Skills for your AI
Helps QA testers plan, set up, execute, analyze, and report on performance tests, from test plans and scripts to data, troubleshooting, and visualizations. Use when the user needs a performance test plan, environment setup, test data, load or stress scripts, r
/cs:post-mortem <decision> — Honest retrospective on an executed decision, scored against original assumptions and dissent. Closes the strategic sprint loop. Use when a decision hits its 90-day review checkpoint or its kill criteria trigger — e.g. scoring last
Design presentation visuals and slide layouts. Create visual concepts, suggest graphics, and provide design specifications for impactful PowerPoint slides.
Turns PR campaign data into findings, performance reports, competitor and trend analyses, ROI breakdowns, and optimization recommendations. Use when the user needs to analyze social media metrics, media coverage, web traffic, or campaign costs, measure KPIs, m
Turns maintenance records, sensor feeds, and equipment data into failure predictions, optimized schedules, alerts, reports, and improvement plans. Use when a service manager needs maintenance pattern analysis, predictive scheduling, alert setup, downtime repor
Analyzes business processes, maps workflows, benchmarks performance, tracks KPIs, designs automation, and plans improvements from owner-provided data. Use when users want to find bottlenecks or inefficiencies, compare metrics to benchmarks, run root cause anal
Analyzes quality control data, runs statistical tests, generates QC reports and visualizations, performs SPC, root cause and compliance analysis, and applies advanced quality methodologies like FMEA, DOE, Six Sigma and MSA. Use when the user provides QC data,
Maps, analyzes, and redesigns business processes for management consultants, covering process mapping, data analysis, benchmarking, change management, KPIs, technology assessment, cost-benefit and risk, training, and standardization. Use when a consultant need
Use when defining product KPIs, building metric dashboards, running cohort or retention analysis, or interpreting feature adoption trends across product stages.
Aggregates scattered product feedback into compiled lists, sentiment breakdowns, categories, feature and bug inventories, trends, competitor comparisons, priorities, segments, response drafts, reports, dashboards, and survey questions. Use when the user wants
Analyzes product metrics from raw data to insights, covering collection, exploration, visualization, cohorts, funnels, A/B tests, forecasting, reporting, engagement, satisfaction, adoption, churn, and pricing. Use when a product manager needs metrics analyzed,
Collects, analyzes and reports on production data covering output, quality, efficiency, cost, downtime, resources, compliance and forecasting, and generates reports for distribution on approval. Use when the user asks to summarize production data, analyze tren
Analyzes project data to produce summaries, risk assessments, resource plans, forecasts, quality and lessons-learned reports, and dashboard specs. Use when the user asks for project timelines, risk mitigation, workload or resource optimization, outcome forecas
Guides biochemists through retrieving, visualizing, converting, comparing, annotating and sharing 3D protein structures, including custom tools, 3D printing, molecular dynamics and machine learning. Use when the user asks about protein structure data, molecula
Runs the full PyDESeq2 differential expression pipeline on bulk RNA-seq counts and metadata, including validation, Wald tests, FDR correction, LFC shrinkage, and significant gene reporting. Use when the user supplies bulk RNA-seq counts and metadata and asks f
Processes and analyzes LC-MS/MS proteomics and metabolomics data with PyOpenMS, covering file I/O, signal processing, feature detection, peptide and protein identification, metabolomics workflows, and export to pandas or NumPy. Use when the user asks to load m
Structures PyTorch code into LightningModules, configures Trainers, LightningDataModules, callbacks, logging, and distributed strategies. Use when converting PyTorch models to Lightning, setting up multi-GPU/TPU training, building data pipelines, adding checkp
Designs and executes QA strategies across the development lifecycle—strategy, audits, release readiness, test plans, metrics, automation, manual testing, defects, API, performance and security testing. Use when planning QA, auditing quality, assessing release
Guides medical device companies through ISO 13485:2016 QMS implementation, documentation, audits, CAPA, risk management, supplier quality, and certification maintenance. Use when the user needs gap analysis, document control templates, management review prep,
Turns raw quality data into structured analysis, reports, and improvement recommendations for QA managers. Use when organizing feedback, analyzing trends or defects, benchmarking, checking compliance, building reports, or evaluating test coverage, satisfaction
Analyzes quality metrics data into trend, benchmark, root cause, predictive, coverage, defect, and performance reports with prioritized improvement recommendations. Use when consolidating scattered quality data, tracking metrics against benchmarks, forecasting
Collects, cleans, analyzes, and visualizes research and development data from websites, databases, sensors, and text, including scraping, statistics, machine learning, dashboards, and data quality work. Use when an R&D engineer needs raw data turned into struc
Randomly selects raffle, giveaway, and contest winners from lists, spreadsheets, or Google Sheets with secure randomness, duplicate prevention, weighted odds, runner-ups, exports, and team assignment. Use when picking winners, splitting participants into teams
Turns real estate data into market, property, investment, and financial analyses and reports. Use when the broker needs market trends, a CMA, investment returns, sales forecasts, competitor positioning, lead or campaign analytics, survey design, financial repo
