Results for “parma”

Prisma ORM expert for schema design, migrations, query optimization, relations modeling, and database operations. Use PROACTIVELY for Prisma schema issues, migration problems, query performance, relation design, or database connection issues.

Prisma ORM expert for schema design, migrations, query optimization, relations modeling, and database operations. Use PROACTIVELY for Prisma schema issues, migration problems, query performance, relation design, or database connection issues.

Provides production patterns and non-obvious traps for Prisma ORM in TypeScript backends, covering schema design, query optimization, transactions, pagination, and common pitfalls.

Expert in Prisma - the TypeScript ORM for type-safe database access. Covers schema design, migrations, Prisma Client queries, relations, edge deployment, and performance optimization. Essential for building reliable database layers in TypeScript applications. Use when "prisma, orm, database typescript, prisma client, prisma migrate, type-safe database, prisma, orm, database, typescript, postgresql, migrations, type-safe" mentioned.

Prisma ORM expert for schema design, migrations, query optimization, relations modeling, and database operations. Use PROACTIVELY for Prisma schema issues, migration problems, query performance, relation design, or database connection issues.

Decompose an unknown quantity into 3-5 estimable factors and produce a defensible order-of-magnitude answer without needing precise data. Load when the user needs to size something without data — market size, resource requirements, effort estimates, user numbers, costs — or when a decision is blocked by "we don't know the numbers". Also triggers on "ballpark this", "rough estimate", "how big is this market", "how long would this take", "how many users", or when deep-thinking diagnoses a sizing/estimation frame. The goal is not precision — it is a defensible answer that enables a decision to be made. Based on Enrico Fermi's estimation method.

Set up worker environment and per-worker state for parallel pools. Use when code needs paths, environment variables, database connections, loaded libraries, or expensive objects available on workers before parfor/parfeval runs. Teaches parallel.pool.Constant, parfevalOnAll, and parpool name-value pairs. Also use when refactoring existing code that uses spmd for side-effect setup (an anti-pattern). Triggers: worker setup, pool constant, per-worker state, non-serializable, loadlibrary on workers, database connection parfor, addpath workers, spmd before parfor, worker environment, reduce parfor overhead, parfor setup, resource creation in parallel loop, cannot serialize error, undefined function or variable on workers error, load data per worker, reduce data transfer, parallelize setup, improve parallel code.

Spectral similarity and compound identification for metabolomics. Use for comparing mass spectra, computing similarity scores (cosine, modified cosine), and identifying unknown compounds from spectral libraries. Best for metabolite identification, spectral matching, library searching. For full LC-MS/MS proteomics pipelines use pyopenms.

Prisma ORM for Node.js/TypeScript. Covers schema definition, migrations, and type-safe queries. Use when working with Prisma. USE WHEN: user mentions "prisma", "schema.prisma", "prisma migrate", "prisma generate", "prisma studio", "@prisma/client", asks about "how to define models in prisma", "prisma relations", "prisma transactions", "type-safe database queries" DO NOT USE FOR: raw SQL queries - use `database-query` MCP; Drizzle ORM - use `drizzle` skill; TypeORM - use `typeorm` skill; SQLAlchemy - use `sqlalchemy` skill

Applies Schema.org structured data principles to guide decision-making, structure analysis, and improve search visibility outcomes.

Runs large language models locally with Ollama, including model management, custom Modelfiles, and API integration. Use for private, offline LLM inference.

TypeScript 后端的 Prisma ORM 模式——Schema 设计、查询优化、事务、分页、迁移与测试

Prisma ORM patterns for TypeScript backends — schema design, query optimization, transactions, pagination, and critical traps like updateMany returning count not records, $transaction timeouts, migrate dev resetting the DB, @updatedAt skipped on bulk writes, and serverless connection exhaustion.

Production patterns and non-obvious traps for Prisma ORM in TypeScript backends, covering schema design, query optimization, transactions, pagination, and serverless connection handling.

提供英格玛·伯格曼导演风格的创意建议，涵盖视觉方案、叙事手法和场景设计，适用于剧本创作和影像设计。

Structured verbal communication framework for Senior PM and TPM interviews. Use when preparing for interviews, rehearsing answers, practicing English (or Spanish) delivery under pressure, or when any interview question needs to be answered in a crisp, structured way. Covers SCQA/STAR/C-F-I scaffolding, answer templates by question type, pushback handling, English- and Spanish-under-pressure tactics, and post-interview debrief methodology. Trigger on any variant of "how do I answer this?", "rehearse with me", "how would you say this?", or "practice interview question".

Process and analyze mass spectrometry data with the Matchms Python library, including importing spectra, filtering peaks, calculating similarity scores, and building reproducible analytical workflows.

Train, fine-tune, and deploy LLMs using LitGPT's clean implementations of 20+ architectures like Llama, Gemma, and Phi.

