GitHub Emerging Repositories Radar

Find and prioritize GitHub repositories for integration, partnership, sponsorship, or monitoring.

This Actor combines GitHub Trending with repository metadata and ranks results by fit, adoption, activity, maintenance, license, and momentum. It answers: which open source projects should I investigate next?

Why use GitHub Emerging Repositories Radar?

GitHub search produces a list. This Actor turns that list into a research queue:

• ranks repositories with an opportunity score from 0 to 100;
• separates active, stale, inactive, and archived projects;
• identifies early, growing, and established adoption;
• highlights declared licenses;
• adds a daily, weekly, monthly, or yearly trending signal when the repository appears on GitHub Trending;
• changes the recommended next action for integration, partnership, sponsorship, or monitoring;
• produces clean JSON rows for spreadsheets, CRM research, and downstream Apify workflows.

What input does the GitHub repository finder accept?

The required input is one query, such as browser automation, ecommerce scraping, LLM evaluation, or privacy analytics.

Optional filters are language, createdAfter, businessGoal, and maxResults. runId is retained in RUN_SUMMARY for workflow reconciliation.

Example:

{
  "query": "browser automation",
  "language": "JavaScript",
  "businessGoal": "integrate",
  "timeWindow": "weekly",
  "maxResults": 10
}

Input fields

Field	Required	What it changes
query	Yes	Technology, problem, or theme, such as browser automation.
language	No	Limits results to one primary language.
businessGoal	No	Frames the action as integration, partnership, sponsorship, or monitoring.
timeWindow	No	Uses daily, weekly, monthly, or yearly Trending signals.
createdAfter	No	Keeps repositories created after an ISO date.
maxResults	No	Controls dataset size from 1 to 100.
runId	No	Stores an external identifier in RUN_SUMMARY.

What data does the GitHub repository finder return?

Each repository becomes one dataset row:

{
  "repository": "citrolabs/ego-lite",
  "url": "https://github.com/citrolabs/ego-lite",
  "description": "The fastest browser for AI agents to run browser automation...",
  "topics": ["ai-agent", "automation", "browser-automation", "codex"],
  "language": "JavaScript",
  "stars": 15106,
  "forks": 786,
  "createdAt": "2026-04-16T12:51:09Z",
  "lastActivity": "2026-09-06T04:30:02Z",
  "license": "MIT",
  "maintenanceStatus": "active",
  "adoptionTier": "established",
  "opportunityScore": 91,
  "recommendedAction": "investigate_integration",
  "reason": "Strong keyword/topic fit; active maintenance; established adoption with MIT license.",
  "evidenceTier": "public_repository_metadata"
}

When a repository also appears on GitHub Trending, the Actor uses that signal internally in opportunityScore. The selected window stays in RUN_SUMMARY, while the public dataset keeps consistently useful repository fields.

Scores are prioritization heuristics, not investment, legal, security, or acquisition advice. evidenceTier indicates that the row is based on public repository metadata; it does not certify code quality, license compliance, project governance, or future activity.

How the opportunity score works

The score combines:

• query fit across the repository name, description, and topics;
• adoption from stars and forks, using logarithmic scaling;
• activity recency based on the latest repository push;
• maintenance signals such as archive status and declared license metadata;
• a bounded momentum bonus when the same repository appears in the selected GitHub Trending window.

It does not inspect code, vulnerabilities, maintainers, funding, or commercial viability. Treat ranked rows as research candidates, not automatic approvals.

Who uses this GitHub repository radar?

Integration research

Search for a technology category, filter by language, and prioritize active repositories with a declared license.

Partnership discovery

Find maintained projects with meaningful adoption that may be relevant to ecosystem or developer-relations outreach.

Sponsorship research

Use the sponsorship goal to create a shortlist of visible open source projects, then perform human review before contacting maintainers.

Recurring monitoring

Schedule weekly or monthly runs for the same themes and compare the output over time. The Actor is an on-demand discovery and ranking step; it does not itself send alerts.

How do I run the Actor through the API?

Start a run through the Apify API:

curl -X POST "https://api.apify.com/v2/acts/YOUR_USERNAME~github-emerging-repositories-radar/runs" \
  -H "Authorization: Bearer YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"query":"browser automation","language":"JavaScript","businessGoal":"integrate","maxResults":10}'

Read the default dataset with:

curl "https://api.apify.com/v2/acts/YOUR_USERNAME~github-emerging-repositories-radar/runs/last/dataset/items" \
  -H "Authorization: Bearer YOUR_APIFY_TOKEN"

Keep maxResults small for interactive workflows and increase it for broader market mapping.

How can I use it with MCP and automation?

The Actor has no direct MCP connector or external writeback. It can be called through Apify-compatible MCP tooling or workflows. A typical pipeline runs it on a schedule, filters by opportunityScore or maintenanceStatus, and sends candidates to a review queue. Use runId to reconcile runs.

How do I troubleshoot the Actor?

The Actor returns no repositories

Broaden query, remove language, or move createdAfter further back. GitHub applies search qualifiers together.

Trending data does not appear as separate columns

This is intentional. Sparse Trending matches affect the score internally and are summarized in RUN_SUMMARY.

A repository looks popular but ranks below another project

Stars are only one component. Read reason, maintenanceStatus, createdAt, and lastActivity together.

The license field is empty or says NOASSERTION

No clear SPDX license was returned. Do not interpret an empty value as permission to reuse the code.

The run hits a GitHub API limit

Wait for the GitHub rate-limit window and retry with fewer results.

Limitations

• Discovery combines the public GitHub Trending page with the public GitHub repository API and its indexed metadata.
• The Actor does not clone repositories, inspect source code, evaluate security, contact maintainers, or verify sponsorship availability.
• GitHub search and API limits apply. A single run intentionally keeps the request footprint small.
• Opportunity scores are explainable heuristics using keyword fit, stars, forks, recent activity, archive state, and license metadata.
• A missing license is a research signal, not a legal conclusion.
• Public repository metadata may change between runs.
• GitHub Trending does not provide arbitrary keyword search, so theme searches use the GitHub API while Trending contributes momentum when a result matches.

FAQ

Does it search repository topics?

Yes. GitHub search covers the query against repository metadata, and returned topic labels are included when available.

Can I use it for private repositories?

No. This version is scoped to public repository discovery and does not request or store GitHub credentials.

Is this a talent finder?

No. It does not collect contributor profiles, emails, or personal contact information.

Is it legal to use?

Use the public API responsibly and follow GitHub's terms, rate limits, and applicable laws. The Actor is not legal advice and does not certify a downstream use.

Does it contact maintainers or send sponsorship messages?

No. It produces a research shortlist only. It does not collect personal contact details or perform outreach.

Feedback and support

Report unexpected results through the Actor's Issues tab with the input, run ID, and one example repository. Never include access tokens. No upstream Actor is required.

Changelog

0.1.0

• Initial public repository discovery and opportunity ranking workflow.