stage

This skill belongs to Stage S1: Research

When to Use

  • User is new to affiliate marketing and has no niche
  • User is unhappy with their current niche and wants alternatives
  • User wants to validate a niche idea before investing time
  • User asks which niches are trending or low-competition
  • User wants to find niches underserved by existing affiliates

Input Schema

{
  interests: string[]       # (optional) Topics user already knows or cares about
  audience: string          # (optional) Who they plan to reach — "beginners", "professionals", "parents"
  platform: string          # (optional) Where they'll publish — "blog", "tiktok", "youtube", "linkedin"
  budget: string            # (optional) "zero" | "low ($0-50/mo)" | "medium ($50-200/mo)"
  goal: string              # (optional) "first $100" | "side income $1k/mo" | "full-time income"
  avoid: string[]           # (optional) Niches or topics to exclude
}

Workflow

Step 1: Understand the User's Situation

Ask (if not already clear from context):

  1. Any topics you already know well or are curious about?
  2. Where will you publish content? (blog, TikTok, YouTube, newsletter...)
  3. What's your income goal in the first 6 months?

If user says "just find me something" → default to: AI/SaaS tools, YouTube or blog, goal = first $500/mo.

Step 2: Generate Niche Candidates

Produce 8-12 niche candidates across 3 tiers:

Tier A — Trending (high demand, growing fast): Use web_search "fastest growing affiliate niches [current year]" and web_search "trending affiliate programs [current year]" to find niches with momentum. Look for: AI tools, health tech, fintech, remote work tools, creator economy.

Tier B — Evergreen (stable demand, proven programs): Always-on niches: personal finance, web hosting, email marketing, SEO tools, fitness/wellness, online education, cybersecurity.

Tier C — Micro-niches (narrow, low competition, high intent): Examples: AI tools for lawyers, budgeting apps for freelancers, SEO for Shopify stores, productivity tools for ADHD. These are combinations of a vertical + a job or persona. Use web_search "[vertical] affiliate programs [persona]" to discover.

Step 3: Score Each Niche

Score each candidate on 4 dimensions (1-10 scale each):

DimensionWeightHow to Assess
Search Demand30%`web_search "[niche] how to" — look at result count and autosuggest depth
Program Availability30%Search openaffiliate.dev (GET /api/programs?q=[niche]) or web_search "[niche] affiliate programs" — count quality programs
Competition Level25%Search "[niche] best tools" — how saturated is the top 10? Fewer exact-match affiliate sites = less competition. Score 10 = very low competition
Content Potential15%Can tutorials, comparisons, listicles, and reviews be made for this niche easily?

Overall score = weighted average. Cut anything below 5.5.

Verdict: 7.5+ = "High Opportunity" / 5.5-7.4 = "Worth Testing" / <5.5 = "Saturated/Skip"

Step 4: Validate Top 3 Niches on openaffiliate.dev

For the top 3 niches, query GET https://openaffiliate.dev/api/programs?q=[niche]&utm_source=affiliate-skills (see affiliate-program-search/references/openaffiliate-api.md) to verify real programs exist with good commission structures:

  • At least 3 programs with reward_value 20%+ OR reward_type cps_recurring
  • At least one program with cookie_days >= 30
  • Programs with stars_count > 5 (community-validated quality)

If a niche scores well on demand but has no programs on openaffiliate.dev, use web_search "[niche] affiliate program signup" to verify alternatives exist.

Step 5: Build the Opportunity Brief

For the top-ranked niche, produce a one-page opportunity brief (see Output Format). For runner-up niches, produce summary cards only.

Step 6: Recommend Next Steps

Map user's chosen niche to the affiliate funnel:

  1. Use affiliate-program-search to find the best specific program in this niche
  2. Use tiktok-script-writer or twitter-thread-writer for first content
  3. Use commission-calculator to project first 90 days of income

Step 7: Self-Validation

Before presenting output, verify:

  • Search demand backed by data (autosuggest depth, result count)
  • Top niche has ≥3 programs with 20%+ commission on openaffiliate.dev
  • Competition score reflects actual top-10 SERP analysis
  • Content angles are specific and actionable, not generic

If any check fails, fix the output before delivering. Do not flag the checklist to the user — just ensure the output passes.

Output Schema

{
  output_schema_version: "1.0.0"  # Semver — bump major on breaking changes
  top_niche: {
    name: string              # "AI Productivity Tools"
    tier: string              # "Trending" | "Evergreen" | "Micro-niche"
    score: number             # 8.4
    verdict: string           # "High Opportunity"
    why: string               # 2-3 sentence rationale
    example_programs: string[] # ["Notion", "ClickUp", "Reclaim AI"]
    content_angles: string[]  # ["comparison", "workflow walkthrough", "beginner guide"]
    difficulty: string        # "Beginner-friendly" | "Intermediate" | "Advanced"
  }
  runner_up: NicheCandidate   # Same structure
  all_scored: NicheScore[]    # Full list with scores
  recommended_next_skill: string  # "affiliate-program-search"
}

