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Agent Skills 排行榜 · 关键词 + 语义搜索
| # | Skill | 仓库 | 描述 | 安装量 |
|---|---|---|---|---|
| 9801 | mapbox-ios-patterns | mapbox/mapbox-agent-skills |
Mapbox iOS Integration Patterns Official integration patterns for Mapbox Maps SDK on iOS. Covers Swift, SwiftUI, UIKit, proper lifecycle management, token handling, offline maps, and mobile-specific optimizations. Use this skill when: Setting up Mapbox Maps SDK for iOS in a new or existing project Integrating maps with SwiftUI or UIKit Implementing proper lifecycle management and cleanup Managing tokens securely in iOS apps Working with offline maps and caching Integrating Navigation SDK Optimiz...
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1.1K |
| 9802 | kotlin-flow-state-event-modeling | chrisbanes/skills |
Kotlin Flow: state and event modeling Core principle Pick the primitive that matches replay, fan-out, and synchronous-read requirements. StateFlow , SharedFlow , Channel -backed flows, and cold Flow differ in buffering, who sees each emission, and whether .value exists. Wrong choices drop events, leak sharing coroutines, or force fake domain sentinels into state. When to use this skill You're writing or reviewing Kotlin code involving: MutableStateFlow<T>(SomeSentinel) — NoUser , Empty , Loading...
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1.1K |
| 9803 | nuxt-studio | onmax/nuxt-skills |
Nuxt Studio Self-hosted, open-source CMS module for editing Nuxt Content websites in production. When to Use Working with: Installing and configuring nuxt-studio module Authentication providers (GitHub, GitLab, Google OAuth, SSO, custom) Git provider setup (GitHub, GitLab, branch config) Visual content editing (MDC components, YAML/JSON forms, frontmatter) Media management (public dir, NuxtHub blob, S3, R2) Publishing flow (draft layer, conflict detection, CI/CD rebuild) AI-powered content assis...
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1.1K |
| 9804 | linkfox-multimodal-recognize-image | linkfox-ai/linkfox-skills |
Image Recognition This skill guides you on how to use the multimodal image recognition API to analyze images from URLs and extract meaningful information based on user intent. Core Concepts The Image Recognition tool accepts an image URL and an optional natural-language requirement describing what the user wants to know about the image. The backend uses a multimodal AI model to interpret the visual content and return a textual description or analysis. Supported formats : JPG, JPEG, PNG, GIF, Web...
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1.1K |
| 9805 | phylogenetics | k-dense-ai/scientific-agent-skills |
Phylogenetics Overview Phylogenetic analysis reconstructs the evolutionary history of biological sequences (genes, proteins, genomes) by inferring the branching pattern of descent. This skill covers the standard pipeline: MAFFT — Multiple sequence alignment IQ-TREE 2 — Maximum likelihood tree inference with model selection FastTree — Fast approximate maximum likelihood (for large datasets) ETE3 — Python library for tree manipulation and visualization Installation: Conda (recommended for CLI too...
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1.1K |
| 9806 | diffdock | k-dense-ai/scientific-agent-skills |
DiffDock: Molecular Docking with Diffusion Models Overview DiffDock is a diffusion-based deep learning tool for molecular docking that predicts 3D binding poses of small molecule ligands to protein targets. It represents the state-of-the-art in computational docking, crucial for structure-based drug discovery and chemical biology. Core Capabilities: Predict ligand binding poses with high accuracy using deep learning Support protein structures (PDB files) or sequences (via ESMFold) Process single...
