github-trending-analyzer

github-trending-analyzer is a skill for Claude Code, Codex from Dianel555/DSkills. It costs 65 tokens per session (2,905 once invoked), scanned A, original, MIT.

A workflow that collects repositories from GitHub's Trending page and produces Markdown reports with structured analysis in Chinese. GitHub Trending lists repositories that are receiving unusual attention, and the workflow can compare current results with saved history.

In plain words
What is it for?
Use it for daily, weekly, or monthly repository discovery, theme classification, historical comparisons, brief reports, or optional per-project analysis.
Why use it?
It reduces the manual work of finding notable repositories, grouping them by topic, and tracking how trends change over time.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/dianel555/dskills/github-trending-analyzer
Any agent
npx skills add Dianel555/DSkills --skill github-trending-analyzer
Clone the repo
git clone --depth 1 https://github.com/Dianel555/DSkills

Made for: Claude Code, Codex.

Its marketplace also offers this one on its own, as the plugin github-trending-analyzer/plugin install github-trending-analyzer after adding the marketplace above.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for github-trending-analyzer

README.md
[![agentmods](https://agentmods.dev/badge/skills/dianel555/dskills/github-trending-analyzer.svg)](https://agentmods.dev/skills/dianel555/dskills/github-trending-analyzer)
Your own site
<a href="https://agentmods.dev/skills/dianel555/dskills/github-trending-analyzer"><img src="https://agentmods.dev/badge/skills/dianel555/dskills/github-trending-analyzer.svg" alt="Measured on agentmods" height="20"></a>
Per session 65 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,905 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00065 $0.02905
Opus 5 $0.00032 $0.01452
Sonnet 5 $0.00013 $0.00581
Haiku 4.5 $0.00006 $0.00291

Measured 5d ago against content hash 41da4da8147d, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

github-trending-analyzer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/github-trending-analyzer/SKILL.md · 257 lines

How it starts

The opening of the file, as written. The whole thing — 257 lines — stays where its author put it; the contents beside it link to each section on GitHub.

A workflow protocol for tracking GitHub trending repositories with LLM-powered analysis. Fetches trending projects, enriches each with structured Chinese insights (what/analogy/help/who), classifies by themes, compares against historical snapshots, and generates reports in two modes — a compact brief (default) or a detailed report with per-project analysis (opt-in).

Trigger Signals

  • GitHub trending analysis
  • Weekly tech trend report
  • Repository discovery automation
  • Incremental analysis refresh
  • Theme-based repo categorization

Preconditions

  • HTTP access to github.com/trending (no auth required for public trending)
  • LLM backend capable of JSON-structured output (for the 4-field analysis schema)
  • File system access for memory cache and report output
  • HTML parsing capability (regex or DOM parser)

Strategy

Run the five-step pipeline in order.

Step 1: Fetch trending HTML

Construct the URL with time range and optional language filter:

https://github.com/trending[/{language}]?since={daily|weekly|monthly}

Fetch with a browser User-Agent to avoid bot detection. Parse the HTML to extract:

  • name (org/repo)
  • url (full GitHub link)
  • desc (one-line description from the page)
  • lang (primary language)
  • stars (total stargazers count)
  • today_stars (increment for this period)

Regex patterns (reference from source):

  • Project name: <h2[^>]*>.*?<a href="/([^"]+)"
  • Description: <p class="[^"]*col-9[^"]*"[^>]*>\s*(.*?)\s*</p>
  • Language: <span itemprop="programmingLanguage">([^<]+)</span>
  • Stars: parse from /stargazers link text after stripping HTML tags
  • Today increment: ([\d,]+)\s*stars?\s*(?:this|today) (case-insensitive)

Step 2: Batch LLM analysis

For each batch of 5 projects (to avoid token limits), send this prompt to your LLM:

Analyze the following {N} GitHub Trending projects. Output strict JSON array.
Each project needs 4 fields:
- what: What it is (≤30 Chinese characters)
- analogy: Life analogy (one sentence)
- help: What it helps you do (2 items, each ≤40 chars, array)
- who: Who needs it (one sentence, ≤30 chars)

Project list:
1. org/repo (Language) — description...
2. ...

Output ONLY the JSON array, no other text. Example:
[{"name":"org/repo","what":"...","analogy":"...","help":["...","..."],"who":"..."}]

Read the full file on GitHub · 257 lines

Files

What ships with it

3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 5d ago First seen · 257 lines · 65 tokens per session scan A 41da4da8147d

Subscribe to this mod's changes

github-trending-analyzer is a skill published in the GitHub repository Dianel555/DSkills (64 stars, last pushed yesterday), licensed MIT. It adds 65 tokens to every session and 2,905 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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