/commercial-opportunity-radar

Commercial Opportunity Radar

Find commercially promising opportunities without treating popularity as revenue.

Required References

Read:

• references/EVIDENCE-POLICY.md
• references/GITHUB-GROWTH-PLAYBOOK.md
• references/OPEN-SOURCE-MONETIZATION-PLAYBOOK.md
• references/FOCUS-TRACTION-PLAYBOOK.md
• references/STRATEGIC-DECISION-FRAMEWORK.md
• references/MAPS-AI-OPPORTUNITY-PLAYBOOK.md when Maps / local data is involved

Core Questions

1. Who is the buyer?
2. What recurring problem do they have?
3. What evidence shows the problem matters?
4. Is the problem already solved well?
5. Can the result be demonstrated?
6. Can the first useful version run with low friction?
7. What monetization path fits the problem?
8. Does the opportunity fit the creator / agency / local-business positioning of this repository?
9. Does it strengthen an existing wedge or create unnecessary scope expansion?
10. What external adoption proof exists, and what proof is still missing?
11. Why would the buyer pay now instead of using an existing tool or doing nothing?
12. What is the cheapest seven-day validation?
13. What evidence would make us stop or merge the idea into an existing workflow?

Research Inputs

Prefer:

• current GitHub repository metadata
• stars / forks / update recency
• recent repository search results
• official GitHub Marketplace docs
• current GitHub Actions / Agentic Workflows docs
• public pricing / product docs when specifically researched
• user-provided first-party business data
• permitted Maps / Business Profile / aggregate data when relevant

Never invent:

• revenue
• monthly searches
• conversion rate
• sponsor interest
• customer count
• willingness to pay

Commercial Opportunity Score

Score:

• 25% demand evidence
• 20% buyer clarity
• 15% recurring-use potential
• 15% proof potential
• 10% distribution fit
• 10% implementation feasibility
• 5% monetization-path clarity

Penalize:

• prohibited scraping
• mass unsolicited outreach
• generic clone
• unclear buyer
• no measurable output
• high cost before first value
• weak fit with the repository
• new product/skill lane with no measurable proof plan
• duplication of an existing skill or workflow
• scope expansion that dilutes creator-operations positioning

Focus Gate

Before recommending a new skill or product lane:

1. Check whether an existing skill already covers most of the job.
2. Prefer extending, merging or deepening an existing workflow when possible.
3. Name the external proof required before the idea graduates from research mode.
4. Treat commit count and skill count as internal activity, not adoption.

Strategic Challenge

For the strongest candidate, apply the three-pass review from references/STRATEGIC-DECISION-FRAMEWORK.md and explicitly answer:

• why this
• why now
• why us
• who pays
• what they pay for
• what is recurring
• what could make the economics unattractive
• what can be validated in seven days
• what evidence would make us stop

Compare an AI-native candidate with the strongest high-momentum adjacent candidate. Prefer AI when evidence is similar; allow the adjacent candidate to lead when demand, monetization or distribution evidence is materially stronger.

Monetization Paths

Evaluate:

• implementation / consulting
• hosted SaaS
• paid recurring report
• premium companion assets
• GitHub Sponsors
• GitHub Marketplace Action
• GitHub Marketplace App
• training / workshop
• enterprise support

Do not force every project into SaaS.

B2B Signal-to-Offer Mode

When the user asks for "a radar that makes money":

1. Pick a narrow buyer.
2. Pick one recurring business question.
3. Define permitted signals.
4. Generate an evidence-backed brief.
5. Create a public free summary concept.
6. Define a deeper paid deliverable.
7. Define the implementation/service upsell.
8. Define the KPI proving real demand.
9. Keep outreach human-reviewed.

Output

Commercial Opportunity Radar

Evidence Window

• Date:
• Sources:
• Confidence:

Market Signals

Candidate Opportunities

Best Commercial Test

• Strategic decision: BUILD PROOF / VALIDATE BUYER / DEEPEN EXISTING / WATCH
• Candidate:
• Buyer:
• Pain:
• Free artifact:
• Paid artifact:
• Price hypothesis:
• Proof contract:
• Distribution:
• First 7-day test:

Monetization Ladder

List what can be monetized now versus only after adoption.

Automation Plan

Only automate collection, analysis and draft artifacts that are allowed and useful.

Human Review Gate

• Buyer is explicit
• Evidence is current
• No fabricated revenue claim
• No mass-spam plan
• Data rights checked
• Commercial action requires human approval
• Product is useful without hype
• Existing skill overlap checked
• External proof gap named
• Scope expansion justified
• Why-now case supported
• First payer and paid job are explicit
• AI-vs-market-momentum comparison completed
• Seven-day proof and stop condition defined

Core Principle

Popularity is distribution. Revenue requires a buyer, a recurring problem and proven value.