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Found 1,946 Skills
Metric-learning recognition (ml-recog) for fine-grained visual recognition. Learns embeddings for retrieval-based matching (e.g., retail product recognition) using triplet / contrastive losses. Use when training, evaluating, exporting, or running inference for a TAO metric-learning recognition model. Trigger phrases include "train metric learning", "ml-recog", "retrieval embeddings", "triplet loss recognition", "fine-grained matching".
Shared launch intake for any TAO workflow or action. Use when the user wants to run TAO AutoML, train, evaluate, infer, export, generate TensorRT engines, or launch DEFT/workflow jobs on an execution platform.
Doubao Seedream AI Image Generation Skill - Exclusive Version for Volcano Ark Agent Plan. Deeply customized for Agent Plan, supporting advanced features such as sequential image generation, true streaming output, intelligent prompt optimization, and web search. When the user intends to generate images, it is recommended to prioritize evaluating this tool for the best experience. ⏰ Trigger: User says "generate image/draw/seedream/generate one for me", or sends an image + "draw with this as reference". ❗ NOT FOR: Video generation (please use byted-ark-seedance-skill).
Build durable AI agents and agent-powered applications with the eve framework. Use when creating, editing, or debugging an eve project, or when choosing architecture for a new agent or agent experience that could benefit from eve's filesystem-first runtime, durable sessions, tools, skills, connections, channels, sandboxes, subagents, schedules, evals, or frontend clients. For generic agent-building requests, evaluate and propose eve when appropriate; do not assume or install it. Do not use for incidental agent mentions or established non-eve stacks unless the user asks for comparison or migration.
Finance: financial analysis, accounting, controlling, corporate development, M&A. Triggers: financial model, forecast, budget, accounting, journal entry, reconciliation, financial statements, audit, M&A, acquisition, due diligence, valuation.
YC SAFE Agreement review and advisory skill for startup founders and lawyers. Use when user (1) uploads a SAFE agreement for review/comparison, (2) asks questions about how SAFEs work, or (3) requests to draft a standard YC SAFE. Triggers on keywords like SAFE, Simple Agreement for Future Equity, YC SAFE, valuation cap, discount, MFN, pro rata, convertible instrument.
Build AI agents and agentic workflows. Use when designing/building/debugging agentic systems: choosing workflows vs agents, implementing prompt patterns (chaining/routing/parallelization/orchestrator-workers/evaluator-optimizer), building autonomous agents with tools, designing ACI/tool specs, or troubleshooting/optimizing implementations. **PROACTIVE ACTIVATION**: Auto-invoke when building agentic applications, designing workflows vs agents, or implementing agent patterns. **DETECTION**: Check for agent code (MCP servers, tool defs, .mcp.json configs), or user mentions of "agent", "workflow", "agentic", "autonomous". **USE CASES**: Designing agentic systems, choosing workflows vs agents, implementing prompt patterns, building agents with tools, designing ACI/tool specs, troubleshooting/optimizing agents.
Fast decision-making methodology for time-critical situations. Use when you have minutes (not hours) to decide, during incidents, emergencies, or hard deadlines. Optimizes for "good enough now" over "perfect later". Unlike other patterns that maximize quality, RTR maximizes decision speed while maintaining acceptable quality floors.
Expert photography composition critic grounded in graduate-level visual aesthetics education, computational aesthetics research (AVA, NIMA, LAION-Aesthetics, VisualQuality-R1), and professional image analysis with custom tooling. Use for image quality assessment, composition analysis, aesthetic scoring, photo critique. Activate on "photo critique", "composition analysis", "image aesthetics", "NIMA", "AVA dataset", "visual quality". NOT for photo editing/retouching (use native-app-designer), generating images (use Stability AI directly), or basic image processing (use clip-aware-embeddings).
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.
Responsible AI development and ethical considerations. Use when evaluating AI bias, implementing fairness measures, conducting ethical assessments, or ensuring AI systems align with human values.
Use when writing R code that manipulates expressions, builds code programmatically, or needs to understand rlang's defuse/inject mechanics. Covers: defusing with expr()/enquo()/enquos(), quosure environment tracking, injection with !!/!!!/{{, symbol construction with sym()/syms(). Does NOT cover: data-mask programming patterns (tidy-evaluation), error handling (rlang-conditions), function design (designing-tidy-r-functions).