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Found 154 Skills
Guide counterparty credit risk measurement and management for OTC and securities trading. Use when measuring current or potential future exposure to a counterparty, setting or reviewing counterparty credit limits, evaluating ISDA Master Agreement netting benefits, designing collateral management or CSA terms, assessing central clearing mandates under Dodd-Frank or EMIR, monitoring counterparty creditworthiness via CDS spreads or ratings, managing Herstatt or settlement risk in FX, quantifying wrong-way risk, or building real-time exposure dashboards. Also use for counterparty default scenarios, credit deterioration events, EAD and SA-CCR calculations, and CVA capital charges.
Run and interact with KarpathyTalk, an open markdown-based developer social network with GitHub auth, SQLite, and an LLM-friendly JSON/markdown API.
Use when writing, reviewing, or committing code to enforce Karpathy's 4 coding principles — surface assumptions before coding, keep it simple, make surgical changes, define verifiable goals. Triggers on "review my diff", "check complexity", "am I overcomplicating this", "karpathy check", "before I commit", or any code quality concern where the LLM might be overcoding.
Behavioral guidelines to reduce common LLM coding mistakes. Use when writing, reviewing, or refactoring code to avoid overcomplication, make surgical changes, surface assumptions, and define verifiable success criteria.
Research tool for visually exploring BLS Occupational Outlook Handbook data with an interactive treemap, LLM-powered scoring pipeline, and data scraping/parsing utilities.
Use when normal web_fetch cannot read a page, when a site blocks basic fetching, or when the user needs YouTube content in AI-ready form. Guides fallback use of Firecrawl for single-page web scraping and SerpApi for YouTube search/video metadata/transcripts only.
Write competitive research proposals for NSF, NIH, DOE, and DARPA. Agency-specific formatting, review criteria, budget preparation, broader impacts, significance statements, innovation narratives, and compliance with submission requirements.
Guidance for training FastText text classification models with constraints on model size and accuracy. This skill should be used when training FastText models, optimizing hyperparameters, or balancing trade-offs between model size and classification accuracy.
Use when "scikit-learn", "sklearn", "machine learning", "classification", "regression", "clustering", or asking about "train test split", "cross validation", "hyperparameter tuning", "ML pipeline", "random forest", "SVM", "preprocessing"
Эксперт AutoML. Используй для automated machine learning, hyperparameter tuning и model selection.
Guides structured 4-stage experiment execution with attempt budgets and gate conditions: Stage 1 initial implementation (reproduce baseline), Stage 2 hyperparameter tuning, Stage 3 proposed method validation, Stage 4 ablation study. Integrates with evo-memory (load prior strategies, trigger IVE/ESE) and experiment-craft (5-step diagnostic on failure). Use when: user has a planned experiment, needs to reproduce baselines, organize experiment workflow, or systematically validate a method. Do NOT use for debugging a specific experiment failure (use experiment-craft) or designing which experiments to run (use paper-planning).
Guidelines for building RoboCorp RPA automation with Python, emphasizing functional programming, Pydantic validation, and async operations.