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Found 380 Skills
Use when working with Tigris file storage - uploading, downloading, deleting, listing files, presigned URLs, client uploads, or setting up Tigris CLI and SDK. Covers Next.js, Remix, Express, Rails, and Laravel. For Python/Django, see the tigris-python-sdk skill.
Fast DataFrame library (Apache Arrow). Select, filter, group_by, joins, lazy evaluation, CSV/Parquet I/O, expression API, for high-performance data analysis workflows.
When user asks about "confidence", "accuracy", "how sure", "uncertain", "reliable", "track record", or when Claude should express calibrated uncertainty. Enables domain-aware self-assessment.
Code of Conduct for De-Buzzwording Chinese Output. Automatically activated when the model responds in Chinese to ensure concise, direct, and natural output, avoiding AI-style expressions such as consulting buzzwords, internet slang, false sense of urgency, and emotional manipulation. Trigger words: 'Speak human language', 'Cut the fluff', 'Remove buzzwords', 'Get rid of AI tone', 'Don’t be so GPT-like', 'Speak normally'. Even without trigger words, the rules of this Skill shall take effect whenever the model generates Chinese responses. It also applies to scenarios where users say 'This text is too GPT-like', 'Help me rewrite it in human language', 'The output is too cheesy', 'Stop beating around the bush', etc.
Query Reactome REST API for pathway analysis, enrichment, gene-pathway mapping, disease pathways, molecular interactions, expression analysis, for systems biology studies.
Build applications using the x402 protocol — Coinbase's open standard for HTTP-native stablecoin payments using the HTTP 402 status code. Use this skill when: - Creating APIs that require USDC payments per request (seller/server side) - Building clients or AI agents that pay for x402-protected resources (buyer/client side) - Implementing MCP servers with paid tools for Claude Desktop - Adding payment middleware to Express, Hono, or Next.js applications - Working with Base (EVM) or Solana (SVM) payment flows - Building machine-to-machine or agent-to-agent payment systems - Integrating micropayments, pay-per-use billing, or paid API access Triggers: x402, HTTP 402, payment required, USDC payments, micropayments, pay-per-use API, agentic payments, stablecoin payments, paid API endpoint, paywall middleware
Japanese version of the PUA Universal Motivation Engine. It compels exhaustive problem-solving using corporate PUA rhetoric and structured debugging methodology in Japanese. MUST trigger under the following conditions: (1) Any task has failed 2+ times, or you're stuck in a loop of tweaking the same approach; (2) You're about to say 'I cannot', suggest manual handling to the user, or blame the environment without verification; (3) You find yourself being passive — not searching, not reading source code, not verifying, just waiting for instructions; (4) The user expresses frustration in any form: 'try harder', 'stop giving up', 'figure it out', 'why isn't this working', 'again???', 'もっと頑張れ', 'なんでまた失敗したの', 'もう一回やって', 'なんとかしろ', or any similar sentiment regardless of phrasing. It should also trigger when facing complex multi-step debugging, environment issues, configuration problems, or deployment failures where early surrender is tempting. Applies to ALL task types: code, configuration, research, writing, deployment, infrastructure, API integration. DO NOT trigger on first-attempt failures or when a known fix is already executing successfully.
Use these skills to set up and optimize production-ready vector workloads by simply expressing your intent and performance requirements.
Using records, pattern matching, primary constructors, collection expressions. C# 12-15 by TFM.
Two-step image grounding pipeline: extracts referring expressions from (image, caption) pairs and grounds them to pixel-space bounding boxes via a VLM. Use when the user wants to ground captions to bboxes, generate phrase-grounded annotations, auto-label images for grounding, or run the image_grounding pipeline. Triggers include 'image grounding', 'phrase grounding', 'ground captions', 'auto-label image grounding', 'image_grounding'.
Use switch expressions and pattern matching where appropriate
Comprehensive patient stratification for precision medicine by integrating genomic, clinical, and therapeutic data. Given a disease/condition, genomic data (germline variants, somatic mutations, expression), and optional clinical parameters, performs multi-phase analysis across 9 phases covering disease disambiguation, genetic risk assessment, disease-specific molecular stratification, pharmacogenomic profiling, comorbidity/DDI risk, pathway analysis, clinical evidence and guideline mapping, clinical trial matching, and integrated outcome prediction. Generates a quantitative Precision Medicine Risk Score (0-100) with risk tier assignment (Low/Intermediate/High/Very High), treatment algorithm (1st/2nd/3rd line), pharmacogenomic guidance, clinical trial matches, and monitoring plan. Use when clinicians ask about patient risk stratification, treatment selection, prognosis prediction, or personalized therapeutic strategy across cancer, metabolic, cardiovascular, neurological, or rare diseases.