Data & AI skills

Constitutional AI and safety guardrail prompts for aligned LLM behavior

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Few-shot example generation and optimization for improved LLM performance

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Chain-of-thought and step-by-step reasoning prompts for complex problem solving

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Guardrails AI validation framework setup for LLM applications. Implement input/output validation, safety checks, and structured output enforcement.

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WASM-based instant code transforms for simple tasks, achieving 352x speedup over LLM inference with zero cost.

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System and API design guidance covering component boundaries, data flow, integration patterns, and scalability considerations.

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Search flights by origin, destination, and departure date using the bundled flights dataset. Use this skill when proposing flight options or checking whether a route/date combination exists.

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List cities for a given state using the bundled background data. Use this skill to validate state inputs or expand destination choices before flight/restaurant/attraction/driving/accommodation lookups.

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Generate compression reports for video processing. Use when you need to create structured JSON reports with duration statistics, compression ratios, and segment details after video processing.

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Retrieve attractions by city from the bundled dataset. Use this skill when surfacing points of interest or building sightseeing suggestions for a destination.

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ObsPy allows you to easily download earthquake data from various data centers/networks through its client API. This is an overview of available services and a demo of the client API for International Federation of Digital Seismograph Networks (FDSN). Use this if you need to download earthquake research data.

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Retrieve restaurants by city from the bundled dataset. Use this skill when recommending places to eat or validating dining options for a destination.

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Recover missing spreadsheet values from row and column totals, percentage shares, year-over-year changes, CAGR relationships, and cross-sheet constraints.

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Lookup accommodations by city from the bundled dataset. Use this skill when you need to recommend places to stay in a given city or filter lodging options before building an itinerary.

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Calculate per-second RMS energy from audio files. Use when you need to analyze audio volume patterns, prepare data for silence/pause detection, or create an energy profile for audio analysis tasks.

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World-class data science skill for statistical modeling, experimentation, causal inference, and advanced analytics. Expertise in Python (NumPy, Pandas, Scikit-learn), R, SQL, statistical methods, A/B testing, time series, and business intelligence. Includes experiment design, feature engineering, model evaluation, and stakeholder communication. Use when designing experiments, building predictive models, performing causal analysis, or driving data-driven decisions.

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This skill should be considered when you need to answer reflow machine maintenance questions or provide detailed guidance based on thermocouple data, MES data or defect data and reflow technical handbooks. This skill covers how to obtain important concepts, calculations, definitions, thresholds, and others from the handbook and how to do cross validations between handbook and datasets.

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Replay an LLM inference request trace (Mooncake / vLLM / SGLang hash_ids format) against a block-level KV prefix cache and compute hit statistics. Use when given a request trace plus cache configuration and asked for hit rate, hit tokens, or final cache contents. Covers the longest-contiguous-prefix semantics that distinguishes KV prefix caching from full-prompt prompt caching, the policy-specific residency and eviction rules (LRU, LFU, S3FIFO), and the partial-last-block accounting rule.

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Perform various data analysis on SEC 13-F and obtain some insights of fund activities such as number of holdings, AUM, and change of holdings between two quarters.

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Optimize Python code for reduced memory usage and improved memory efficiency. Use when asked to reduce memory footprint, fix memory leaks, optimize data structures for memory, handle large datasets efficiently, or diagnose memory issues. Covers object sizing, generator patterns, efficient data structures, and memory profiling strategies.

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Define custom distance/similarity metrics for clustering and ML algorithms. Use when working with DBSCAN, sklearn, or scipy distance functions with application-specific metrics.

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A toolkit for fuzzy string matching and data reconciliation. Useful for matching entity names (companies, people) across different datasets where spelling variations, typos, or formatting differences exist.

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Read and process GLM output files. Use when you need to extract temperature data from NetCDF output, convert depth coordinates, or calculate RMSE against observations.

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Detect flood events by comparing water levels to thresholds. Use when determining if flooding occurred, counting flood days, aggregating instantaneous data to daily values, or classifying flood severity.

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