What is github-trending?

A tool that collects popular and fast-growing GitHub repositories, the projects hosted on GitHub, over weekly, monthly, daily, and monthly-growth periods. It marks repositories related to AI and software development.

Creating a dated Markdown research report of trending AI and developer repositories in a vault.

It avoids manually checking several GitHub lists and helps distinguish newly popular projects from older projects that are suddenly gaining attention.

github-trending — Skill for Claude Code and Codex by cth9191

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.

Any agent

npx skills add cth9191/morning-intel --skill github-trending

Clone the repo

git clone --depth 1 https://github.com/cth9191/morning-intel

Made for: Claude Code, Codex.

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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/cth9191/morning-intel/github-trending/github.svg)](https://agentmods.dev/skills/cth9191/morning-intel/github-trending)

Your own site

<a href="https://agentmods.dev/skills/cth9191/morning-intel/github-trending"><img src="https://agentmods.dev/badge/skills/cth9191/morning-intel/github-trending/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/cth9191/morning-intel/github-trending"><img src="https://agentmods.dev/badge/skills/cth9191/morning-intel/github-trending.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 92 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 723 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

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.

Model	Per session	Once invoked
Fable 5.1	$0.00092	$0.00723
Opus 5.5	$0.00037	$0.00289
Sonnet 5.5	$0.00018	$0.00145
Haiku 4.5	$0.00009	$0.00072

Measured 2mo ago against content hash c4f01d1a1d69, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

github-trending 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 2mo ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/fetch.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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/SKILL.md · 55 lines

How it starts

The opening of the file, as written. The whole thing — 55 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Mechanical fetch — no AI judgment needed. Four metrics, ranks by stars / star-growth, flags AI/dev relevance from topics + description, writes markdown.

The four metrics

This Week — repos created:>7d, sorted by stars (REST search API).
This Month — repos created:>30d, sorted by stars (REST search API).
Fastest Growing (24h) — top AI/dev repos by stars gained today, scraped from github.com/trending?since=daily. Catches same-day spikes.
Fastest Growing (30d) — top AI/dev repos by stars gained this month, scraped from github.com/trending?since=monthly. The durable breakouts.

Metrics 3 & 4 are the velocity pair. Unlike 1 & 2 (which filter on created:<date> and so only ever see brand-new repos), they surface a repo of any age that is suddenly ripping. A pure stars-sorted API query cannot do velocity — the top of that list is all mega-repos, so a single-digit-k sleeper never appears. The trending page is GitHub's own growth ranking.

Output

<VAULT>/inbox/research/github-trending/YYYY-MM-DD-trending.md — VAULT from AGENTIC_OS_VAULT in ~/.claude/.env, default ~/the-vault.

Sections: Top 10 This Week, Top 5 This Month, Top 10 Fastest Growing (24h), Top 10 Fastest Growing (30d), Content Radar (AI-pick summary). Each repo block: stars, language, created date, topics, description, [AI/DEV] flag. If a scrape fails, that section degrades gracefully and the others still render.

Manual invocation

python ~/.claude/skills/github-trending/scripts/fetch.py

AI/Dev classifier

Substring match (case-insensitive) on topics OR description against: ai, llm, gpt, claude, anthropic, agent, mcp, prompt, embedding, rag, deepseek, kimi, gemini, openai, copilot, codex, fine-tun, transformer, ollama, langchain, chatgpt

Not perfect — false positives on "DarkGPT"-style spam, false negatives on AI projects with vague descriptions. Good enough for a glance.

Rate limit

Per run: 2 Search API calls + 2 trending-page GETs + up to ~1 enrich call per trending repo scanned (GET /repos/{full}). Unauthenticated Search = 10 req/min; core REST = 60/hr per IP — fine for a few runs/day, but bursty manual re-runs can exhaust it. Set GITHUB_TOKEN in ~/.claude/.env to lift both to 5000/hr.

Read the full file on GitHub · 55 lines

Files

What ships with it

1 file 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.

scripts/fetch.py 14 KB runs code

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.

2mo ago First seen · 55 lines · 92 tokens per session scan A c4f01d1a1d69

Subscribe to this mod's changes

github-trending is a skill published in the GitHub repository cth9191/morning-intel (17 stars, last pushed 2mo ago), licensed MIT. It adds 92 tokens to every session and 723 once invoked, about $0.0004 per session on Opus 5.5. 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 2026-08-31.

Analytics and metrics Research

github-trending next to 6 skills from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
github-trendingcth9191/morning-intel	Skill	17	2mo ago	MIT	A	92	Claude Code, Codex
imagegenopenai/codex	Skill	134k	today	Apache-2.0	A	113	Codex
local-ai-agentsmicrosoft/ai-agents-for-beginners	Skill	79k	today	MIT	A	200	Claude Code, Codex
playwright-climicrosoft/playwright	Skill	99k	today	Apache-2.0	A	19	Claude Code
systematic-debuggingobra/superpowers	Skill	314k	3d ago	MIT	A	21	Claude Code
next-cache-components-adoptionvercel/next.js	Skill	143k	today	MIT	A	95	Claude Code
chat-pet-sprite-creationmicrosoft/vscode	Skill	195k	today	MIT	A	53	Claude Code, Codex