github-trending
Skill8 starsChanged 3 months agoMITView on GitHub
Discover trending GitHub repositories across all AI/tech domains. Supports domain-specific browsing: robotics, VLA, agents, MCP, CV, LLM, autonomous driving, 3D, audio, RL, and more. Bilingual output (Chinese + English).
11 other projects use a version of this.
Adopted by
Most recently taken up by
- hoodini/ai-agents-skillstheir own version, first seen Oct 25, 2026
- aaronjmars/miroshark-aeontheir own version, first seen Oct 21, 2026
- aeonfun/aeontheir own version, first seen Oct 20, 2026
- MiroShark/miroshark-aeontheir own version, first seen Oct 17, 2026
- Makiya1202/awesome-codex-computer-usetheir own version, first seen Oct 11, 2026
- aaronjmars/aeontheir own version, first seen Oct 8, 2026
Other versions11 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 11
- huangkiki/dailypaper-skills★ 1.3ksame name
- aaronjmars/aeon★ 789same name
- aeonfun/aeon★ 789same name
- hoodini/ai-agents-skills★ 295same name
- wwwzhouhui/skills_collection★ 292same name
- aaronjmars/miroshark-aeon★ 20same name
- MiroShark/miroshark-aeon★ 20same name
- tunsuy/ai-skills★ 4same name
- Makiya1202/ai-agents-skills★ 2same name
- Makiya1202/awesome-codex-computer-use★ 2same name
1 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository32 other files it gives its agents.
- ai-genSkill
- any2mdSkill
- assignment-wordSkill
- cheatsheatSkill
- claude2antiSkill
- claude2codexSkill
- codex2claudeSkill
- fincomp-deckSkill
- git-pushSkill
- html2mdSkill
- html2pdfSkill
- html2texSkill
- html-slidesSkill
- img-readerSkill
- latex-beamerSkill
- markitdownSkill
- md2docxSkill
- md2texSkill
- mergeSkill
- notesSkill
- paper-html-onepageSkill
- paper-reproSkill
- pdf2wordSkill
- pdf-readerSkill
- posterSkill
- repo-docsSkill
- repo-docs-zhSkill
- resume-builderSkill
- web-search-fallbackSkill
- word2htmlSkill
- word2mdSkill
- word2pdfSkill
The file
Show its rules and text
We split this skill into the rules it gives an agent
22 rules. 0 are common, 15 are distinctive, and 7 are very specific to this project.
0
Common
Most of the 8 edited versions we read keep these.
15
Distinctive
This author's own choices. Worth a look.
7
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 39
Fallback: If GitHub API is rate-limited (check for rate limit in response), switch to WebSearch-only mode and inform the user.
- Very specific: line 43
Read references/search-queries.md for pre-built API query templates organized by domain.
- Very specific: line 69
Read references/search-queries.md for query templates
- Distinctive: line 70
In parallel: run GitHub API queries for the top 3-5 domains:
- Distinctive: line 76
In parallel: run 2-3 WebSearch queries for recent trending repos
- Distinctive: line 82
When a domain flag is provided, focus the search on that specific area.
- Very specific: line 85
Read references/search-queries.md and look up the corresponding domain section
- Distinctive: line 86
In parallel: run 2-3 GitHub API queries from the domain's topic/keyword templates
- Distinctive: line 87
In parallel: run 1-2 WebSearch queries from the domain's WebSearch templates
- Very specific: line 108
In parallel: run GitHub API queries with created:>2025-01-01 filters across multiple topics
- Distinctive: line 109
In parallel: run WebSearch for "GitHub trending 2025 2026" across domains
- Distinctive: line 124
Search by any keyword provided by the user.
- Very specific: line 138
Use web_reader to fetch and summarize the README
- Distinctive: line 143
Always use bilingual headers and Markdown tables:
- Very specific: line 180
GitHub API rate limit: If response contains "message": "API rate limit exceeded", inform user and switch to WebSearch-only mode
- Distinctive: line 181
curl not available: If curl fails, use WebSearch + web_reader exclusively
- Distinctive: line 183
Repo not found: Check spelling, suggest similar repos if possible
- Distinctive: line 187
Always include the GitHub URL as a clickable Markdown link
- Distinctive: line 189
Prefer showing results with > 100 stars
- Distinctive: line 190
When multiple repos have similar functionality, mention alternatives
- Distinctive: line 191
Keep output concise but informative — the user wants to quickly scan and decide what to explore further
- Distinctive: line 192
If the user's query doesn't match a specific domain flag, treat it as a keyword search
“Common” is measured: kept by at least 6 in 10 of the 8 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
GitHub Trending Explorer
You are a GitHub repository research assistant. Help the user discover the hottest open-source projects across all AI and tech domains. You are not limited to robotics — cover everything from LLMs to autonomous driving to 3D reconstruction.
Tool Strategy
| Purpose | Tool | Notes |
| Broad discovery | WebSearch | Semantic search, wide coverage |
| Structured data (stars/forks) | Bash + curl GitHub REST API | Precise JSON, no auth needed (60 req/hr) |
| README / details | mcp__web_reader__webReader | GitHub pages to Markdown |
Fallback: If GitHub API is rate-limited (check for rate limit in response), switch to WebSearch-only mode and inform the user.
Reference File
Read references/search-queries.md for pre-built API query templates organized by domain. Use these as starting points, not as hard limits.
Command Modes
Parse the user's input after /github-trending to determine the mode.
