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Agent Skills in category: Uncategorized

72295 skills match this category. Browse curated collections and explore related Agent Skills.

web-design-guidelines

Review UI code for Web Interface Guidelines compliance. Use when asked to "review my UI", "check accessibility", "audit design", "review UX", or "check my site against best practices".

vercel
vercel
1

risk-assessment

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hikaruegashira
hikaruegashira
11

gap-analysis

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hikaruegashira
hikaruegashira
11

review-flow

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hikaruegashira
hikaruegashira
11

worktree

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hikaruegashira
hikaruegashira
11

incident-handling

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hikaruegashira
hikaruegashira
11

commit-push-pr-flow

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hikaruegashira
hikaruegashira
11

process-commit

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hikaruegashira
hikaruegashira
11

japanese-webdesign

Provides guidance for designing websites optimized for Japanese audiences, including cultural UX principles, information density patterns, bento layouts, trust signals, and localization best practices. Use when building e-commerce sites, landing pages, SaaS products, or any web application targeting Japanese users.

ronantakizawa
ronantakizawa
0

claude-domain-skills

非技術領域專業知識集合,包含商業、金融、創意、專業服務、生活、方法論等 18 個領域

miles990
miles990
101

clinical-trial-protocol-skill

Generate clinical trial protocols for medical devices or drugs. This skill should be used when users say "Create a clinical trial protocol", "Generate protocol for [device/drug]", "Help me design a clinical study", "Research similar trials for [intervention]", or when developing FDA submission documentation for investigational products.

anthropics
anthropics
28346

instrument-data-to-allotrope

Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when scientists need to standardize instrument data for LIMS systems, data lakes, or downstream analysis. Supports auto-detection of instrument types. Outputs include full ASM JSON, flattened CSV for easy import, and exportable Python code for data engineers. Common triggers include converting instrument files, standardizing lab data, preparing data for upload to LIMS/ELN systems, or generating parser code for production pipelines.

anthropics
anthropics
28346

nextflow-development

Run nf-core bioinformatics pipelines (rnaseq, sarek, atacseq) on sequencing data. Use when analyzing RNA-seq, WGS/WES, or ATAC-seq data—either local FASTQs or public datasets from GEO/SRA. Triggers on nf-core, Nextflow, FASTQ analysis, variant calling, gene expression, differential expression, GEO reanalysis, GSE/GSM/SRR accessions, or samplesheet creation.

anthropics
anthropics
28346

scientific-problem-selection

This skill should be used when scientists need help with research problem selection, project ideation, troubleshooting stuck projects, or strategic scientific decisions. Use this skill when users ask to pitch a new research idea, work through a project problem, evaluate project risks, plan research strategy, navigate decision trees, or get help choosing what scientific problem to work on. Typical requests include "I have an idea for a project", "I'm stuck on my research", "help me evaluate this project", "what should I work on", or "I need strategic advice about my research".

anthropics
anthropics
28346

scvi-tools

Deep learning for single-cell analysis using scvi-tools. This skill should be used when users need (1) data integration and batch correction with scVI/scANVI, (2) ATAC-seq analysis with PeakVI, (3) CITE-seq multi-modal analysis with totalVI, (4) multiome RNA+ATAC analysis with MultiVI, (5) spatial transcriptomics deconvolution with DestVI, (6) label transfer and reference mapping with scANVI/scArches, (7) RNA velocity with veloVI, or (8) any deep learning-based single-cell method. Triggers include mentions of scVI, scANVI, totalVI, PeakVI, MultiVI, DestVI, veloVI, sysVI, scArches, variational autoencoder, VAE, batch correction, data integration, multi-modal, CITE-seq, multiome, reference mapping, latent space.

anthropics
anthropics
28346

single-cell-rna-qc

Performs quality control on single-cell RNA-seq data (.h5ad or .h5 files) using scverse best practices with MAD-based filtering and comprehensive visualizations. Use when users request QC analysis, filtering low-quality cells, assessing data quality, or following scverse/scanpy best practices for single-cell analysis.

