By github
Refines rough prompts, vague ideas, or task descriptions into finished, copy-pasteable prompts optimized for any LLM chat interface, outputting a single code block with no placeholders.
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npx claudepluginhub simplycubed/skills --plugin prompt-optimizerVisual whiteboard collaboration — opens an interactive whiteboard in your browser, Copilot sees your drawings and responds. NOTE: Copilot CLI only — this plugin uses Copilot CLI plugin structure (.github/plugin/plugin.json) which Claude Code does not discover.
Scaffolds an xUnit integration test project for validating Oracle-to-PostgreSQL database migration behavior in.NET solutions. Creates the test project, transaction-rollback base class, and seed data manager. Use when setting up test infrastructure before writing migration integration tests, or…
Review and refactor code in your project according to defined instructions
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.
Full STRIDE-A threat model analysis and incremental update skill for repositories and systems. Supports two modes: (1) Single analysis — full STRIDE-A threat model of a repository, producing architecture overviews, DFD diagrams, STRIDE-A analysis, prioritized findings, and executive assessments.…
+ask +deep +web <- modifiers | optimize your prompts
Analyze and optimize AI prompts for better results
Intelligent prompt optimization: injects the right context at the right moment so Claude lands a better first output. Clarifies vague prompts with research-based questions, plus targeted nudges for approach selection, plan readability, workflow routing, background execution, subagent routing, output readability, user-decision questions, and plan-mode assessment
Expert Prompt Engineer with Context Engineering, Meta-Prompting, Chain-of-Thought, Few-Shot, Agent Design, 50+ Template Library, and A/B Testing
Review AI prompts for safety, bias, and security vulnerabilities, with improvement recommendations, testing methodologies, and frameworks for hardening prompt-driven systems.
Tools for crafting, reviewing, analyzing, refining, and optimizing LLM prompts for clarity, precision, goal effectiveness, and token efficiency