Seo tool discovery

Overview

Most free tools built for SEO fail because they're picked by gut, not by a gate. They duplicate something Lorem-Ipsum-generic, run on commodity data, drift outside the site's niche, or have no monetization path — so even when they get traffic, they don't earn links and don't move revenue. This skill encodes the discovery funnel that prevents that: a niche-fit + data-moat gate that kills 80% of bad ideas before any build effort, a 5-candidate scoring rubric that ranks survivors, and a hand-off format that names the downstream build agent so nothing falls between roles.

Use this skill BEFORE any tool-build work. Skip it if the user has already validated their concept and just wants to ship.

Instructions

Core Rules

• The data moat decides everything. A tool without proprietary or hard-to-replicate data is a commodity. Commodity tools earn no durable links — competitors clone them in a day. If no moat, kill the idea even if everything else looks good.
• Niche fit is non-negotiable. A "useful" tool that doesn't serve the site's existing audience earns off-topic links that Google discounts. Cosmetics site → skin-tone matcher YES, SEO checker NO.
• 80/20 the planning. 80% of the value of this skill is in idea selection (niche fit + data moat). Building is downstream. Do not let users skip the gate to "just start building."
• Five candidates, not one. Single-idea brainstorms anchor to whatever came first. Always generate five and rank — even if four are obvious dead ends, the comparison clarifies why the survivor wins.
• Output a strategy brief, not a verdict. The skill's deliverable is a written brief covering niche fit, data moat, SEO signals, feasibility, monetization, and alignment. Build, on-page wrapping, and launch content are downstream concerns owned by the orchestrating agent.
• Compound over spike. Prefer tools that keep earning links for years (calculators on durable data, embed widgets) over tools tied to a news cycle.

The Funnel

Stage 1 — Gatekeeping Questions (kill or proceed)

Before anything else, force two answers from the user. If either is "no" or "unclear," stop and ask. Do not proceed to candidate generation.

1. Niche question: "What is the site's niche, in one sentence? Who exactly visits today?"
2. Data question: "What data do you already own or can ingest cheaply? List concretely."

Examples of valid data sources:

• Product or service specifications (catalogs, SKUs, configurations)
• Blog post / article databases (your content corpus)
• Public APIs you can hit affordably (price feeds, weather, gov data, sports stats)
• Proprietary metrics (your own benchmarks, performance data, conversion stats)
• Customer datasets (anonymized usage data, survey results)
• Community-generated content (reviews, ratings, comments — with rights)

If the user can't name concrete data, kill the engagement: "Without a data source you own or can ingest cheaply, every tool you build will be commodity. Come back when you have at least one of these." Do not soften this.

Stage 2 — Generate 5 Candidates

Brainstorm exactly five candidate tools that:

• Use one or more of the user's named data sources
• Solve a problem the user's existing audience actually has
• Could plausibly be embedded, shared, or cited

Write each as one sentence: [Tool name] — [what it does] — [data it uses].

Example for a GPU benchmark site:

1. GPU Compatibility Matrix — checks if a GPU fits a given motherboard/case/PSU — uses spec database
2. FPS Estimator — predicts FPS for game × GPU × resolution — uses benchmark database
3. Upgrade ROI Calculator — shows cost-per-FPS gained for an upgrade — uses spec + benchmark + price data
4. Power Draw Estimator — calculates total system wattage needed — uses spec database
5. GPU Generation Timeline — visualizes performance gains across generations — uses benchmark database

Stage 3 — Score Each Candidate Across 5 Dimensions

Score 1–5 (1 = bad, 5 = excellent) on each dimension. Total a candidate by summing — but a single 1 in data_moat or niche_fit is a kill regardless of total.

Dimension	What 5 looks like	What 1 looks like
Niche fit	The site's exact audience uses this monthly	The audience would never search for this
Data moat	Built on proprietary data competitors can't easily replicate	Built on data anyone can scrape in a day
SEO signals	Sticky (3–5 min dwell), produces shareable outputs, AI-citable answers, natural embed hook	Static result, nothing to embed, no citation hook
Feasibility	Mostly client-side, ships in days	Months of backend, infrastructure-heavy
Monetization path	Clear path to email capture / affiliate / paid upgrade / sponsorship	No revenue connection at all

A score of 1 on niche_fit OR data_moat → strike the candidate. No exceptions.

Stage 4 — Alignment Checklist (final gate on the top candidate)

Before recommending the highest-scoring candidate, run it through:

• Audience match — does this solve a problem the site's existing visitors face?
• Brand fit — would the site's customers expect them to build this? (Yes = free credibility. No = build credibility before launching.)
• Competitive moat — would a competitor need the user's specific data/position to replicate, or could they build it in a week?
• Longevity — will this tool still be relevant in 2 years, or is it a trend rider?

A "no" on any of these is not an automatic kill — but every "no" must be acknowledged in the hand-off brief with mitigation.

Stage 5 — Hand-Off Brief

Output a single brief in the format below. This is the deliverable.

