文件操作
文件系统与批量文件任务
sync-model-catalog
Agenta-AI
Regenerate and refresh the curated agent model catalog (the label/description/pricing/ratings behind the agent model picker). Use when the pinned @earendil-works/pi-ai version bumps, when a Claude Code build changes its accepted alias set, or before a release when the curated Claude/Pi facts (lineup, pricing, ratings) need refreshing from current public sources. Owns the data files under sdks/python/agenta/sdk/agents/data/; never edits capabilities.py logic.
write-issue
Agenta-AI
Write and file Linear issues (bugs and feature requests) the Agenta way. Use when the user asks to create, file, or draft a Linear or GitHub issue, write a bug report or feature request, or turn a problem into a tracked issue. Covers the title format, reproduction-first structure, when to use a todo list, and the team/project/label/priority/state conventions, plus filing it through the Linear MCP so the linked GitHub issue is auto-created and the PR links back.
processing-markdown
harehare
Processes Markdown files using mq, a jq-like query language for Markdown. Use when the user mentions Markdown processing, content extraction, document transformation, or mq queries.
copilot-otel-metrics
microsoft
'Set up GitHub Copilot OpenTelemetry capture: configure the VS Code export settings, generate a local Grafana stack and dashboard, or generate the Azure collector, infrastructure, and dashboard for an organization.'
python-foundational
microsoft
"Foundational Python best practices, idioms, and code quality fundamentals"
aura-asset-images
MengTo
"Use when you need high-quality stock-style images from Aura Assets (aura.build/assets) similar to Unsplash for design mockups and marketing: backgrounds, abstract wallpapers, architecture, portraits, and headshots. Includes a workflow for searching by tag on aura.build/assets and returns 5 real image URLs per category plus practical guidance for using different resolutions and aspect ratios."
deploy-to-temps
gotempsh
Deploy applications to the Temps platform with automatic framework detection, Dockerfile generation, and container orchestration. Supports Next.js, Vite, React, Node.js, Python, Go, Rust, Java, and C# applications. Use when the user wants to: (1) Deploy their app to Temps, (2) Set up CI/CD with Temps, (3) Configure deployment settings, (4) Create a Dockerfile for Temps, (5) Deploy a containerized application, (6) Set up automatic deployments from Git. Triggers: "deploy to temps", "temps deployment", "push to temps", "containerize for temps", "temps ci/cd".
marketing-demand-acquisition
alirezarezvani
Multi-channel demand generation, paid media optimization, SEO strategy, and partnership programs for Series A+ startups
ads-microsoft
AgriciDaniel
Microsoft/Bing Ads deep analysis covering search, Performance Max, Audience Network, and Copilot integration. Evaluates 20 checks with focus on Google import validation, unique Microsoft features, and cost advantage assessment. Use when user says "Microsoft Ads", "Bing Ads", "Bing PPC", "Copilot ads", or "Microsoft campaign".
ads-google
AgriciDaniel
Google Ads deep analysis covering Search, Performance Max, Display, YouTube, and Demand Gen campaigns. Evaluates 74 checks across conversion tracking, wasted spend, account structure, keywords, ads, and settings. Use when user says "Google Ads", "Google PPC", "search ads", "PMax", "Performance Max", or "Google campaign".
ads-competitor
AgriciDaniel
Competitor ad intelligence analysis across Google, Meta, LinkedIn, TikTok, and Microsoft. Analyzes competitor ad copy, creative strategy, keyword targeting, estimated spend, and identifies competitive gaps and opportunities. Use when user says "competitor ads", "ad spy", "competitive analysis", "competitor PPC", or "ad intelligence".
mq
kylesnowschwartz
This skill SHOULD be used when the user asks to "get code blocks from README", "extract links from markdown", "find all headers in this doc", "pull the table from documentation", "what code examples are in this file", or when needing specific elements (code, links, headers, tables) from large Markdown files without loading the entire file.
