010-archive/backups-20251108/plugin-enhancements/plugin-backups/ai-ml-engineering-pack_20251019_161259/skills/skill-adapter/SKILL.md
This skill optimizes prompts for Large Language Models (LLMs) to reduce token usage, lower costs, and improve performance. It analyzes the prompt, identifies areas for simplification and redundancy removal, and rewrites the prompt to be more concise and effective. It is used when the user wants to reduce LLM costs, improve response speed, or enhance the quality of LLM outputs by optimizing the prompt. Trigger terms include "optimize prompt", "reduce LLM cost", "improve prompt performance", "rewrite prompt", "prompt optimization".
npx skillsauth add intent-solutions-io/plugins-nixtla Optimizing PromptsInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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This skill empowers Claude to refine prompts for optimal LLM performance. It streamlines prompts to minimize token count, thereby reducing costs and enhancing response speed, all while maintaining or improving output quality.
This skill activates when you need to:
User request: "Optimize this prompt for cost and quality: 'I would like you to create a detailed product description for a new ergonomic office chair, highlighting its features, benefits, and target audience, and also include information about its warranty and return policy.'"
The skill will:
User request: "Optimize this prompt for better summarization: 'Please read the following document and provide a comprehensive summary of all the key points, main arguments, supporting evidence, and overall conclusion, ensuring that the summary is accurate, concise, and easy to understand.'"
The skill will:
This skill integrates with the prompt-architect agent to leverage advanced prompt engineering techniques. It can also be used in conjunction with the llm-integration-expert to optimize prompts for specific LLM APIs.
testing
This skill enables Claude to manage isolated test environments using Docker Compose, Testcontainers, and environment variables. It is used to create consistent, reproducible testing environments for software projects. Claude should use this skill when the user needs to set up a test environment with specific configurations, manage Docker Compose files for test infrastructure, set up programmatic container management with Testcontainers, manage environment variables for tests, or ensure cleanup after tests. Trigger terms include "test environment", "docker compose", "testcontainers", "environment variables", "isolated environment", "env-setup", and "test setup".
tools
This skill uses the test-doubles-generator plugin to automatically create mocks, stubs, spies, and fakes for unit testing. It analyzes dependencies in the code and generates appropriate test doubles based on the chosen testing framework, such as Jest, Sinon, or others. Use this skill when you need to generate test doubles, mocks, stubs, spies, or fakes to isolate units of code during testing. Trigger this skill by requesting test double generation or using the `/gen-doubles` or `/gd` command.
tools
This skill enables Claude to generate realistic test data for software development. It uses the test-data-generator plugin to create users, products, orders, and custom schemas for comprehensive testing. Use this skill when you need to populate databases, simulate user behavior, or create fixtures for automated tests. Trigger phrases include "generate test data", "create fake users", "populate database", "generate product data", "create test orders", or "generate data based on schema". This skill is especially useful for populating testing environments or creating sample data for demonstrations.
development
This skill analyzes code coverage metrics to identify untested code and generate comprehensive coverage reports. It is triggered when the user requests analysis of code coverage, identification of coverage gaps, or generation of coverage reports. The skill is best used to improve code quality by ensuring adequate test coverage and identifying areas for improvement. Use trigger terms like "analyze coverage", "code coverage report", "untested code", or the shortcut "cov".