Cursor Skill 目錄

Generate tailored AI agent instruction files via AgentRC instructions command. Produces .github/copilot-instructions.md (default, recommended for Copilot in VS Code) plus optional per-area .instructions.md files with applyTo globs for monorepos. Use after running /acreadiness-assess to close gaps in the AI Tooling pillar.

A comprehensive guide for GitHub Copilot to craft immersive, high-performance web experiences with advanced motion, typography, and architectural craftsmanship.

Creates an integration testing plan for .NET data access artifacts during Oracle-to-PostgreSQL database migrations. Analyzes a single project to identify repositories, DAOs, and service layers that interact with the database, then produces a structured testing plan. Use when planning integration test coverage for a migrated project, identifying which data access methods need tests, or preparing for Oracle-to-PostgreSQL migration validation.

PostgreSQL-specific development assistant focusing on unique PostgreSQL features, advanced data types, and PostgreSQL-exclusive capabilities. Covers JSONB operations, array types, custom types, range/geometric types, full-text search, window functions, and PostgreSQL extensions ecosystem.

Identifies Oracle-to-PostgreSQL migration risks by cross-referencing code against known behavioral differences (empty strings, refcursors, type coercion, sorting, timestamps, concurrent transactions, etc.). Use when planning a database migration, reviewing migration artifacts, or validating that integration tests cover Oracle/PostgreSQL differences.

Universal SQL performance optimization assistant for comprehensive query tuning, indexing strategies, and database performance analysis across all SQL databases (MySQL, PostgreSQL, SQL Server, Oracle). Provides execution plan analysis, pagination optimization, batch operations, and performance monitoring guidance.

Creates structured bug reports for defects found during Oracle-to-PostgreSQL migration. Use when documenting behavioral differences between Oracle and PostgreSQL as actionable bug reports with severity, root cause, and remediation steps.

Generate a complete Model Context Protocol server project in Swift using the official MCP Swift SDK package.

Bulk-migrate metadata to GitHub issue fields from two sources: repo labels (e.g. priority labels to a Priority field) and Project V2 fields. Use when users say "migrate my labels to issue fields", "migrate project fields to issue fields", "convert labels to issue fields", "copy project field values to issue fields", or ask about adopting issue fields. Issue fields are org-level typed metadata (single select, text, number, date) that replace label-based workarounds with structured, searchable, cross-repo fields.

Prompt for generating an AGENTS.md file for a repository

Creates, reads, updates, and deletes Arize AI integrations that store LLM provider credentials used by evaluators and other Arize features. Supports any LLM provider (e.g. OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, Vertex AI, Gemini, NVIDIA NIM). Use when the user mentions AI integration, LLM provider credentials, create integration, list integrations, update credentials, delete integration, or connecting an LLM provider to Arize.

Creates, manages, and queries Arize datasets and examples. Covers dataset CRUD, appending examples, exporting data, and file-based dataset creation using the ax CLI. Use when the user needs test data, evaluation examples, or mentions create dataset, list datasets, export dataset, append examples, dataset version, golden dataset, or test set.

Creates, runs, and analyzes Arize experiments for evaluating and comparing model performance. Covers experiment CRUD, exporting runs, comparing results, and evaluation workflows using the ax CLI. Use when the user mentions create experiment, run experiment, compare models, model performance, evaluate AI, experiment results, benchmark, A/B test models, or measure accuracy.

Use when: comparing SQL Server tables across instances, data migration validation, ETL verification, row mismatch detection, schema drift, reconciliation report, production vs staging comparison. Uses mssql-python driver with Apache Arrow for fast columnar data transfer and comparison.

Adds Arize AX tracing to an LLM application for the first time. Follows a two-phase agent-assisted flow to analyze the codebase then implement instrumentation after user confirmation. Use when the user wants to instrument their app, add tracing from scratch, set up LLM observability, integrate OpenTelemetry or openinference, or get started with Arize tracing.

Converts draft customer-story Markdown into Langfuse website MDX (Fumadocs), collects missing metadata and assets, wires meta.json and authors. Use when adding or converting a customer case study, user story, or /users page, or when the user mentions customer story setup, cresta/canva-style posts, or CustomerStoryCTA/BlogHeader for customers.

Search, find, discover, install, remove, update, review, list, move, optimise, and iterate on skills for AI coding agents. Use when user asks "find a skill for X", "search for a skill", "is there a skill for X", "install skill", "remove skill", "update skills", "list skills", "review skill quality", "move skill", "check for updates", "optimise skill", "train skill on tasks", "iterate skill", "audit skill edits", "log skill edit", "diff skill versions", "trigger test skill", "transfer skill across agents", or "how do I do X" where X might have an existing skill. THE tool for skill discovery, ecosystem search, and SkillOpt-style training loops. Do not use for creating skills from scratch (use /skill-creator instead).

Delegate your agent-skill lifecycle: keep skills current, audit and clean up your inventory, and vet skills before you install them. The Skillsmith Agent diagnoses in full for free, proposes a batched fix plan, and changes files only with your per-changeset approval, with one-step undo. Triggers: "ask the Skillsmith Agent", "clean up my skills", "what skills are outdated", "audit my skills", "vet this skill before I install it".

Use when the user wants to plan and implement a non-trivial task in this repo. Runs a multi-phase flow — discovery, parallel exploration, clarifying questions, parallel architectures, approval gate, implementation, parallel review, summary.

Use when the user wants to plan and implement a non-trivial task in this repo. Runs a multi-phase flow — discovery, parallel exploration, clarifying questions, parallel architectures, approval gate, implementation, parallel review, summary.

Use when the user wants to plan and implement a non-trivial task in this repo. Runs a multi-phase flow — discovery, parallel exploration, clarifying questions, parallel architectures, approval gate, implementation, parallel review, summary.

Use when the user wants to plan and implement a non-trivial task in this repo. Runs a multi-phase flow — discovery, parallel exploration, clarifying questions, parallel architectures, approval gate, implementation, parallel review, summary.

Use when the user wants to plan and implement a non-trivial task in this repo. Runs a multi-phase flow — discovery, parallel exploration, clarifying questions, parallel architectures, approval gate, implementation, parallel review, summary.

Use when the user wants to plan and implement a non-trivial task in this repo. Runs a multi-phase flow — discovery, parallel exploration, clarifying questions, parallel architectures, approval gate, implementation, parallel review, summary.