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phanghonghaophanghonghao/THU-Awesome-Skills/skills/github-trending/SKILL.md

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.

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The file

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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
  1. Very specific:

    Fallback: If GitHub API is rate-limited (check for rate limit in response), switch to WebSearch-only mode and inform the user.

    line 39
  2. Very specific:

    Read references/search-queries.md for pre-built API query templates organized by domain.

    line 43
  3. Very specific:

    Read references/search-queries.md for query templates

    line 69
  4. Distinctive:

    In parallel: run GitHub API queries for the top 3-5 domains:

    line 70
  5. Distinctive:

    In parallel: run 2-3 WebSearch queries for recent trending repos

    line 76
  6. Distinctive:

    When a domain flag is provided, focus the search on that specific area.

    line 82
  7. Very specific:

    Read references/search-queries.md and look up the corresponding domain section

    line 85
  8. Distinctive:

    In parallel: run 2-3 GitHub API queries from the domain's topic/keyword templates

    line 86
  9. Distinctive:

    In parallel: run 1-2 WebSearch queries from the domain's WebSearch templates

    line 87
  10. Very specific:

    In parallel: run GitHub API queries with created:>2025-01-01 filters across multiple topics

    line 108
  11. Distinctive:

    In parallel: run WebSearch for "GitHub trending 2025 2026" across domains

    line 109
  12. Distinctive:

    Search by any keyword provided by the user.

    line 124
  13. Very specific:

    Use web_reader to fetch and summarize the README

    line 138
  14. Distinctive:

    Always use bilingual headers and Markdown tables:

    line 143
  15. Very specific:

    GitHub API rate limit: If response contains "message": "API rate limit exceeded", inform user and switch to WebSearch-only mode

    line 180
  16. Distinctive:

    curl not available: If curl fails, use WebSearch + web_reader exclusively

    line 181
  17. Distinctive:

    Repo not found: Check spelling, suggest similar repos if possible

    line 183
  18. Distinctive:

    Always include the GitHub URL as a clickable Markdown link

    line 187
  19. Distinctive:

    Prefer showing results with > 100 stars

    line 189
  20. Distinctive:

    When multiple repos have similar functionality, mention alternatives

    line 190
  21. Distinctive:

    Keep output concise but informative — the user wants to quickly scan and decide what to explore further

    line 191
  22. Distinctive:

    If the user's query doesn't match a specific domain flag, treat it as a keyword search

    line 192

“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.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

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

PurposeToolNotes
Broad discoveryWebSearchSemantic search, wide coverage
Structured data (stars/forks)Bash + curl GitHub REST APIPrecise JSON, no auth needed (60 req/hr)
README / detailsmcp__web_reader__webReaderGitHub 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

FlagDomainChinese
--roboticsRobotics & Embodied AI机器人 & 具身智能
--vlaVision-Language-Action Models视觉-语言-动作模型
--agentsAI Agents & FrameworksAI 智能体
--mcpModel Context ProtocolMCP 生态
--cvComputer Vision计算机视觉
--llmLLM Tools & Inference大语言模型工具
--drivingAutonomous Driving自动驾驶
--3d3D Reconstruction & Gaussian3D 重建 & 高斯泼溅
--audioTTS & Audio AI语音合成 & 音频 AI
--rlReinforcement Learning强化学习

Default (no flags) — Cross-Domain Overview

Present a categorized overview of the hottest repos across all domains.

Steps:

  1. Read references/search-queries.md for query templates
  2. In parallel run GitHub API queries for the top 3-5 domains:
    • topic:robotics sorted by stars (top 5)
    • topic:autonomous-agents sorted by stars (top 5)
    • topic:generative-ai sorted by stars (top 5)
    • topic:llm sorted by stars (top 5)
    • topic:mcp sorted by stars (top 5)
  3. In parallel run 2-3 WebSearch queries for recent trending repos
  4. Merge, deduplicate, and categorize results by domain
  5. 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:

  1. Read references/search-queries.md and look up the corresponding domain section
  2. In parallel run 2-3 GitHub API queries from the domain's topic/keyword templates
  3. In parallel run 1-2 WebSearch queries from the domain's WebSearch templates
  4. Merge, deduplicate, and categorize results within the domain's sub-categories
  5. 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:

  1. In parallel run GitHub API queries with created:>2025-01-01 filters across multiple topics
  2. In parallel run WebSearch for "GitHub trending 2025 2026" across domains
  3. Categorize by domain, present top repos per domain

--awesome — Curated Awesome Lists

Find and summarize awesome-list style repositories across domains.

Steps:

  1. GitHub API: search awesome+robotics OR awesome+embodied OR awesome+agents OR awesome+LLM OR awesome+MCP sorted by stars
  2. WebSearch for additional awesome lists
  3. For each found awesome list, use web_reader to fetch the README
  4. Summarize each list: main topics covered, number of entries, notable highlights

--search <keyword> — Custom Search

Search by any keyword provided by the user.

Steps:

  1. GitHub API: search the keyword, sorted by stars
  2. WebSearch: search the keyword in both Chinese and English
  3. Present results in a unified table

--detail <repo> — Repository Deep Dive

Provide comprehensive details for a specific repository (format: owner/repo).

Steps:

  1. GitHub API: fetch repo metadata (/repos/{owner}/{repo})
  2. GitHub API: fetch recent releases (/repos/{owner}/{repo}/releases?per_page=5)
  3. Use web_reader to fetch and summarize the README
  4. 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

  1. GitHub API rate limit: If response contains "message": "API rate limit exceeded", inform user and switch to WebSearch-only mode
  2. curl not available: If curl fails, use WebSearch + web_reader exclusively
  3. No results: Suggest alternative keywords or switching between Chinese/English terms
  4. 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

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