Results for “april-dunford”

Build stateful, coordinated applications on Cloudflare's edge using Durable Objects with SQLite storage, RPC methods, alarms, and WebSockets.

Get best practices for Entity Framework Core, covering data context design, entity design, performance, migrations, querying, change tracking, security, and testing.

Provides expertise for analyzing DWARF debug files and understanding the DWARF debug format (v3-v5). Triggers when understanding DWARF information, interacting with DWARF files, answering DWARF-related questions, or working with code that parses DWARF data.

Optimize Entity Framework Core queries by fixing N+1 problems, choosing correct tracking modes, using compiled queries, and avoiding common performance traps.

Expert in NFT development - minting infrastructure, metadata standards, marketplaces, royalties, and collection management across EVM and SolanaUse when "nft, erc721, erc1155, mint, collection, metadata, opensea, metaplex, pfp, generative art, nft, erc721, erc1155, metaplex, opensea, royalties, metadata, ipfs" mentioned.

Foundational SPARQL patterns covering RDF querying, triple patterns, graph patterns, and semantic web fundamentals. Use when querying RDF data or working with knowledge graphs. This is the entry point for SPARQL development.

Domain-Driven Design patterns. Bounded contexts, aggregates, entities, value objects, domain events, repositories, and application services. Strategic and tactical DDD for complex business domains. USE WHEN: user mentions "DDD", "Domain-Driven Design", "bounded context", "aggregate", "value object", "domain event", "ubiquitous language", "aggregate root", "domain service" DO NOT USE FOR: database schema design - use database skills; CQRS/Event Sourcing specifics - use `event-sourcing-cqrs`

Query Google Data Commons for public statistical data aggregated from global sources, resolving geographic entities and pulling time-series statistics. Use when working with demographic data, economic indicators, health statistics, or environmental data — population counts, GDP figures, unemployment rates, disease prevalence — or when resolving places to DCIDs and exploring relationships between statistical entities. Part of the AlterLab Academic Skills suite.

Expert-level PostgreSQL database administration, advanced queries, performance tuning, and production operations

Use this skill whenever the user wants to conduct an event study, create event study plots, test for parallel trends, implement difference-in-differences designs, or work with any panel data estimation that involves pre/post treatment comparisons. Trigger on phrases like "event study", "parallel trends", "pre-trends", "dynamic treatment effects", "leads and lags", "TWFE", "two-way fixed effects", "staggered adoption", "staggered treatment", "difference-in-differences", "DiD", "Sun and Abraham", "Callaway and Sant'Anna", "de Chaisemartin", "Borusyak", "did_multiplegt", "fixest", "did2s", "bacon decomposition", or any reference to plotting coefficients around a treatment event. Also trigger when the user uploads panel data and wants to estimate treatment effects with variation in treatment timing. All code is in R.

PyTorch, TensorFlow, neural networks, CNNs, transformers, and deep learning for production

Walk a business/UAT approver through a plain-language demo of a verified feature and capture business acceptance signoff.

Build a USASpending relationship snapshot for the incumbent and buying agency on a pursuit row. Use when user needs award flows and rel counts before battlecard or teaming work — deterministic from DuckDB bulk.

Get best practices for Entity Framework Core

Fan one question out across every connected source and return a single ranked, deduplicated, attributed result set.

EL2N: Deep Learning on a Data Diet

Analyzes a completed phase diff for high-confidence behavior-preserving simplifications and applies only explicitly approved proposals, reducing duplication, dead code, needless complexity, or avoidable inefficiency.