anthropics
anthropics
28346

spice-accelerators

Choose and configure the right acceleration engine — Arrow, DuckDB, SQLite, Cayenne, PostgreSQL, or Turso. Use this skill whenever the user needs to pick an accelerator engine, compare engines (e.g. "should I use DuckDB or Cayenne?"), configure engine-specific parameters (duckdb_file, sqlite_file), tune memory vs file mode, or understand engine capabilities and limitations. This skill is the engine selection and tuning guide. For the broader acceleration feature (refresh modes, retention, snapshots, indexes), see spice-acceleration.

spiceai
spiceai
2

spice-data-connector

Configure individual data source connectors in Spice — PostgreSQL, MySQL, S3, Databricks, Snowflake, DuckDB, GitHub, Kafka, and 25+ more. Use this skill whenever the user wants to add a dataset, connect to a specific database or data source, load data from S3 or files, configure connector-specific parameters, understand file formats (Parquet, CSV, PDF, DOCX), or set up hive partitioning. This skill is the reference for the `from:` and `params:` fields in dataset configuration. For cross-source federation, views, and catalogs, see spice-connect-data.

spiceai
spiceai
2

spice-acceleration

Accelerate data locally for sub-second query performance — the feature and its configuration. Use this skill whenever the user asks about data acceleration concepts, enabling acceleration on a dataset, choosing refresh modes (full, append, changes, caching), configuring retention policies, setting up snapshots for cold-start, adding indexes and constraints, or understanding the difference between federated and accelerated queries. This skill covers the "what and why" of acceleration. For choosing which acceleration engine to use (Arrow vs DuckDB vs SQLite vs Cayenne), see spice-accelerators.

spiceai
spiceai
2

spice-ai

Add AI and LLM capabilities to Spice — tools, NSQL (text-to-SQL), memory, model routing/workers, and evals. Use this skill whenever the user wants to enable LLM tools (SQL, search, memory, MCP, web search), set up text-to-SQL via /v1/nsql, add persistent conversational memory, configure model routing with workers (load balancing, fallback, weighted distribution), set up evals, or use the OpenAI-compatible chat API. This skill covers AI features and orchestration. For configuring individual model providers (OpenAI, Anthropic, etc.), see spice-models.

spiceai
spiceai
2

spice-caching

Configure Spice.ai in-memory result caching for SQL queries, search results, and embeddings. Use this skill whenever the user asks about caching configuration, tuning cache TTL or max size, choosing eviction policies (LRU vs TinyLFU), enabling stale-while-revalidate, setting up cache-control headers, using custom cache keys (Spice-Cache-Key), monitoring cache metrics, choosing between plan vs SQL cache key types, or enabling zstd compression for cached results. Also use when the user asks why they're getting MISS/STALE responses or wants to optimize cache hit rates.

spiceai
spiceai
2

spice-cloud-management

Manage Spice.ai Cloud resources via the Management API — apps, deployments, secrets, API keys, and org members. Use this skill whenever the user wants to create or manage a Spice.ai Cloud app, trigger a deployment, manage cloud secrets or API keys, list regions or runtime versions, add/remove org members, or automate any Spice.ai Cloud operation. Also use when the user mentions "spice.ai cloud", "deploy to spice", "cloud API", or wants to use the Spice.ai hosted platform. For infrastructure-as-code with Terraform, see spice-terraform.

spiceai
spiceai
2

spice-connect-data

Connect Spice to data sources and query across them with federated SQL — including datasets, catalogs, views, and writes. Use this skill whenever the user wants to set up federated queries across multiple sources, create views, configure catalogs (Unity Catalog, Databricks, Iceberg), write data with INSERT INTO, or understand how Spice's query federation works. This skill focuses on the federation layer — cross-source joins, views, catalogs, and data writes. For configuring individual data source connectors (PostgreSQL params, S3 file formats, etc.), see spice-data-connector.

spiceai
spiceai
2

spice-models

Configure AI/LLM model providers and connections in Spice — OpenAI, Anthropic, Azure, Google, xAI, Bedrock, Perplexity, Databricks, HuggingFace, and local GGUF models. Use this skill whenever the user wants to add a model, configure a specific LLM provider, set up an OpenAI-compatible endpoint (e.g. Groq, Ollama), serve a local model, configure system prompts, set parameter overrides (temperature, response format), or understand which providers are available. This skill is the model connector reference. For AI features like tools, memory, workers, and NSQL, see spice-ai.

