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SKILL verified MIT Self-run

Niche Opportunity Finder

skill-affitor-affiliate-skills-niche-opportunity-finder · by Affitor

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Install

$ agentstack add skill-affitor-affiliate-skills-niche-opportunity-finder

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

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Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

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About

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):

| Dimension | Weight | How to Assess | |-----------|--------|---------------| | Search Demand | 30% | web_search "[niche] how to" — look at result count and autosuggest depth | | Program Availability | 30% | Search openaffiliate.dev (GET /api/programs?q=[niche]) or web_search "[niche] affiliate programs"` — count quality programs | | Competition Level | 25% | Search "[niche] best tools" — how saturated is the top 10? Fewer exact-match affiliate sites = less competition. Score 10 = very low competition | | Content Potential | 15% | 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" / = 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
chain_metadata:
  skill_slug: "niche-opportunity-finder"
  stage: "research"
  timestamp: string
  suggested_next:
    - "affiliate-program-search"
    - "monopoly-niche-finder"
    - "keyword-cluster-architect"

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.