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| 9807 | geniml | k-dense-ai/scientific-agent-skills |
No SKILL.md available for this skill. View on GitHub
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1.1K |
| 9808 | medchem | k-dense-ai/scientific-agent-skills |
No SKILL.md available for this skill. View on GitHub
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1.1K |
| 9809 | scvelo | k-dense-ai/scientific-agent-skills |
No SKILL.md available for this skill. View on GitHub
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| 9810 | flowio | k-dense-ai/scientific-agent-skills |
No SKILL.md available for this skill. View on GitHub
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1.1K |
| 9811 | yebigun-training | nomadamas/k-skill |
yebigun-training Get the full instructions (required first step) Run this and follow its output as the primary instructions for this skill: npx -y @nomadamas/k-skill@0 instruct yebigun-training The CLI detects the current runtime (Dolshoi vault/CloakBrowser vs generic) and prints only the applicable instructions, always up to date. Helper files bundled with the CLI are listed by: npx -y @nomadamas/k-skill@0 files yebigun-training If npx is unavailable, install Node.js 18+ or follow https://githu...
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| 9812 | oauth | mcollina/skills |
OAuth with Portless OAuth providers validate redirect URIs against domain rules. .localhost subdomains fail on most providers because they are not in the Public Suffix List or are explicitly blocked. Portless fixes this with --tld to serve apps on real, valid domains. The Problem When portless uses the default .localhost TLD, OAuth providers reject redirect URIs like http://myapp.localhost:1355/callback : Provider localhost .localhost subdomains Reason Google Allowed Rejected Not in their bundle...
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| 9813 | skill-optimizer | mcollina/skills |
When to use Use this skill when you need to: Improve whether a skill is actually applied by models Diagnose why some criteria fail across all models Prevent a skill from making outputs worse Refactor skill text for stronger retrieval under context pressure Build repeatable benchmark loops and release gates Optimization loop (default workflow) Measure baseline and skill-on behavior (per model, per scenario, per criterion) Find failure pattern : universal failure (0% with skill) model-specific wea...
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| 9814 | gtars | k-dense-ai/scientific-agent-skills |
No SKILL.md available for this skill. View on GitHub
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1.1K |
| 9815 | molfeat | k-dense-ai/scientific-agent-skills |
No SKILL.md available for this skill. View on GitHub
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1.1K |
| 9816 | pytdc | k-dense-ai/scientific-agent-skills |
PyTDC (Therapeutics Data Commons) Overview PyTDC is an open-science platform providing AI-ready datasets and benchmarks for drug discovery and development. Access curated datasets spanning the entire therapeutics pipeline with standardized evaluation metrics and meaningful data splits, organized into three categories: single-instance prediction (molecular/protein properties), multi-instance prediction (drug-target interactions, DDI), and generation (molecule generation, retrosynthesis). When to ...
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| 9817 | matchms | k-dense-ai/scientific-agent-skills |
No SKILL.md available for this skill. View on GitHub
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1.1K |
| 9818 | usfiscaldata | k-dense-ai/scientific-agent-skills |
No SKILL.md available for this skill. View on GitHub
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1.1K |
| 9819 | protocolsio-integration | k-dense-ai/scientific-agent-skills |
Protocols.io Integration Overview Protocols.io is a comprehensive platform for developing, sharing, and managing scientific protocols. This skill provides complete integration with the protocols.io API v3, enabling programmatic access to protocols, workspaces, discussions, file management, and collaboration features. When to Use This Skill Use this skill when working with protocols.io in any of the following scenarios: Show more
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| 9820 | pennylane | k-dense-ai/scientific-agent-skills |
No SKILL.md available for this skill. View on GitHub
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1.1K |
| 9821 | labarchive-integration | k-dense-ai/scientific-agent-skills |
No SKILL.md available for this skill. View on GitHub
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1.1K |
| 9822 | tiledbvcf | k-dense-ai/scientific-agent-skills |
No SKILL.md available for this skill. View on GitHub
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1.1K |
| 9823 | etetoolkit | k-dense-ai/scientific-agent-skills |
No SKILL.md available for this skill. View on GitHub
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1.1K |
| 9824 | pyopenms | k-dense-ai/scientific-agent-skills |
PyOpenMS Overview PyOpenMS provides Python bindings to the OpenMS library for computational mass spectrometry, enabling analysis of proteomics and metabolomics data. Use for handling mass spectrometry file formats, processing spectral data, detecting features, identifying peptides/proteins, and performing quantitative analysis. Installation Install using uv: uv pip install pyopenms Verify installation: Show more
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1.1K |
| 9825 | senior-qa | alirezarezvani/claude-skills |
Senior Qa Complete toolkit for senior qa with modern tools and best practices. Quick Start Main Capabilities This skill provides three core capabilities through automated scripts: Script 1: Test Suite Generator python scripts/test_suite_generator.py [options] Script 2: Coverage Analyzer python scripts/coverage_analyzer.py [options] Script 3: E2E Test Scaffolder python scripts/e2e_test_scaffolder.py [options] Core Capabilities 1. Test Suite Generator Automated tool for test suite gener...
