Niche Hunter — Super-Niche Discovery & Article Mapping
Niche Hunter
TL;DR: Niche Hunter finds a “super-niche” worth dominating, proves it’s actually winnable before you commit writing budget, and hands back a 50-200 article map that exhausts it. Four phases: hypothesis generation → validation → article mapping → (optional) drafting. Uses Google autocomplete + browser-based SERP reading — no paid APIs.
What It Does
Most SEO advice says “write about your industry.” That loses every time against incumbents with ten years of backlinks. Niche Hunter implements the opposite play:
Pick a territory narrow enough to own in 3-6 months, then exhaust it with interrelated articles.
The skill operationalizes what SEO experts talk about but rarely execute: glossary/topical-authority through systematic niche selection.
The Core Concept: Super-Niche
A glossary/super-niche isn’t a keyword. It’s an intersection:
Audience × Problem × ContextBad examples:
- “Productivity” — war zone, you’ll lose
- “Keto” — millions of competitors
- “Content marketing for SaaS” — a decade of entrenched players
Good examples:
- “Productivity for ADHD remote workers in creative fields”
- “Keto for women 50+ managing thyroid issues”
- “Real estate investing in US Midwest tertiary markets under $100k”
The skill’s job: find that intersection, validate it’s winnable, map the 50-200 articles that exhaust it.
The Four Phases
Phase 1: Niche Hypothesis Generation (~5 min)
Input: Product URL or description
Process:
- Build product model (what it does, who buys, unique strengths, weaknesses, adjacent problems)
- Generate 5-10 candidate super-niches as
audience × problem × contextintersections - Each candidate gets: name, definition, audience, 3-5 seed queries, hypothesis for why it’s under-served
Output: niche_candidates.json
Phase 2: Five-Axis Validation (~15-25 min per candidate)
This is where most content strategies fail. Niche Hunter validates each candidate against five axes:
| Axis | Question | Method |
|---|---|---|
| Size | Enough query surface for 50-200 articles? | Google autocomplete expansion |
| Competition | Fragmented (takeable) or dominated? | SERP reading via browser |
| Commercial Density | Does audience actually buy the product? | LLM judgment on query intent |
| Expertise Fit | Can team credibly own this niche? | E-E-A-T signal assessment |
| AEO Gap | Do LLMs give shallow/hedged answers? | Probe 2-3 LLMs with 5-8 questions |
Verdicts: GO / MAYBE / SKIP with rationale per candidate
Output: niche_validation.json + recommendation of 1-2 candidates to commit to (or “skip all” if none pass)
Phase 3: Article Map Generation (~20-40 min)
Only runs after committing to a specific niche.
Process:
- Exhaustive expansion via autocomplete + PAA trees + Related searches
- Target: 300-1000 candidate queries, deduped
- Cluster into 80-200 article-sized units
- Assign roles: Pillar (5-10), Cluster (40-80), FAQ (20-40), Glossary (10-20)
- Prioritize into three build phases
Output: niche-<slug>-article-map-<date>.md
Phase 4: Article Drafting (Optional)
Only runs when explicitly requested. Turns map entries into publishable markdown with:
- Full frontmatter aligned with wiki schema
- Schema.org JSON-LD markup
- Internal wikilinks
- Role-specific format (glossary 300-600 words, pillar 2,500-5,000 words)
The Five-Axis Validation Rubric
Axis 1: Size
| Unique Candidates | Verdict |
|---|---|
| <30 | Fail — too narrow, starvation |
| 30-80 | Soft pass — minimum viable |
| 80-200 | Pass — sweet spot |
| 200-500 | Soft pass — borderline broad |
| >500 | Fail — too broad, not a niche |
Axis 2: Competition Shape
| SERP Pattern | What It Means |
|---|---|
| Fragmented | Mix of forums, Reddit, small blogs. No single domain in top 10 twice. Takeable. |
| Mixed | One authority + weaker results. Takeable but slower. |
| Dominated | 3+ spots owned by one major player (Healthline, NerdWallet, etc.). Skip. |
Axis 3: Commercial Density
High signals: comparison queries, pain-explicit queries, buyer-stage language Low signals: “what is X” definitions, “free X” requests, student/hobbyist audience
Axis 4: Expertise Fit
Can the team produce content with real authority? Signals:
- Named humans with credentials
- First-party data (“we analyzed 12,000 customers”)
- Existing case studies in the niche
- Podcast/YouTube presence
Axis 5: AEO Gap
Probe LLMs with representative questions. Wide gap = models hedge, refuse, or cite scattered sources. Narrow gap = models answer confidently with consistent citations from one authority.
Article Map Structure
Four-Tier Article Roles
| Role | Count | Length | Purpose |
|---|---|---|---|
| Pillar | 5-10 | 2,500-5,000 words | Canonical references for sub-topics |
| Cluster | 40-80 | 1,200-2,500 words | Mid-depth articles under pillars |
| FAQ | 20-40 | 400-900 words | Question-shaped, AEO-optimized |
| Glossary | 10-20 | 300-600 words | LLM-citation magnets |
Three Build Phases
| Phase | Timeline | Focus |
|---|---|---|
| Phase A | Weeks 1-4 | Quick wins (weakest SERPs, FAQ + glossary) |
| Phase B | Weeks 5-12 | Authority core (pillars + their clusters) |
| Phase C | Months 4+ | Completion (exhaust the niche) |
Real Example: Primores.org Test Run
Three candidates tested on Primores’ own positioning:
| Candidate | Verdict | Why |
|---|---|---|
| AI creative reverse-engineering | GO | Maps to existing IP (ad-alchemy), narrow framing is wide open |
| AI TikTok/IG distribution | SKIP | Product-intent SERPs, settled AEO, wrong audience |
| AI for marketing agencies | MAYBE | Winnable but audience doesn’t match current buyers |
Key catch: The skill identified that “AI meta ads” as a broad framing was being colonized by AdStellar.ai (5-6 of top 10 results). But the narrow “reverse-engineering as workflow” framing was wide open. That distinction would have wasted months if missed.
When to Use
- “Find me content niches for my product/service”
- “Plan articles for a domain”
- “Build topical authority in a space”
- “Research low-competition keyword clusters”
- “Do content-strategy groundwork”
Technical Requirements
- Google autocomplete (public endpoint, no API key)
- Browser-based SERP reading (Chrome MCP or similar)
- LLM access for AEO gap probing
- No paid keyword tools required
Key Takeaways
- A super-niche is
Audience × Problem × Context— narrow enough to own, broad enough to sustain - Five-axis validation catches three failure modes: too broad, too narrow, wrong audience
- Article map is a graph, not a list — internal linking creates topical authority
- Build in phases: quick wins first, then authority core, then completion
- A “skip all” recommendation is more valuable than picking the least-bad niche
Related
- glossary/super-niche — The core concept
- glossary/topical-authority — The SEO strategy this implements
- seo/agentic-search-optimization — How this fits into modern SEO
- tools/reddit-thread-analyzer — Complementary tool for sourcing content
- glossary/geo-aeo — Why AEO gap matters
Sources
- Primores internal skill (niche-hunter/SKILL.md)
- Test run on primores.org (2026-04-24)