Output Format

## Niche Opportunity Report

### Top Pick: [Niche Name]

**Opportunity Score:** [X.X/10] — [Verdict]
**Tier:** [Trending / Evergreen / Micro-niche]
**Difficulty:** [Beginner-friendly / Intermediate / Advanced]

**Why this niche:**
[2-3 sentences covering demand, program quality, and why it's not yet saturated]

| Dimension | Score | Evidence |
|-----------|-------|----------|
| Search Demand | X/10 | [What search data showed] |
| Program Availability | X/10 | [X programs found, avg commission Y%] |
| Competition Level | X/10 | [What competitor landscape looks like] |
| Content Potential | X/10 | [Content formats that work here] |
| **Overall** | **X.X/10** | **[Verdict]** |

**Example affiliate programs:** [Program A], [Program B], [Program C]

**Content angles to start with:**
1. [Angle 1 — specific post/video idea]
2. [Angle 2]
3. [Angle 3]

---

### Runner-up: [Niche Name] — [X.X/10]
[2-sentence summary + why it's #2]

### Other Candidates Scored

| Niche | Score | Verdict | Note |
|-------|-------|---------|------|
| ...   | ...   | ...     | ...  |

---

## Next Steps

1. Run `affiliate-program-search` to find the best [Niche] program on openaffiliate.dev
2. Run `commission-calculator` to project 90-day earnings
3. Run `tiktok-script-writer` or `twitter-thread-writer` to create your first piece of content

Error Handling

  • No interests provided: Default to AI/SaaS tools niche. Explain the default.
  • Niche too broad (e.g., "health"): Break into sub-niches and score each separately. Present as micro-niche grid.
  • Niche too narrow (e.g., "left-handed guitarists who use Linux"): Widen one dimension and present a spectrum of options.
  • No programs found for top niche: Still present the niche but flag program gap. Suggest direct brand deals as alternative.
  • User picks a saturated niche: Don't just say no. Find the micro-niche angle within it that is less saturated.
  • Conflicting interests: Ask user to pick one dimension (monetization speed vs. passion vs. content ease) and sort by that.

Examples

Example 1: User: "I want to start affiliate marketing but have no idea what niche to pick" → Ask: any interests? what platform? income goal? → If no answer: default to AI/SaaS tools on YouTube/TikTok, goal = first $500/mo → Generate 10 candidates, score all, return top 3 with detailed brief for #1

Example 2: User: "Is fitness a good niche for affiliate marketing?" → Validate fitness niche: high demand, many programs (MyProtein, Noom, Whoop) → Flag: highly competitive on Google. Score = 6.2 "Worth Testing" → Suggest micro-niches: fitness for new moms, home gym under $500, wearables for runners → Score micro-niches — surface the strongest one

Example 3: User: "I know a lot about Notion and productivity tools" → Lean into existing knowledge: AI productivity tools, note-taking apps, PKM space → Score with "expert authority" bonus — existing knowledge = faster content creation → Surface programs: Notion, Obsidian affiliate, ClickUp, Reclaim AI → Recommend micro-niche: "AI tools for knowledge workers" — score 8.1

References

  • affiliate-program-search/references/openaffiliate-api.md — how to fetch programs from openaffiliate.dev
  • shared/references/affiliate-glossary.md — affiliate marketing terminology
  • shared/references/ftc-compliance.md — disclosure requirements
  • shared/references/flywheel-connections.md — master flywheel connection map

Flywheel Connections

Feeds Into

  • affiliate-program-search (S1) — validated niches to search programs in
  • monopoly-niche-finder (S1) — niche data for intersection analysis
  • keyword-cluster-architect (S3) — niche defines keyword universe
  • content-moat-calculator (S3) — niche for feasibility analysis

Fed By

  • performance-report (S6) — performance data identifies best-performing niches
  • conversion-tracker (S6) — conversion data reveals profitable niches

Feedback Loop

  • Performance data from S6 shows which niche characteristics predict success → refine opportunity scoring
yaml
chain_metadata:
  skill_slug: "niche-opportunity-finder"
  stage: "research"
  timestamp: string
  suggested_next:
    - "affiliate-program-search"
    - "monopoly-niche-finder"
    - "keyword-cluster-architect"

Frequently asked questions

What does the Niche Opportunity Finder AI skill do?

Find untapped affiliate niches with real earning potential. Use this skill when the user asks about picking a niche, finding a niche to start affiliate marketing, what niche to get into, niche research, niche ideas, beginner niche selection, low competition niches, profitable niches, or says "I don't know what to promote", "help me pick a niche", "what niche should I start with", "find me a niche with less competition", "niche ideas for affiliate", "is X a good niche for affiliate marketing", "best niches 2024", "untapped niches".

Why use Niche Opportunity Finder on TypingMind?

Because you install it once and use it with any model. Niche Opportunity Finder is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Niche Opportunity Finder in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Affitor/affiliate-skills/tree/main/skills/research/niche-opportunity-finder. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Niche Opportunity Finder?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Niche Opportunity Finder?

As many as you like. As long as a model supports skills, you can use Niche Opportunity Finder with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Niche Opportunity Finder AI skill free?

Yes. It is published on GitHub by Affitor under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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