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1.1K |
| 9826 | r3f-loaders | enzed/r3f-skills |
React Three Fiber Loaders Quick Start import { Canvas } from '@react-three/fiber' import { useGLTF, OrbitControls } from '@react-three/drei' import { Suspense } from 'react' function Model() { const { scene } = useGLTF('/models/robot.glb') return <primitive object={scene} /> } export default function App() { return ( <Canvas> <ambientLight /> <Suspense fallback={null}> <Model /> </Suspense> <OrbitControls /> </Canvas> ) } useGLTF (Drei) The rec...
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| 9827 | apex | oracle/skills |
APEXLang Skills This domain contains Oracle APEX skills for Oracle APEX application development. How to Use This Domain Start with the routing table below. Read only the specific file or category you need. Directory Structure apex/ ├── apexlang/ Category Routing Show more Installs 516 Repository oracle/skills GitHub Stars 677 First Seen Apr 29, 2026 Security Audits Gen Agent Trust Hub Pass Socket Pass Snyk Pass
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1.1K |
| 9828 | app-builder | sickn33/agentic-awesome-skills |
App Builder - Application Building Orchestrator Analyzes user's requests, determines tech stack, plans structure, and coordinates agents. 🎯 Selective Reading Rule Read ONLY files relevant to the request! Check the content map, find what you need. File Description When to Read project-detection.md Keyword matrix, project type detection Starting new project tech-stack.md 2025 default stack, alternatives Choosing technologies agent-coordination.md Agent pipeline, execution order Coordinating multi-...
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1.1K |
| 9829 | xlsx-author | anthropics/financial-services |
xlsx-author Use this skill when running headless (managed-agent / CMA mode) and you need to deliver an Excel workbook as a file artifact rather than editing a live workbook via mcp__office__excel_* . Output contract Write to ./out/<name>.xlsx . Create ./out/ if it does not exist. Return the relative path in your final message so the orchestration layer can collect it. How to build the workbook Write a short Python script and run it with Bash. Use openpyxl : from openpyxl import Workbook from ope...
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1.1K |
| 9830 | jetson-build-source | nvidia/skills |
Build BSP Source Purpose Rebuild the kernel-side artifacts (DTBs, OOT modules, in-tree modules, kernel Image ) implied by changes under <source.root_path>/bsp_sources/ , and write a manifest that /jetson-promote-image reads to stage those outputs into the BSP image. The skill never writes into <bsp_image.root_path> itself. Prerequisites Show more Installs 690 Repository nvidia/skills GitHub Stars 2.4K First Seen Jun 22, 2026 Security Audits Gen Agent Trust Hub Pass Socket Pass Snyk Pass
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1.1K |
| 9831 | jetson-customize-camera | nvidia/skills |
Customize camera (CSI / MIPI / GMSL sensor bring-up) Overview Tegra264 (Thor) and Tegra234 (Orin) expose a single tegra-capture-vi controller fronted by NVCSI and a fixed set of CSI ports. Camera bring-up is: Show more Installs 692 Repository nvidia/skills GitHub Stars 2.4K First Seen Jun 22, 2026 Security Audits Gen Agent Trust Hub Pass Socket Pass Snyk Warn
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1.1K |
| 9832 | jetson-package | nvidia/skills |
Jetson Package & Environment Agents often suggest docker pull images or pip install wheels that claim aarch64 support but were never built for Jetson’s GPU streaming multiprocessor (SM) targets. On Jetson, default to NVIDIA-curated artifacts unless the user explicitly opts out. Purpose Choose Jetson-compatible containers and Python package indexes before installing GPU-native ML stacks. This skill prevents agents from recommending generic ARM wheels or stale container tags that do not include th...