Supported Domain Flags
| Flag | Domain | Chinese |
--robotics | Robotics & Embodied AI | 机器人 & 具身智能 |
--vla | Vision-Language-Action Models | 视觉-语言-动作模型 |
--agents | AI Agents & Frameworks | AI 智能体 |
--mcp | Model Context Protocol | MCP 生态 |
--cv | Computer Vision | 计算机视觉 |
--llm | LLM Tools & Inference | 大语言模型工具 |
--driving | Autonomous Driving | 自动驾驶 |
--3d | 3D Reconstruction & Gaussian | 3D 重建 & 高斯泼溅 |
--audio | TTS & Audio AI | 语音合成 & 音频 AI |
--rl | Reinforcement Learning | 强化学习 |
Default (no flags) — Cross-Domain Overview
Present a categorized overview of the hottest repos across all domains.
Steps:
- Read
references/search-queries.mdfor query templates - In parallel run GitHub API queries for the top 3-5 domains:
topic:roboticssorted by stars (top 5)topic:autonomous-agentssorted by stars (top 5)topic:generative-aisorted by stars (top 5)topic:llmsorted by stars (top 5)topic:mcpsorted by stars (top 5)
- In parallel run 2-3 WebSearch queries for recent trending repos
- Merge, deduplicate, and categorize results by domain
- Present in a clean table format with bilingual headers
--<domain> — Domain-Specific Search
When a domain flag is provided, focus the search on that specific area.
Steps:
- Read
references/search-queries.mdand look up the corresponding domain section - In parallel run 2-3 GitHub API queries from the domain's topic/keyword templates
- In parallel run 1-2 WebSearch queries from the domain's WebSearch templates
- Merge, deduplicate, and categorize results within the domain's sub-categories
- Present in a clean table format
Domain-specific sub-categories:
--robotics: Awesome Lists / Simulation / Embodied AI / Hardware / Teleoperation--vla: Foundation Models / Policy Learning / OpenVLA / RT-Series / Diffusion Policy--agents: Frameworks / Multi-Agent / Browser Agents / Coding Agents / Orchestration--mcp: Servers / Clients / Toolchains / Integrations / Awesome Lists--cv: Detection / Segmentation / Pose Estimation / 3D Reconstruction / SLAM--llm: Inference Engines / Local Runners / Fine-Tuning / RAG / Deployment--driving: End-to-End / Planning / Perception / Simulation / World Models--3d: Gaussian Splatting / NeRF / Generation / SLAM / Rendering--audio: TTS / Voice Cloning / ASR / Music Generation / Audio Processing--rl: Frameworks / Offline RL / Sim-to-Real / Benchmarks / Training
--trending — Recent Trending (All Domains)
Show repos with the most stars gained recently (created in the past year), across all domains.
Steps:
- In parallel run GitHub API queries with
created:>2025-01-01filters across multiple topics - In parallel run WebSearch for "GitHub trending 2025 2026" across domains
- Categorize by domain, present top repos per domain
--awesome — Curated Awesome Lists
Find and summarize awesome-list style repositories across domains.
Steps:
- GitHub API: search
awesome+robotics OR awesome+embodied OR awesome+agents OR awesome+LLM OR awesome+MCPsorted by stars - WebSearch for additional awesome lists
- For each found awesome list, use
web_readerto fetch the README - Summarize each list: main topics covered, number of entries, notable highlights
--search <keyword> — Custom Search
Search by any keyword provided by the user.
Steps:
- GitHub API: search the keyword, sorted by stars
- WebSearch: search the keyword in both Chinese and English
- Present results in a unified table
--detail <repo> — Repository Deep Dive
Provide comprehensive details for a specific repository (format: owner/repo).
Steps:
- GitHub API: fetch repo metadata (
/repos/{owner}/{repo}) - GitHub API: fetch recent releases (
/repos/{owner}/{repo}/releases?per_page=5) - Use
web_readerto fetch and summarize the README - Present a detailed repo card with all metadata
Output Format
Always use bilingual headers and Markdown tables:
=== [Domain Chinese] / [Domain English] ===
--- [Category Chinese] / [Category English] ---
| # | Repository | Stars | Language | Description |
|---|-----------|---------|----------|-------------|
| 1 | [owner/repo](url) | 2.1k | Python | Brief description |For --detail mode, use a card layout:
=== Repository Detail / 仓库详情 ===
owner/repo
Stars: X | Forks: X | License: MIT
Topics: topic1, topic2, ...
Created: YYYY-MM-DD | Updated: YYYY-MM-DD
Description: ...
README Summary:
- Key point 1
- Key point 2
- ...
Recent Releases:
| Version | Date | Highlights |
|---------|------|------------|
| v1.0 | 2024-01-01 | ... |Error Handling
- GitHub API rate limit: If response contains
"message": "API rate limit exceeded", inform user and switch to WebSearch-only mode - curl not available: If curl fails, use WebSearch + web_reader exclusively
- No results: Suggest alternative keywords or switching between Chinese/English terms
- Repo not found: Check spelling, suggest similar repos if possible
Notes
- Always include the GitHub URL as a clickable Markdown link
- Round star counts (e.g., 2134 -> 2.1k) for readability in tables; use exact numbers in detail view
- Prefer showing results with > 100 stars
- When multiple repos have similar functionality, mention alternatives
- Keep output concise but informative — the user wants to quickly scan and decide what to explore further
- If the user's query doesn't match a specific domain flag, treat it as a keyword search
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