Screen US equities for parabolic exhaustion patterns, generate conditional pre-market short plans, and monitor intraday trigger signals using 5-min bars.

Configure and manage - Parse email parser operations. Auto-activating skill for Business Automation. Triggers on: email parser, email parser Part of the Business Automation skill category. Use when working with email parser functionality. Trigger with phrases like "email parser", "email parser", "email".

Fast DataFrame library (Apache Arrow). Select, filter, group_by, joins, lazy evaluation, CSV/Parquet I/O, expression API, for high-performance data analysis workflows.

Process tabular data with Polars' expression API, lazy evaluation, and parallel execution for fast in-memory analysis and pandas migration.

Drive Palmier Pro, an open source AI-native macOS video editor (Swift, SwiftUI/AppKit, AVFoundation) that exposes its timeline as an MCP server at `http://127.0.0.1:19789/mcp` so Claude Code/Desktop, Cursor, or Codex can read and edit a project's tracks, clips, media, transcript, captions, color/effects, and trigger generative AI (video/image/audio) requests side-by-side with a human editor. Use when the user wants to connect an agent to Palmier Pro's MCP server, call its timeline/clip/media/generation tools (`get_timeline`, `add_clips`, `move_clips`, `generate_video`, ...), build/run/test the Swift app from source, or debug the MCP tool surface in `ToolDefinitions.swift`/`ToolExecutor+*.swift`. Triggers on: "palmier pro", "palmier-pro", "AI video editor MCP", "connect Claude to my video editor", "palmier MCP server", "edit my timeline with an agent", "swift build PalmierPro", "palmier-pro mcpb", "manage_project"/"get_timeline"/"add_clips" tool.

Fast DataFrame library (Apache Arrow). Select, filter, group_by, joins, lazy evaluation, CSV/Parquet I/O, expression API, for high-performance data analysis workflows.

Process tabular data with Polars' expression API, lazy evaluation, and parallel execution for faster pandas-style workflows.

Runs a relentless interview that sharpens a plan or design. Use when the user wants to be grilled on an idea, pressure-test a plan, or refine a design through questioning.

Use for writing, reviewing, debugging, testing, or validating Python mpmath arbitrary-precision numerical code. Trigger on mpf, mpc, mp.dps, workdps, interval arithmetic, high-precision quadrature, root finding, special functions, matrices, inverse transforms, or precision/convergence failures. Do not use for ordinary NumPy vectorization, SymPy symbolic manipulation, decimal currency arithmetic, or machine-float code with no precision requirement.

Wilkinson, branchline, ratrace, directional couplers, corporate dividers, Rotman lenses for power splitting and beam-forming. TRIGGER: user asks to design, create, or analyze any coupler, splitter, power divider, combiner, or Rotman lens. Invoke BEFORE writing code — class names and design() availability vary per coupler type. SKIP: EM simulation/S-parameter extraction of an existing component (use matlab-analyze-em), building custom non-catalog geometry (use matlab-assemble-pcb-layout), material/stackup setup only (use matlab-manage-pcb-material), cascading multiple components (use matlab-integrate-pcb-circuit).

Train and run Mamba state-space models with O(n) complexity, achieving faster inference and longer context than Transformers.

State-space model with O(n) complexity vs Transformers' O(n²). 5× faster inference, million-token sequences, no KV cache. Selective SSM with hardware-aware design. Mamba-1 (d_state=16) and Mamba-2 (d_state=128, multi-head). Models 130M-2.8B on HuggingFace.

Use for writing, reviewing, debugging, testing, or optimizing Python SymPy symbolic mathematics. Trigger on Symbol, assumptions, Expr, Eq, solve/solveset, simplify, factor, expand, calculus, matrices, exact arithmetic, lambdify, code generation, or symbolic-to-numeric conversion. Do not use for NumPy-only arrays, mpmath-only arbitrary-precision numerics, CVXPY optimization models, or parsing untrusted mathematical text.

Optimize RF PCB dimensions for bandwidth, return loss, or area via patternsearch and surrogateopt with constraints. TRIGGER: user asks to optimize an RF PCB component for performance (bandwidth, return loss, insertion loss, area) or apply constraints to a design. Invoke BEFORE writing optimization code — RF PCB Toolbox has a built-in optimize() function that differs from generic fmincon/ga approaches. SKIP: designing a component from scratch without an optimization objective (use the specific matlab-design-pcb-* skill), EM analysis without optimization (use matlab-analyze-em), material/stackup setup only (use matlab-manage-pcb-material).

Laravel v12 - The PHP Framework For Web Artisans

Solve single- and multi-objective optimization problems with NSGA-II/III, MOEA/D, and other evolutionary algorithms, including Pareto front analysis, constraint handling, and benchmarking on standard test problems.

Expert guidance for fine-tuning LLMs with LLaMA-Factory - WebUI no-code, 100+ models, 2/3/4/5/6/8-bit QLoRA, multimodal support