Results for “pr”

Use for writing, reviewing, debugging, testing, or diagnosing Bayesian regression and hierarchical models built with Bambi formulas, Model, Family/Likelihood/Link, Prior, fit, prior predictive, and predict. Trigger on common versus group-specific terms, categorical coding, family/link choice, automatic prior scaling, missing rows, PyMC backend settings, and InferenceData predictions. Do not use for hand-built PyMC graphs, NumPyro programs, ArviZ-only analysis of existing draws, frequentist statsmodels formulas, or generic pandas work.

Documents MariaDB-specific GRANT behavior, including privilege scope levels, implicit account creation, MariaDB-only privileges, roles, proxy grants, resource limits, and TLS options, to help write accurate GRANT statements.

Use when implementing SQL functionality with production-grade patterns and safeguards.

Hardens and secures process historian servers (OSIsoft PI, Honeywell PHD, GE Proficy, AVEVA Historian) in OT environments, covering network placement, access control, data replication through DMZ, SQL injection prevention, and data integrity protection.

Translates Oracle PL/SQL stored procedures to PostgreSQL PL/pgSQL, preserving method signatures and type-anchored parameters while applying Oracle-compatible sorting and leveraging orafce.

Extracts Amazon product details, buy box owner, other sellers' prices, and seller ratings for a given ASIN using the BrowserAct API.

Explains MariaDB server-side prepared statements (PREPARE, EXECUTE, DEALLOCATE, EXECUTE IMMEDIATE), including syntax, allowed statements, placeholders, session scope, and restrictions. Use when writing or reviewing dynamic SQL for MariaDB.

Transform data into compelling narratives using visualization, context, and persuasive structure. Use when presenting analytics to stakeholders, creating data reports, or building executive presentations.

Build, fit, validate, and compare Bayesian models using PyMC's modern API, including hierarchical models, MCMC sampling, variational inference, posterior predictive checks, and model comparison.

Orchestrates Python data pipelines with Prefect flows, tasks, retries, caching, parallel execution, and deployments to work pools.

Parse Windows Prefetch files using the windowsprefetch Python library to reconstruct application execution history, detect renamed or masquerading binaries, and identify suspicious program execution patterns.

Points developers to the canonical WordPress Presence API sources and explains its ephemeral-table-plus-TTL architectural pattern, so they avoid inventing postmeta-based presence implementations.

Pre-landing PR review. Analyzes diff against the base branch for SQL safety, LLM trust boundary violations, conditional side effects, and other structural issues. Use when asked to "review this PR", "code review", "pre-landing review", or "check my diff". Proactively suggest when the user is about to merge or land code changes. (gstack)

Analyze PyTorch profiler and vLLM trace files with Perfetto SQL evidence. Use when working with torch profiler traces, merged_trace files, vLLM profiling logs, Perfetto trace analysis, GPU kernel hotspots, synchronization waits, rank imbalance, prefill/decode bottlenecks, or optimization reports.

RICE feature prioritization with scoring and capacity planning. Usage: /rice prioritize <features.csv> [options]

Apache Airflow, dbt, Prefect, Dagster, and modern data orchestration for production data pipelines

Monitors a watchlist of Kalshi prediction markets for price moves, volume spikes, resolution proximity, and kill-criterion triggers, with cross-venue arbitrage detection against paired Polymarket markets adjusted for fees and slippage.

Create Earth2Studio prognostic model wrappers that time-step weather forecasts forward, with triple-inheritance classes, tests, and documentation.

Audits nonprofit operations across impact measurement, fundraising, grant management, and donor retention, producing a prioritized fix plan.

Search the Federal Register for rules, proposed rules, notices, and presidential documents, and monitor regulatory activity.

RICE feature prioritization with scoring and capacity planning. Usage: /rice prioritize <features.csv> [options]

Apply GDPR-compliant engineering practices across your codebase, covering API design, data models, authentication, logging, retention, and cloud infrastructure.

Provides a pre-built Salesforce data model template for Quotes and Orders, including Mermaid diagrams, relationship tables, and key concepts.

Discover, classify, and protect sensitive data across cloud storage, databases, and data pipelines using Amazon Macie, Azure Information Protection, and Google Cloud DLP API.

Predicts gene and transcript structure from a DNA sequence using the hosted Genomic Intelligence API, producing a report and JSON output.

Execute Python code in a safe sandboxed environment with 100+ pre-installed libraries for data processing, web scraping, image manipulation, video creation, 3D model processing, PDF generation, API calls, and automation.

Returns structured prediction-market data for Polymarket, Kalshi, Limitless, Opinion, Predict.Fun, dFlow, and UMA oracle via a local API, covering markets, cross-venue search, leaderboards, smart money, wallet analytics, identity clustering, and resolution status.

Define, track, and interpret product metrics across discovery, growth, and mature product stages using frameworks like AARRR, North Star, and HEART.

Guides monitoring and observability setup for Qdrant vector search deployments, including Prometheus scraping, health checks, and metric-based debugging of production issues.

Generates OMG-compliant BPMN 2.0 XML and SVG diagrams from natural language process descriptions, with validation, automatic layout, and optional process optimization advisories.

Provides real-time access to SEC EDGAR filings, BLS employment statistics, and USDA crop prices through three MCP tools.

"Set up Promptbook \u2014 connect your account to start tracking builds.\n\ Use when the user wants to enable session analytics on promptbook.gg.\nTrigger with\ \ \"/setup\" or \"set up promptbook\".\n"

Diagnose and fix retention problems using the Fogg Behavior Model (B=MAP), covering motivation, ability, prompts, and tiny habits.

Provides code examples and best practices for using Pinecone, a managed vector database for production RAG, recommendation, and semantic search applications.

Provides statistical process control guidance including control chart selection, capability indices, and out-of-control rules for quality management.

Provides a pre-built Salesforce Service Cloud data model template with Mermaid diagrams, ASCII fallback, and relationship summaries for documentation and analysis.