JetBrains Marketplace Reviews Skill

Fetch, analyze, and visualize reviews for any plugin on the JetBrains Marketplace.

Well-Known Plugin IDs

17718

github-copilot--your-ai-pair-programmer

22282

ai-assistant

To find the ID of any plugin, open its JetBrains Marketplace page — the numeric ID is in the URL:

https://plugins.jetbrains.com/plugin/{ID}-{slug}

Workflow

1. Identify the plugin: Determine the plugin ID from user input (default: 17718 for GitHub Copilot)
2. Determine time scope: Parse user input for the desired time range (e.g. "last 2 weeks", "all reviews", "since 2025-06-01")
3. Fetch reviews: Run the fetch script with the appropriate flags
4. Visualize: Run the visualize script against the fetched JSON
5. Report: Present summary statistics and the generated chart to the user

Email Reports

When the user requests an email report or wants charts embedded in HTML:

1. Fetch reviews as usual
2. Render email charts: Use

   render_email_charts.py

   to generate an HTML report with base64-encoded PNG chart images. Email clients strip

   <script>

   tags, so JavaScript-based charting (Chart.js, Plotly) cannot work. This script uses matplotlib to render charts server-side and embeds them as

   <img src="data:image/png;base64,...">

   — universally supported by email clients.
3. Send: Pass the HTML output as the email body via the

   send-email

   skill

Alternatively, use

visualize_reviews.py --base64

Reference Scripts

The

scripts/

fetch_reviews.py

Fetches reviews from the JetBrains Marketplace API with full pagination support. Works with any plugin ID.

# Default: GitHub Copilot, last 3 weeks
py .github/skills/jetbrains-marketplace-reviews/scripts/fetch_reviews.py \
  --output /path/to/reviews.json

# Specific plugin, last N weeks
py .github/skills/jetbrains-marketplace-reviews/scripts/fetch_reviews.py \
  --plugin-id 22282 --plugin-slug ai-assistant \
  --weeks 8 --output /path/to/reviews.json

# All reviews from the beginning
py .github/skills/jetbrains-marketplace-reviews/scripts/fetch_reviews.py \
  --plugin-id 17718 --all --output /path/to/reviews.json

# Date range with full content
py .github/skills/jetbrains-marketplace-reviews/scripts/fetch_reviews.py \
  --since 2025-01-01 --until 2025-06-30 --full-content \
  --output /path/to/reviews.json

CLI options:

--plugin-id ID

17718

--plugin-slug SLUG

github-copilot--your-ai-pair-programmer

--all

--weeks N

--since YYYY-MM-DD

--until YYYY-MM-DD

--full-content

--output PATH

scripts/reviews.json

visualize_reviews.py

Generates visualization charts from the JSON data. Auto-adapts layout and granularity based on the time span of the data:

py .github/skills/jetbrains-marketplace-reviews/scripts/visualize_reviews.py \
  --input /path/to/reviews.json --output /path/to/chart.png \
  --title "My Plugin" --no-show

CLI options:

--input PATH

scripts/reviews.json

--output PATH

scripts/review_analysis.png

--title TEXT

JetBrains Plugin

--no-show

--base64

When

--base64

.json

{chart_name: base64_png_string}

<img>

render_email_charts.py

Renders all review charts as base64-encoded PNG images and outputs a complete HTML report fragment suitable for embedding in email bodies. This is the recommended approach for email reports since email clients strip

<script>

# Generate email-ready HTML report
py .github/skills/jetbrains-marketplace-reviews/scripts/render_email_charts.py \
  --input /path/to/reviews.json --output /path/to/report.html \
  --title "GitHub Copilot"

# Also export individual charts as JSON for custom use
py .github/skills/jetbrains-marketplace-reviews/scripts/render_email_charts.py \
  --input /path/to/reviews.json --output /path/to/report.html \
  --title "GitHub Copilot" --json-output /path/to/charts.json

CLI options:

--input PATH

scripts/reviews.json

--output PATH

scripts/email_report.html

--title TEXT

JetBrains Plugin

--json-output PATH

Charts included:

• Rating Distribution (bar chart)
• Average Rating by Year (bar chart, long-range only)
• Monthly Review Volume (bar chart)
• Monthly Average Rating Trend (line chart with 5-bucket moving avg + neutral line)
• Monthly Rating Breakdown (stacked bar)
• Rolling Average Rating (area chart, when enough data)
• Yearly Summary table, KPI cards, recent feedback tables

The output HTML uses inline styles and

<img src="data:image/png;base64,...">

API Details

GET https://plugins.jetbrains.com/api/plugins/{plugin_id}/comments?size=100&page={page}

• API returns max 100 reviews per page; use

  page=1,2,3…

  for pagination
• Reviews are sorted newest-first

JSON Data Schema

Each review object in the output JSON:

{
  "id": 134243,
  "date": "2026-02-10",
  "rating": 5,
  "has_replies": false,
  "link": "https://plugins.jetbrains.com/plugin/17718-.../reviews#review=134243",
  "author": "Enes Oscar",
  "comment": "Overall, it provides a great experience..."
}

• rating

  : 0 = no rating given, 1-5 = star rating

• author

  and

  comment

  are only present when

  --full-content

  is used

Usage Examples

• "Get the last 2 weeks of JetBrains Copilot reviews" →

  --plugin-id 17718 --weeks 2

• "Fetch all Copilot JetBrains reviews ever" →

  --plugin-id 17718 --all

• "Show reviews for JetBrains AI Assistant from January 2025" →

  --plugin-id 22282 --plugin-slug ai-assistant --since 2025-01-01 --until 2025-01-31

• "Visualize the rating trend for the last 6 months" →

  --weeks 26

• "Analyze recent feedback with full review text" →

  --weeks 3 --full-content

Dependencies

• Python 3.x (stdlib only for fetching)
• matplotlib, numpy (for visualization)
• scipy (optional, for trend smoothing)

Install:

py -m pip install matplotlib numpy scipy

Notes

• Reviews with

  rating: 0

  mean the user left a comment without giving a star rating
• The API rate-limits large batch requests; the fetch script paginates responsibly
• For long ranges, the visualize script automatically switches to monthly aggregation and a 6-panel layout with yearly summaries, stacked breakdowns, and rolling averages