tavily-crawl
tavily-ai
Crawl websites and extract content from multiple pages via the Tavily CLI. Use this skill when the user wants to crawl a site, download documentation, extract an entire docs section, bulk-extract pages, save a site as local markdown files, or says "crawl", "get all the pages", "download the docs", "extract everything under /docs", "bulk extract", or needs content from many pages on the same domain. Supports depth/breadth control, path filtering, semantic instructions, and saving each page as a local markdown file.
tavily-best-practices
tavily-ai
"Build production-ready Tavily integrations with best practices baked in. Reference documentation for developers using coding assistants (Claude Code, Cursor, etc.) to implement web search, content extraction, crawling, and research in agentic workflows, RAG systems, or autonomous agents."
search
tavily-ai
"Search the web using Tavily's LLM-optimized search API. Returns relevant results with content snippets, scores, and metadata. Use when you need to find web content on any topic without writing code."
tavily-search
tavily-ai
Search the web with LLM-optimized results via the Tavily CLI. Use this skill when the user wants to search the web, find articles, look up information, get recent news, discover sources, or says "search for", "find me", "look up", "what's the latest on", "find articles about", or needs current information from the internet. Returns relevant results with content snippets, relevance scores, and metadata — optimized for LLM consumption. Supports domain filtering, time ranges, and multiple search depths.
axiom-file-protection-ref
CharlesWiltgen
Use when asking about 'FileProtectionType', 'file encryption iOS', 'NSFileProtection', 'data protection', 'secure file storage', 'encrypt files at rest', 'complete protection', 'file security' - comprehensive reference for iOS file encryption and data protection APIs
axiom-build-debugging
CharlesWiltgen
Use when encountering dependency conflicts, CocoaPods/SPM resolution failures, "Multiple commands produce" errors, or framework version mismatches - systematic dependency and build configuration debugging for iOS projects. Includes pressure scenario guidance for resisting quick fixes under time constraints
dnanexus-integration
K-Dense-AI
DNAnexus cloud genomics platform. Build apps/applets, manage data (upload/download), dxpy Python SDK, run workflows, FASTQ/BAM/VCF, for genomics pipeline development and execution.
GeoMaster
K-Dense-AI
A set of ready to use Agent Skills for research, science, engineering, analysis, finance and writing.
gget
K-Dense-AI
"Fast CLI/Python queries to 20+ bioinformatics databases. Use for quick lookups: gene info, BLAST searches, AlphaFold structures, enrichment analysis. Best for interactive exploration, simple queries. For batch processing or advanced BLAST use biopython; for multi-database Python workflows use bioservices."
adaptyv
K-Dense-AI
"How to use the Adaptyv Bio Foundry API and Python SDK for protein experiment design, submission, and results retrieval. Use this skill whenever the user mentions Adaptyv, Foundry API, protein binding assays, protein screening experiments, BLI/SPR assays, thermostability assays, or wants to submit protein sequences for experimental characterization. Also trigger when code imports adaptyv, adaptyv_sdk, or FoundryClient, or references foundry-api-public.adaptyvbio.com."
geopandas
K-Dense-AI
Python library for working with geospatial vector data including shapefiles, GeoJSON, and GeoPackage files. Use when working with geographic data for spatial analysis, geometric operations, coordinate transformations, spatial joins, overlay operations, choropleth mapping, or any task involving reading/writing/analyzing vector geographic data. Supports PostGIS databases, interactive maps, and integration with matplotlib/folium/cartopy. Use for tasks like buffer analysis, spatial joins between datasets, dissolving boundaries, clipping data, calculating areas/distances, reprojecting coordinate systems, creating maps, or converting between spatial file formats.
geniml
K-Dense-AI
This skill should be used when working with genomic interval data (BED files) for machine learning tasks. Use for training region embeddings (Region2Vec, BEDspace), single-cell ATAC-seq analysis (scEmbed), building consensus peaks (universes), or any ML-based analysis of genomic regions. Applies to BED file collections, scATAC-seq data, chromatin accessibility datasets, and region-based genomic feature learning.