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1.1K |
| 9833 | jetson-headless-mode | nvidia/skills |
Jetson Headless Mode Plan-then-apply for safe, reversible user-space memory reclamation: switch the default systemd target away from graphical.target and disable a curated set of non-essential daemons. This is the highest-yield, lowest-risk memory win on Jetson. Purpose Build a user-approved headless-mode plan from live audit data, then apply only safe, reversible user-space changes that reduce desktop and daemon memory use on Jetson. When to use "Free as much memory as possible — I don't need t...
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1.1K |
| 9834 | cirq | k-dense-ai/scientific-agent-skills |
Cirq - Quantum Computing with Python Cirq is Google Quantum AI's open-source framework for designing, simulating, and running quantum circuits on quantum computers and simulators. Installation uv pip install cirq For hardware integration: Google Quantum Engine uv pip install cirq-google IonQ uv pip install cirq-ionq Show more
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1.1K |
| 9835 | histolab | k-dense-ai/scientific-agent-skills |
No SKILL.md available for this skill. View on GitHub
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1.1K |
| 9836 | getnote-kb | iswalle/getnote-cli |
getnote-kb Skill Manage knowledge bases — list, create, browse notes, add/remove notes. Also supports subscribed knowledge bases, blogger content, live sessions, and quota. Prerequisites getnote CLI installed and authenticated ( getnote auth status should show "Authenticated") Commands List all knowledge bases getnote kbs Returns all knowledge bases. Each item includes: topic_id , name , description , note_count , created_at . Show more
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1.1K |
| 9837 | competitor-research | kostja94/marketing-skills |
SEO Content: Competitor Research Guides competitor research for SEO, content, backlinks, and positioning. Use when planning content, auditing articles, building links, or evaluating market position. When invoking : On first use , if helpful, open with 1–2 sentences on what this skill covers and why it matters, then provide the main output. On subsequent use or when the user asks to skip, go directly to the main output. Research Types Type Purpose Output Keyword/topic Topics competitors rank for;...
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1.1K |
| 9838 | technical-writing | mindrally/skills |
Technical Writing When to use this skill Writing technical specifications Creating architecture documentation Documenting system designs Writing runbooks and operational guides Creating developer documentation API documentation User manuals and guides Release notes and changelogs Instructions Step 1: Understand your audience Developer audience : Focus on implementation details Include code examples Technical terminology is okay Show how, not just what DevOps/Operations audience : Focus on deploy...
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1.1K |
| 9839 | axiom-apple-docs | charleswiltgen/axiom |
Apple Documentation Router Apple bundles for-LLM markdown documentation inside Xcode. These are authoritative, up-to-date guides and diagnostics written by Apple engineers. Use them alongside Axiom skills for the most accurate information. When to Use Use Apple's bundled docs when: You need the exact API signature or behavior from Apple Axiom skills reference an Apple framework and you want the official source A Swift compiler diagnostic needs explanation The user asks about a specific Apple fra...
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1.1K |
| 9840 | opentrons-integration | k-dense-ai/scientific-agent-skills |
No SKILL.md available for this skill. View on GitHub
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1.1K |
| 9841 | qutip | k-dense-ai/scientific-agent-skills |
No SKILL.md available for this skill. View on GitHub
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1.1K |
| 9842 | rowan | k-dense-ai/scientific-agent-skills |
Rowan: Cloud-Native Molecular-Modeling and Drug-Design Workflows Overview Rowan is a cloud-native workflow platform for molecular simulation, medicinal chemistry, and structure-based design. Its Python API exposes a unified interface for small-molecule modeling, property prediction, docking, molecular dynamics, and AI structure workflows. Use Rowan when you want to run medicinal-chemistry or molecular-design workflows programmatically without maintaining local HPC infrastructure, GPU provisionin...