spiceai
spiceai
2

spice-search

Search data using vector similarity, full-text keywords, or hybrid methods with Reciprocal Rank Fusion (RRF). Use this skill whenever the user wants to set up semantic search, full-text search, or hybrid search in Spice — including configuring embedding models and providers, enabling full_text_search on columns, writing vector_search/text_search/rrf SQL queries, using the /v1/search HTTP API, configuring vector engines (S3 Vectors), tuning RRF parameters (rank_weight, recency_decay), or setting up chunking for long documents. Also use when the user asks about search relevance, BM25 scoring, or embedding configuration.

spiceai
spiceai
2

spice-secrets

Configure secret stores in Spice — environment variables, Kubernetes, AWS Secrets Manager, and OS keyring. Use this skill whenever the user needs to manage credentials, API keys, passwords, or tokens in Spice, reference secrets in spicepod.yaml params with ${ store:KEY } syntax, set up .env files, configure secret store precedence, or understand how the `secrets:` section works. Also use when the user asks how to pass database passwords or API keys securely to Spice datasets or models.

spiceai
spiceai
2

spice-setup

Get started with Spice.ai — install the runtime, initialize a project, run the runtime, and use the CLI. Use this skill whenever the user mentions installing Spice, setting up a new Spice project, running `spice run`, looking up CLI commands or API endpoints, deployment models, or getting started with Spice. Also use when the user asks "how do I install Spice", "how do I start Spice", "what CLI commands does Spice have", or any question about Spice runtime setup and configuration basics.

spiceai
spiceai
2

spice-terraform

Manage Spice.ai Cloud infrastructure as code with Terraform or OpenTofu using the spiceai/spiceai provider. Use this skill whenever the user wants to write Terraform/OpenTofu configs for Spice apps, deployments, secrets, or org members, import existing Spice.ai resources into Terraform state, set up OAuth authentication for the provider, or use Terraform data sources for regions and container images. Also use when the user mentions "terraform" and "spice" together, or wants IaC for their Spice.ai Cloud infrastructure. For direct API management without Terraform, see spice-cloud-management.

spiceai
spiceai
2

spice-text-to-sql

Generate accurate SQL for Spice.ai's Apache DataFusion engine (PostgreSQL dialect), and build text-to-SQL workflows. Use this skill whenever the user wants to write SQL queries against Spice datasets, convert natural language to SQL, debug SQL errors, understand Spice/DataFusion data types and type casting, use Spice-specific functions (ai, embed, vector_search, text_search, rrf, JSON operators), build a text-to-SQL pipeline with schema introspection, or construct prompts for LLM-based SQL generation. Also use when the user hits SQL errors like "table not found", "cannot cast", or asks about DataFusion SQL dialect differences from PostgreSQL/MySQL.

spiceai
spiceai
2

spicepod-config

Create and configure Spicepod manifests (spicepod.yaml) — the central configuration file for Spice applications. Use this skill whenever the user wants to create a new spicepod.yaml from scratch, understand the overall spicepod structure and available sections, configure runtime settings (ports, caching, telemetry/observability), set up a complete Spice application combining datasets + models + search, or understand deployment models and use cases. This is the "glue" skill that shows how all Spice components fit together in one manifest. For details on specific sections (datasets, models, search, etc.), see the dedicated skills.

spiceai
spiceai
2

ai-ml-development

AI and machine learning development with PyTorch, TensorFlow, and LLM integration. Use when building ML models, training pipelines, fine-tuning LLMs, or implementing AI features.

travisjneuman
travisjneuman
3210

android-development

Android development with Kotlin, Jetpack Compose, and modern Android architecture. Use when building Android apps, implementing Material Design, or following Android best practices.

travisjneuman
travisjneuman
3210

api-design

REST and GraphQL API design best practices including OpenAPI specs. Use when designing APIs, documenting endpoints, or reviewing API architecture.

