/trending-repos-discovery

name: trending-repos-discovery
description: Discover and analyze trending GitHub repositories from TrendShift and other sources — evaluate usefulness, extract learnings, and identify valuable skills/tools
tags: [github, trending, research, discovery, skills]
related_skills: [github-repo-management, ecosystem-tool-evaluation]
origin: unknown
source_license: see upstream
language: en

Trending Repos Discovery

Discover and analyze trending GitHub repositories from TrendShift and other sources. Evaluate usefulness, extract learnings, and identify valuable skills/tools for adoption.

When to Use

• User asks "apa yang trending?" or "what's trending?"
• User wants to discover new tools/libraries
• User asks about specific trending repo
• Looking for inspiration or best practices
• Evaluating whether to adopt new tools

Sources

1. TrendShift (Primary)

**URL:** https://trendshift.io/

**What it tracks:**

• GitHub's most-discussed open-source projects
• Daily engagement rankings
• Real-time mentions from X/Twitter
• Discussions from Reddit and Hacker News

**How to fetch:** See `references/trendshift-fetch-methods.md` for TinyFish and GitHub API examples

2. GitHub Trending (Alternative)

**URL:** https://github.com/trending

**Languages:**

• All languages: https://github.com/trending
• Python: https://github.com/trending/python
• TypeScript: https://github.com/trending/typescript
• Rust: https://github.com/trending/rust

3. GitHub API (For Details)

See `references/trendshift-fetch-methods.md` for API usage examples.

**Rate limit:** 60 requests/hour (unauthenticated), 5000/hour (authenticated)

Analysis Workflow

Phase 1: Fetch Trending List

1. **Fetch from TrendShift** (primary source) 2. **Extract repo names** (owner/repo format) 3. **Get first 10-20 repos** (manageable batch)

Phase 2: Get Repo Details

For each repo, fetch from GitHub API:

• Stars, forks, watchers
• Description
• Language
• Topics
• Created/updated dates

**Batch strategy:**

• Fetch 10 repos at a time
• If rate limited, wait or use cached data

Phase 3: Categorize by Usefulness

For each repo, assess:

A. Relevance Score

| Factor | Weight | Criteria | |--------|--------|----------| | **Stars** | 30% | > 10K = high, 1K-10K = medium, < 1K = low | | **Description match** | 30% | Keywords match user's interests | | **Language** | 20% | User's tech stack (Python, TypeScript, Rust) | | **Recency** | 10% | Updated in last 30 days | | **Topics** | 10% | Relevant tags (ai, agent, skills, tools) |

B. Usefulness Categories

**✅ Highly Useful:**

• Directly applicable to user's projects
• Solves current problems
• Fills gaps in toolset
• High stars (> 10K) + active development

**🟡 Potentially Useful:**

• Interesting but not immediate need
• Requires evaluation/testing
• Medium stars (1K-10K)
• Niche use case

**❌ Not Useful:**

• Wrong tech stack (e.g., Mac-only for Linux user)
• Too niche (e.g., biology tools for software dev)
• Duplicate of existing tools
• Low stars (< 1K) + no clear value

Phase 4: Extract Learnings

For useful repos, identify:

1. Skills/Patterns

• What skills does it provide?
• What patterns does it use?
• What best practices does it demonstrate?

**Example (obra/superpowers):**

• Skills framework architecture
• Agentic workflow patterns
• Production-ready methodology

2. Tools/Libraries

• What tools does it introduce?
• What dependencies does it use?
• What integrations does it support?

**Example (addyosmani/agent-skills):**

• Production-grade engineering patterns
• Web performance optimization
• Chrome DevTools expertise

3. Concepts/Ideas

• What problems does it solve?
• What approaches does it take?
• What innovations does it introduce?

**Example (andrej-karpathy-skills):**

• LLM coding pitfalls
• AI code quality patterns
• Production AI best practices

Phase 5: Present Analysis

**Format:**

## 🔥 TOP TRENDING REPOS

### 1. owner/repo ⭐ X,XXX stars 🏆

**Description:** [One-line description]

**Berguna?** ✅ SANGAT / 🟡 MUNGKIN / ❌ TIDAK

**Why:**
- [Reason 1]
- [Reason 2]
- [Reason 3]

**Use Case:** [How user can use it]

**Action:** [What to do next]

---

## 🎯 RECOMMENDED ACTIONS

### Priority 1: MUST CHECK 🔥
1. [Repo 1] - [Why]
2. [Repo 2] - [Why]

### Priority 2: WORTH CHECKING ✅
3. [Repo 3] - [Why]

### Priority 3: MAYBE ⚠️
5. [Repo 5] - [Why]

## ❌ SKIP THESE
- [Repo X] - [Why not useful]

User Preference Patterns

For "Analisa trending repos"

When user asks to analyze trending repos:

**DO:**

• ✅ Fetch from TrendShift (most comprehensive)
• ✅ Get details for top 10-20 repos
• ✅ Categorize by usefulness (✅ 🟡 ❌)
• ✅ Explain WHY each is useful/not useful
• ✅ Provide actionable recommendations
• ✅ Group by priority (must check, worth checking, maybe, skip)

**DON'T:**

• ❌ Just list repo names (no value)
• ❌ Skip usefulness assessment
• ❌ Recommend everything (no filtering)
• ❌ Ignore user's tech stack/constraints

For "Ada yang berguna gak?"

When user asks if trending repos are useful:

**Response pattern:** 1. **Quick verdict:** "ADA YANG BERGUNA? ✅ BANYAK!" or "❌ TIDAK ADA" 2. **Top picks:** List 3-5 most useful repos 3. **Why useful:** Explain specific benefits 4. **Action:** What to do next (clone, study, adapt)

**Example:**

✅ ADA YANG MENARIK — review dulu sebelum klaim apapun

1. obra/superpowers — Skills framework
2. andrej-karpathy-skills — coding guidelines
3. mattpocock/skills — TypeScript / engineering workflows
4. addyosmani/agent-skills — frontend & performance practices

Mention star counts only when reporting raw findings; do not aggregate
them into "X K combined stars" or claim authors as contributors to a
downstream repo. Authors of upstream public skill repos have not endorsed
or contributed to any aggregator unless they explicitly say so.

MAU GUE CLONE & ANALISA SEKARANG? 🚀

Evaluation Criteria

For Skills Repos

**Look for:**

• ✅ SKILL.md or .claude dire