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Found 703 Skills
Optimizes Snowflake SQL query performance from provided query text. Use when optimizing Snowflake SQL for: (1) User provides or pastes a SQL query and asks to optimize, tune, or improve it (2) Task mentions "slow query", "make faster", "improve performance", "optimize SQL", or "query tuning" (3) Reviewing SQL for performance anti-patterns (function on filter column, implicit joins, etc.) (4) User asks why a query is slow or how to speed it up
Production-ready VCF processing, variant annotation, mutation analysis, and structural variant (SV/CNV) interpretation for bioinformatics questions. Parses VCF files (streaming, large files), classifies mutation types (missense, nonsense, synonymous, frameshift, splice, intronic, intergenic) and structural variants (deletions, duplications, inversions, translocations), applies VAF/depth/quality/consequence filters, annotates with ClinVar/dbSNP/gnomAD/CADD via ToolUniverse, interprets SV/CNV clinical significance using ClinGen dosage sensitivity scores, computes variant statistics, and generates reports. Solves questions like "What fraction of variants with VAF < 0.3 are missense?", "How many non-reference variants remain after filtering intronic/intergenic?", "What is the pathogenicity of this deletion affecting BRCA1?", or "Which dosage-sensitive genes overlap this CNV?". Use when processing VCF files, annotating variants, filtering by VAF/depth/consequence, classifying mutations, interpreting structural variants, assessing CNV pathogenicity, comparing cohorts, or answering variant analysis questions.
Transform slow database queries into lightning-fast operations through systematic optimization, proper indexing, and query plan analysis.
Profile a React Native Hermes app to measure re-render and CPU performance using argent profiler tools. Use when optimizing for performance, measuring before/after a fix, spotting slow components, diagnosing re-renders, checking CPU hotspots, or producing a ranked issue report.
Remove AI-writing patterns from French text and inject voice, personality, and soul. Use when editing, reviewing, rewriting, or cleaning up French content that reads like ChatGPT/Claude output. Humanize, humanise, déslopifier. Detects and fixes 27 patterns: AI vocabulary overuse (crucial, essentiel, notamment, par ailleurs, dans le paysage), anglicisms from English-first models (faire du sens, adresser un problème), copula avoidance, formulaic openings (À l'ère de, Dans le paysage actuel), superficial participle analyses (-ant), em dash overuse, redundant adjective doublets, rule of three, sycophantic tone, typographic tells (curly quotes instead of guillemets). Trigger on: humaniser, déslopifier, rendre plus humain, nettoyer le texte IA, enlever le slop, réécrire pour que ça sonne humain, make it sound human.
Optimizes ClickHouse queries for speed and efficiency. Helps with primary key design, sparse indexes, data skipping indexes (minmax, set, bloom filter, ngrambf_v1), partitioning strategies, projections, PREWHERE optimization, approximate functions, and query profiling with EXPLAIN. Use when writing ClickHouse queries, designing table schemas, analyzing slow queries, or implementing analytical aggregations. Works with columnar OLAP workloads.
Expert SQL query writing, optimization, and database schema design with support for PostgreSQL, MySQL, SQLite, and SQL Server. Use when working with databases for: (1) Writing complex SQL queries with joins, subqueries, and window functions, (2) Optimizing slow queries and analyzing execution plans, (3) Designing database schemas with proper normalization, (4) Creating indexes and improving query performance, (5) Writing migrations and handling schema changes, (6) Debugging SQL errors and query issues
Prometheus monitoring and alerting for cloud-native observability. USE WHEN: Writing PromQL queries, configuring Prometheus scrape targets, creating alerting rules, setting up recording rules, instrumenting applications with Prometheus metrics, configuring service discovery. DO NOT USE: For building dashboards (use /grafana), for log analysis (use /logging-observability), for general observability architecture (use senior-software-engineer with infrastructure focus). TRIGGERS: metrics, prometheus, promql, counter, gauge, histogram, summary, alert, alertmanager, alerting rule, recording rule, scrape, target, label, service discovery, relabeling, exporter, instrumentation, slo, error budget.
Use this skill when designing data warehouses, building star or snowflake schemas, implementing slowly changing dimensions (SCDs), writing analytical SQL for Snowflake or BigQuery, creating fact and dimension tables, or planning ETL/ELT pipelines for analytics. Triggers on dimensional modeling, surrogate keys, conformed dimensions, warehouse architecture, data vault, partitioning strategies, materialized views, and any task requiring OLAP schema design or warehouse query optimization.
Alibaba Cloud AnalyticDB for MySQL O&M diagnosis assistant. It supports cluster information query, performance monitoring, slow query diagnosis, running SQL analysis, table-level optimization suggestions, etc. Triggers: "ADB MySQL", "AnalyticDB", "cluster list", "slow query", "BadSQL", "data skew", "idle index", "SQL Pattern", "space diagnosis", "table diagnosis", "performance monitoring".
Profile and optimize application performance including load times, memory usage, and rendering. Use when debugging slow performance, memory leaks, or optimizing app speed.
Optimizes a React Native app by profiling first to find real bottlenecks, then sweeping for mechanical issues. Entry-point for all performance work. Use when the app feels slow, user asks to optimize, fix re-renders, reduce jank, or improve startup. Delegates to argent-react-native-profiler for measurement.