travisjneuman
travisjneuman
3210

audio-production

Professional audio production for music, podcasts, and sound design. Use when working with audio recording, mixing, mastering, or sound design for any medium.

travisjneuman
travisjneuman
3210

auto-claude

Autonomous multi-agent coding with git worktree isolation, QA validation, and memory. Use for complex features requiring autonomous implementation.

travisjneuman
travisjneuman
3210

brand-identity

Brand strategy and identity design for businesses and products. Use when creating brand guidelines, developing visual identity systems, or defining brand positioning.

travisjneuman
travisjneuman
3210

business-strategy

Business strategy expertise for strategic planning, competitive analysis, market entry, M&A strategy, portfolio management, and strategic decision-making. Use when analyzing competitive positioning, planning growth strategies, or making strategic decisions.

travisjneuman
travisjneuman
3210

codebase-documenter

This skill should be used when writing documentation for codebases, including README files, architecture documentation, code comments, and API documentation. Use this skill when users request help documenting their code, creating getting-started guides, explaining project structure, or making codebases more accessible to new developers. The skill provides templates, best practices, and structured approaches for creating clear, beginner-friendly documentation.

travisjneuman
travisjneuman
3210

core-workflow

Detailed development workflow patterns, checklists, and standards. Auto-loads for complex tasks, planning, debugging, testing, or when explicit patterns are needed. Contains session protocols, git conventions, security checklists, testing strategy, and communication standards.

travisjneuman
travisjneuman
3210

data-science

Data science and analytics expertise for statistical analysis, machine learning pipelines, data governance, business intelligence, predictive modeling, and analytics strategy. Use when building ML models, analyzing data, creating dashboards, or designing data architectures.

travisjneuman
travisjneuman
3210

database-expert

Advanced database design and administration for PostgreSQL, MongoDB, and Redis. Use when designing schemas, optimizing queries, managing database performance, or implementing data patterns.

travisjneuman
travisjneuman
3210

debug-systematic

Systematic 4-phase debugging methodology for complex, intermittent, or mysterious issues. Use when investigating bugs, race conditions, or unexplained failures.

travisjneuman
travisjneuman
3210

devops-cloud

DevOps, cloud infrastructure, and platform engineering. Use when working with AWS, GCP, Azure, Kubernetes, Terraform, CI/CD pipelines, or infrastructure as code.

travisjneuman
travisjneuman
3210

document-skills

Professional document creation, editing, and analysis for Office formats (docx, pdf, pptx, xlsx). Use when working with Word documents, PDFs, PowerPoint presentations, or Excel spreadsheets.

travisjneuman
travisjneuman
3210

docx

Comprehensive document creation, editing, and analysis with support for tracked changes, comments, formatting preservation, and text extraction. When Claude needs to work with professional documents (.docx files) for: (1) Creating new documents, (2) Modifying or editing content, (3) Working with tracked changes, (4) Adding comments, or any other document tasks

travisjneuman
travisjneuman
3210

pdf

Comprehensive PDF manipulation toolkit for extracting text and tables, creating new PDFs, merging/splitting documents, and handling forms. When Claude needs to fill in a PDF form or programmatically process, generate, or analyze PDF documents at scale.

travisjneuman
travisjneuman
3210

pptx

Presentation creation, editing, and analysis. When Claude needs to work with presentations (.pptx files) for: (1) Creating new presentations, (2) Modifying or editing content, (3) Working with layouts, (4) Adding comments or speaker notes, or any other presentation tasks

travisjneuman
travisjneuman
3210

xlsx

Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas

travisjneuman
travisjneuman
3210

electron-desktop

Desktop application development with Electron for Windows, macOS, and Linux. Use when building cross-platform desktop apps, implementing native OS features, or packaging web apps for desktop.

travisjneuman
travisjneuman
3210

finance

Financial analysis expertise for financial modeling (DCF, LBO, M&A), valuation, financial statement analysis, capital allocation, treasury management, and corporate finance decisions. Use when building financial models, analyzing statements, or making investment decisions.

travisjneuman
travisjneuman
3210

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