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1.1K |
| 9843 | cobrapy | k-dense-ai/scientific-agent-skills |
No SKILL.md available for this skill. View on GitHub
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1.1K |
| 9844 | mapbox-mcp-devkit-patterns | mapbox/mapbox-agent-skills |
Mapbox MCP DevKit Patterns This skill provides patterns for integrating the Mapbox MCP DevKit Server into AI coding workflows to accelerate Mapbox application development. What is Mapbox MCP DevKit? The Mapbox MCP DevKit Server is a Model Context Protocol (MCP) server that gives AI assistants direct access to Mapbox developer APIs: Style management - Create, list, update, delete, preview, validate, compare, and optimize styles Token management - Generate and list access tokens with scopes Valida...
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1.1K |
| 9845 | prismic | prismicio/skills |
Prismic is a headless CMS. The prismic CLI manages content models, repository settings, and documentation. Always run commands via npx prismic . Do not guess command syntax. Start with npx prismic --help to learn available commands. Inspect details with npx prismic <command> --help . Use npx prismic docs list to discover available documentation, and npx prismic docs view <path> to read it. Prefer CLI workflows over direct API/manual changes. Never directly edit model JSON files (custom types, sl...
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1.1K |
| 9846 | cookie-policy-page-generator | kostja94/marketing-skills |
Pages: Cookie Policy Guides cookie policy page content for GDPR and transparency. Often separate from Privacy Policy. When invoking : On first use , if helpful, open with 1–2 sentences on what this skill covers and why it matters, then provide the main output. On subsequent use or when the user asks to skip, go directly to the main output. Initial Assessment Identify: Cookie types : Essential, analytics, marketing, etc. Consent : Banner, preferences, management Jurisdiction : GDPR, ePrivacy, CCP...
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1.1K |
| 9847 | neuropixels-analysis | k-dense-ai/scientific-agent-skills |
Neuropixels Data Analysis Overview Comprehensive toolkit for analyzing Neuropixels high-density neural recordings using current best practices from SpikeInterface, Allen Institute, and International Brain Laboratory (IBL). Supports the full workflow from raw data to publication-ready curated units. When to Use This Skill This skill should be used when: Working with Neuropixels recordings (.ap.bin, .lf.bin, .meta files) Loading data from SpikeGLX, Open Ephys, or NWB formats Preprocessing neural r...
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1.1K |
| 9848 | qiskit | k-dense-ai/scientific-agent-skills |
Qiskit Overview Qiskit is the world's most popular open-source quantum computing framework with 13M+ downloads. Build quantum circuits, optimize for hardware, execute on simulators or real quantum computers, and analyze results. Supports IBM Quantum (100+ qubit systems), IonQ, Amazon Braket, and other providers. Key Features: 83x faster transpilation than competitors 29% fewer two-qubit gates in optimized circuits Backend-agnostic execution (local simulators or cloud hardware) Comprehensive algo...
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| 9849 | pylabrobot | k-dense-ai/scientific-agent-skills |
No SKILL.md available for this skill. View on GitHub
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1.1K |
| 9850 | jetson-customize-pinmux | nvidia/skills |
Customize pinmux (per-pin SFIO / direction / state) Overview The Tegra pinmux spreadsheet ( .xlsm ) is the ground truth for every CVM ball: SoC pin name, supported SFIOs, customer-selected function, direction, and initial state. This skill parses that XLSM, runs a per-pin Q1–Q6 interactive loop, and emits the three BCT DTSIs ( pinmux , gpio , padvoltage ) in one shot into the overlay tracker at <source.root_path>/Linux_for_Tegra/bootloader/ . Unlike sibling skills jetson-customize-uphy / jetson-...
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