prompt-optimization-analyzer

More from exploration-labs/nates-substack-skills

• skill-security-analyzer

  Comprehensive security risk analysis for Claude skills. Use when asked to analyze security risks, review security stance, audit skills for vulnerabilities, check security before deployment, or evaluate safety of skill files. Triggers include "analyze security," "security risks," "security audit," "security review," "is this skill safe," or "check for vulnerabilities.

  13

• vibe-coding

  Comprehensive guide for AI-assisted vibe coding. Use when the user wants to build applications through natural language prompts using tools like Lovable, Cursor, Replit, or Bolt. Includes best practices, pitfall awareness, tool-specific guidance, architectural decision support, and MVP scope definition with a bias toward cutting features aggressively to ship faster.

  12

• skill-testing-framework

  Provides test cases and validation tools for skills. Use when creating tests for a new skill, adding regression tests after skill updates, running test suites to verify skill functionality, or validating that skill outputs match expected results. Supports unit tests, integration tests, and regression tests with input/output pair validation.

  10

• learning-capture

  Recognize and capture reusable patterns, workflows, and domain knowledge from work sessions into new skills. Use when completing tasks that involve novel approaches repeated 2+ times, synthesizing complex domain knowledge across conversations, discovering effective reasoning patterns, or developing workflow optimizations. Optimizes for high context window ROI by identifying patterns that will save 500+ tokens per reuse across 10+ future uses.

  9

• agentic-development

  Conversational guidance for building software with AI agents, covering workflows, tool selection, prompt strategies, parallel agent management, and best practices based on real-world high-volume agentic development experience. Use this skill when users ask about setting up agentic workflows, choosing models, optimizing prompts, managing parallel agents, or improving agent output quality.

  9