RubyGems Package Intelligence — Gem Health & Downloads (AI)

Before you add a Ruby dependency, know what you're pulling in. Give this Actor a list of RubyGems gem names and it turns each one into a clear intelligence record: how often it's downloaded, how many dependencies it drags in, when it was last released, how fast it ships, who maintains it, its license — and an AI risk read that tells you plainly whether a gem is active, stale, or effectively abandoned.

You bring the gem names. It hands back a dependency due-diligence sheet.

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The flow

1. Paste RubyGems gem names        2. The Actor gathers facts            3. Get an AI risk read
   (rails, devise, sidekiq,   →       RubyGems API (gems +          →      downloads · deps · age ·
    ...)                               versions, public, no key)            license · maintenance · flags

1. Paste RubyGems (Ruby) gem names into the packages field — one per line.
2. The Actor pulls public data for each: the RubyGems API gem endpoint for metadata, total/version downloads, dependencies and license, and the versions endpoint for version count, latest release date and release cadence. No API key, no scraping of login-walled pages.
3. The AI layer reads the facts and returns a maintenance signal, a popularity tier, concrete risk flags and a two-sentence summary — grounded only in the data, never invented.

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What you get per gem

For every gem, the Actor returns:

1. Identity & release — latestVersion, summary, versionCount, lastRelease (ISO timestamp), lastReleaseAgeDays (how long since the newest release) and releaseCadenceDays (average days between releases across history).
2. Reach — totalDownloads (all-time) and latestVersionDownloads from RubyGems, so you can tell a ubiquitous library from a weekend experiment.
3. Footprint — runtimeDependenciesCount and developmentDependenciesCount (how many gems it requires), and license.
4. Maintenance signals — authorsCount, and the repository, homepage and documentation URLs.

Then the AI layer (OpenAI gpt-4o-mini, a fast and low-cost model) adds:

• maintenanceSignal — active, maintained, stale, or abandoned, from release recency.
• popularityTier — niche, growing, popular, or ubiquitous, from download volume.
• riskFlags — short, data-backed phrases: "unmaintained (last release >18mo)", "single author", "no license declared", "heavy dependency tree", "very few releases".
• aiSummary — two factual sentences on the gem and its risk posture.
• suggestedAlternatives — only well-known, widely-trusted substitutes for the same job, else [].

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Three ways people use it

• Ruby dependency due diligence — before a new gem lands in your Gemfile or .gemspec, run a RubyGems package analysis to see downloads, license, dependency count and whether it's still maintained. Catch an abandoned gem, a no-license release or a single-maintainer bus factor before it's in your build.
• Supply-chain risk — audit an existing dependency list for Ruby dependency risk: surface unmaintained gems, stale projects and heavy dependency trees across your whole stack in one run. A standing input for your supply chain security reviews.
• Library selection — comparing candidates for the same job? Line them up and let download tier, maintenance signal and suggestedAlternatives make the call obvious.

Keywords: RubyGems package analysis, Ruby dependency risk, supply chain, unmaintained gems.

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Input

Field	Type	Notes
packages	array	Required. RubyGems gem names, one per line (e.g. rails, devise, sidekiq). Version pins and rubygems.org/gems/... URLs are tolerated and normalised.
maxResults	integer	Cap how many gems to analyze. Default 200.
maxConcurrency	integer	Gems processed in parallel. Default 6.
model	string	OpenAI model override. Default gpt-4o-mini.

Minimal input example

{
  "packages": ["rails", "devise", "sidekiq"]
}

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Output example

{
  "package": "rails",
  "latestVersion": "8.1.4",
  "summary": "Ruby on Rails is a full-stack web framework optimized for programmer happiness and sustainable productivity.",
  "license": "MIT",
  "totalDownloads": 799616881,
  "latestVersionDownloads": 1262910,
  "lastRelease": "2026-09-24T14:22:14.180Z",
  "lastReleaseAgeDays": 18,
  "releaseCadenceDays": 14,
  "versionCount": 521,
  "authorsCount": 1,
  "runtimeDependenciesCount": 13,
  "developmentDependenciesCount": 0,
  "repository": "https://github.com/rails/rails/tree/v8.1.4",
  "homepage": "https://rubyonrails.org",
  "documentation": "https://api.rubyonrails.org/v8.1.4/",
  "maintenanceSignal": "active",
  "popularityTier": "ubiquitous",
  "riskFlags": [],
  "suggestedAlternatives": ["sinatra", "hanami"],
  "aiSummary": "rails is a ubiquitous, permissively licensed full-stack web framework with hundreds of millions of all-time downloads and an actively maintained release line. It carries a moderate runtime dependency tree and shows no significant supply-chain risk."
}

A gem that is not found on RubyGems comes back with the same shape plus an error field (and is not charged).

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Pay-per-event pricing

This Actor uses pay-per-event billing with a single event:

Event	Price	Charged when
package-analyzed	$0.10	Once per gem successfully analyzed (facts gathered + AI risk read produced).

The Actor logs its OpenAI token usage and the estimated AI cost per gem at the end of every run, so the event price always stays safely above the model cost.

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Data source

Everything comes from public, key-less sources: the RubyGems API gem endpoint (https://rubygems.org/api/v1/gems/<gem>.json) for metadata, downloads, dependencies and license, and the versions endpoint (https://rubygems.org/api/v1/versions/<gem>.json) for version count, latest release date and release cadence. Rate limiting or a missing versions record is handled gracefully — the record still ships, just without release history.

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Setup

The AI layer calls the OpenAI API. Set the environment variable / secret OPENAI_API_KEY on the Actor. The fact-gathering step (downloads, dependencies, license, maintenance) needs no key.

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Use it from an AI agent (Apify MCP server)

This Actor is available through the Apify MCP server, so AI agents (Claude, ChatGPT, or anything that speaks MCP) can call it as a tool — hand it a list of packages and read back the intelligence records — with no custom integration code.

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Run it locally

npm install
# put your input in storage/key_value_stores/default/INPUT.json
export OPENAI_API_KEY=sk-...
apify run -p

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Related actors

• npm Package Intelligence — The Node.js twin of this Actor: downloads, dependencies, maintenance and AI risk for any npm package.
• PyPI Package Intelligence — The Python twin: downloads, dependencies, maintenance and AI risk for any PyPI package.
• GitHub Repo Analyzer — Health, activity and maintenance signals for any GitHub repository.
• CVE Vulnerability Lookup — Look up known vulnerabilities and severity for packages and software.

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Part of the No Niner toolkit — no-code web scraping, enrichment & AI data tools, all pay-per-use. Browse the full set at noniner.io.