# Free Tool Brief: [Tool Name]

## Niche Fit
[One paragraph. Who the tool serves and why this matches the site's existing audience.]

## Data Moat
[One paragraph. The proprietary/exclusive data this runs on. Why competitors can't replicate cheaply.]

## SEO Signals
- Expected dwell time: [estimate, with reasoning]
- Embed opportunity: [yes/no — which publishers would embed and why]
- AI citation potential: [yes/no — does it produce extractable, citable answers? FAQ/structured-output formats?]
- Backlink hook: [the natural reason a journalist or blogger would link]
- Shareability: [does it produce a result users want to share? screenshot? badge?]

## Feasibility
- Mostly client-side? [yes/no]
- Data ingestion needs: [one-time / periodic / live]
- External APIs needed: [list, with cost notes]
- Estimated build effort: [days/weeks]

## Monetization Path
[How the tool feeds the funnel — email capture, affiliate clicks, paid upsell, sponsorship slots, lead gen.]

## Alignment Notes
- Audience match: [✅/⚠️ + note]
- Brand fit: [✅/⚠️ + note]
- Competitive moat: [✅/⚠️ + note]
- Longevity: [✅/⚠️ + note]

## Build Notes (for the orchestrating agent)
- **Stack hint:** [Svelte / Next / static HTML / Astro — based on feasibility]
- **Data source:** [exact source the build needs access to]
- **On-page wrapper:** page copy + meta + schema needs
- **Launch content:** launch post / press hook angle
- **Tracking:** [what events to instrument — embed loads, completions, email captures]

Decision Guide — common cases

Situation	Action
User has no clear data source	Kill the engagement at Stage 1. No moat = no point.
User has data but it's also publicly available	Ask what their version adds (curation, structure, freshness). If nothing, kill.
Two candidates tie on score	Pick the one with the stronger embed hook (compounds harder over time).
Top candidate fails brand fit only	Acceptable IF the user is willing to build credibility first (1–2 supporting blog posts before tool launch). Note in mitigation.
User pushes "let's just start building" before scoring	Hold the line. The whole point of this skill is to refuse premature build.
User's niche is too broad to assess	Force a narrowing question: "Which sub-niche is the priority for the next 6 months?"

Examples

Example 1: Cosmetics e-commerce site

Stage 1 inputs:

• Niche: mid-tier cosmetics e-commerce, focused on inclusive shade ranges for foundations
• Data: SKU database (3,400 products with hex codes + undertone tags), customer purchase history, returns reasons

Stage 2 candidates:

1. Skin-Tone-to-Foundation Matcher — uploads selfie or picks tone, returns matching SKUs — uses SKU database
2. Lorem Ipsum for Beauty Copy — generic placeholder text — none
3. Foundation Coverage Comparison — side-by-side coverage levels — uses SKU database
4. Return-Reason Stats Dashboard — public stats on which products are returned and why — uses returns data
5. SEO Keyword Tool for Beauty Brands — generic SEO checker — none

Stage 3 scores:

Candidate	Niche	Moat	SEO	Feas	Monet	Total	Verdict
1. Tone Matcher	5	5	5	4	5	24	✅
2. Lorem Ipsum	1	1	1	5	1	9	❌ kill (niche=1, moat=1)
3. Coverage Compare	5	4	4	4	4	21	possible
4. Returns Dashboard	4	5	4	3	2	18	privacy risk + weak monet
5. SEO Keyword Tool	1	1	3	3	2	10	❌ kill (niche=1)

Stage 4 — Tone Matcher alignment:

• Audience match ✅ — exact pain point of every shopper
• Brand fit ✅ — site is already known for shade range
• Competitive moat ✅ — matcher accuracy depends on the SKU undertone tags (proprietary)
• Longevity ✅ — foundation matching is a permanent problem

Stage 5 — Strategy brief: (would be written using the template above; client-side image processing noted as a stack hint)

Example 2: Engineering blog with no data

Stage 1 inputs:

• Niche: engineering blog covering distributed systems
• Data: 47 published blog posts, no databases, no APIs, no proprietary metrics

Action: Kill at Stage 1.

"47 blog posts is content, not a tool data source. Building a tool here means building on commodity APIs (GitHub, Stack Overflow) — which means competitors can clone it in a weekend and your moat is zero. Two paths forward:

1. Build a data set FIRST. Run benchmarks, scrape your own corpus, run a community survey. Come back when you have something exclusive.
2. Skip free tools. Earn links via original research posts and digital PR — that plays to what you do have (writing). Different lever, no tool needed."

Do not soften, do not propose a tool anyway. The honest answer is the only useful one.

Example 3: User pushes to skip the funnel

User: "I already know I want to build a salary calculator for tech jobs. Just help me design it."

Response:

"Before producing the brief, two questions — these are the same gates the funnel runs and they're 30 seconds:

1. What salary data are you using? (Public scraped Glassdoor data has no moat — Levels.fyi already won that. Proprietary survey, payroll-anonymized, or company-disclosed data is a different game.)
2. Who's your existing audience and do they search for salary info? (If you're a dev-tools blog, salary data isn't your niche — links from HR sites won't compound your dev-tools rankings.)

If both pass, I'll write the brief. If either fails, we change the tool — not skip the questions."

References

• Original article framework: How to build free tools with Claude Code for backlinks
• Eugene Schwartz, Breakthrough Advertising — for awareness-stage matching when picking the tool's positioning