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/github-opportunity-radar

@114d6c6

Researches GitHub discovery signals, fast-rising repositories, repository-search supply, Agent Skill gaps, packaging patterns and monetization opportunities. Use when the user asks what is trending on GitHub, what people appear to want, how to earn more stars, or what useful Agent Skill to build next.

  • 1 file
  • 5.1 KB
  • MIT
  • Updated 4 days ago
  • GitHub

Use this Skill: https://skilld.dev/gh/alptugharun/ai-social-media-toolkit/github-opportunity-radar

This session only. Nothing lands on disk.

SKILL.md

≈82 tokens always: the name and description. ≈1.2k when used: this file.

GitHub Opportunity Radar

Find evidence-backed repository and Agent Skill opportunities.

The goal is not to manufacture fake popularity or copy trending repositories.

The goal is to detect real demand, identify under-served jobs and build original, useful assets.

Required References

Read:

  • references/EVIDENCE-POLICY.md
  • references/GITHUB-GROWTH-PLAYBOOK.md
  • references/FOCUS-TRACTION-PLAYBOOK.md
  • references/STRATEGIC-DECISION-FRAMEWORK.md

Core Questions

  1. What is rising on GitHub now?
  2. Which problems are repeatedly earning stars or forks?
  3. Which packaging patterns reduce time-to-value?
  4. Which adjacent categories have demand but weak direct supply?
  5. What original skill could solve a sharper job?
  6. How can the repository prove the skill works?
  7. How should the result be packaged for discovery?
  8. Why now, and why should Alptuğ build this instead of another adjacent idea?
  9. What evidence would weaken the idea?
  10. What is the fastest credible path from proof to money?

Research Inputs

Prefer fresh evidence from GitHub Trending, repository search, repository metadata, READMEs, topics, releases, forks, stars, recent activity and official GitHub documentation.

Use external trend sources only when they materially improve the answer.

Search-Volume Rule

Never invent "GitHub monthly searches".

GitHub does not provide an exact public repository-search-volume metric.

Use labeled proxies:

  • recent star velocity
  • Trending overlap
  • recent repository success
  • search result count
  • topic density
  • fork activity
  • update recency

Strategic Challenge

Before recommending a build, run the three-pass review from references/STRATEGIC-DECISION-FRAMEWORK.md:

  1. thesis
  2. assumption check
  3. resolution

The resolution must be one of:

  • BUILD PROOF
  • VALIDATE BUYER
  • DEEPEN EXISTING
  • WATCH

AI is the default strategic lens, but AI does not automatically win. If a high-momentum adjacent opportunity has materially stronger evidence, it may rank equally or higher.

Winner Teardown

For strong repositories, extract:

  • one-line promise
  • target user
  • first-success time
  • install friction
  • example quality
  • proof / benchmark
  • trust signals
  • cross-tool compatibility
  • community surface
  • monetization path
  • genuine differentiation

Do not copy distinctive wording, branding or proprietary assets.

Skill Gap Analysis

For every candidate skill, define demand evidence, direct supply, missing job, proof contract and distribution contract.

The distribution contract should include install path, one-line value proposition, quick start, example, supported hosts and dependency/API requirements.

Opportunity Score

Use a transparent heuristic:

  • 35% demand evidence
  • 20% freshness
  • 20% direct-supply gap
  • 15% proof potential
  • 10% distribution ease

Apply a penalty for copied concepts, unverifiable claims, high setup friction, paid dependencies required for basic use or an unclear target user.

This is a prioritization heuristic, not a prediction of virality.

Output

GitHub Opportunity Radar

Evidence Window

  • Date:
  • Sources:
  • Confidence:

What Is Rising

Theme Evidence Why it matters Confidence

Repository Pattern Teardown

Pattern Evidence Reusable lesson

Search / Supply Proxies

Query Recent signal Search result count Interpretation

Skill Gap Candidates

Candidate Job Demand Direct supply Proof potential Score

Best Skill to Prototype

  • Name:
  • User:
  • Problem:
  • Input:
  • Output:
  • Proof:
  • Quick start:
  • Why now:

Executive Challenge

For the top candidate include concise answers to:

  • Why this?
  • Why now?
  • Why us?
  • Why would anyone pay?
  • Why might this fail?
  • What proof can we obtain in seven days?
  • What existing skill overlaps?
  • What is the stop condition?

Do not expose private chain-of-thought; provide evidence-backed conclusions only.

Repository Growth Actions

Only include actions supported by current evidence.

Monetization Readiness

Separate what is available now, what requires more usage, and what requires account/tax/payment setup.

Review Gate

  • No fake search-volume numbers
  • No copied wording or proprietary assets
  • Trend claims use fresh evidence
  • Candidate "novelty" is labeled as a proxy, not certainty
  • Proposed skill has a measurable job-to-be-done
  • Human approval required before publishing a new skill
  • Existing-skill overlap checked
  • AI-vs-market-momentum decision stated
  • First buyer / user named
  • Seven-day proof and stop condition defined

Core Principle

Find an important unsolved job, prove the result, then make it effortless to try.

Source: SKILL.md on GitHub

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Signed by skilld at 114d6c6. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub yesterday.

Activeupdated 4 days ago
metadata
{
  "version": "0.1.0",
  "author": "Alptuğ Harun"
}

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