skills-trending-analysis

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Fetches trending skills directly from skills.sh, generates statistics, and creates a trend summary. Optimized for ultra-fast, direct execution without complex setup.

22installs
Sourcesunatanuki/skills
Added on

NPX Install

npx skill4agent add sunatanuki/skills skills-trending-analysis

Tags

Translated version includes tags in frontmatter
skills-trend-analysisdata-fetchingstatistical-analysispython-scriptapi-integration

SKILL.md Content

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Skills Trending Analysis (Direct API)

Fetches trending information from the 
skills.sh
ecosystem by directly communicating with its internal JSON API.
This Skill is designed to be "Zero-Setup Ready" by focusing on standard Python libraries.

Input

A keyword can be optionally specified for filtering.
  • --limit
    : Number of items to fetch (default: 1000).
  • With keyword: Filters the fetched items by the keyword.
  • Without keyword: Fetches the top trending items.
Examples: 
swift
, 
python
, 
agent

Output

Generates results including the following:
  1. Trending summary
  2. Top skills
  3. Keyword ranking
  4. Developer ranking
  5. Ecosystem analysis

Execution Steps (Smart Flow)

1. Try Direct Execution (Fastest)

Most environments already have the necessary 
requests
library. Try running directly:
bash
python3 scripts/fetch_trending.py
python3 scripts/analyze_trending.py --input tmp/trending.json --output tmp/trending_analysis.json

2. If it fails (Environment Setup)

If you get a 
ModuleNotFoundError: No module named 'requests'
, then set up the environment:
Using uv (Recommended):
bash
uv venv
source .venv/bin/activate
uv pip install -r requirements.txt
Using standard pip:
bash
python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt

Data Fetching Strategy

  • Direct API Access: Communicates directly with 
    https://skills.sh/api/skills/all-time
    .
  • No Browser Required: Eliminates dependencies like Chromium or Playwright.
  • Efficient: Uses pagination to fetch precisely what is needed.
  • Cached: Results are cached locally for 1 hour.

Statistical Analysis Specifications

  • summary: Total skills, installs, unique developers/keywords.
  • skill_ranking: Sorted by install counts.
  • keyword_ranking: Frequency and install impact.
  • developer_ranking: Top developers and their specialties.
  • concentration: Market share analysis.

Final Summary by AI

Based on the Python analysis results, the AI will provide a premium trend report. Use the output of 
analyze_trending.py
as the source of truth for all numerical data.

Referenced Files

  • requirements.txt
  • scripts/fetch_trending.py
  • scripts/analyze_trending.py
  • references/output-format.md