linkedin-lead-gen
Automated LinkedIn lead generation for tech services. Identifies non-tech founders, performs website gap analysis, and generates professional PDF audit reports for high-value B2B outreach.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
530 skills found
Automated LinkedIn lead generation for tech services. Identifies non-tech founders, performs website gap analysis, and generates professional PDF audit reports for high-value B2B outreach.
Research technical documentation and automatically generate ready-to-use software agent skills in markdown format.
Pragmatic AI-assisted coding standards focused on clean code, simplicity, and maintainability. Enforces best practices like SRP, DRY, and KISS to prevent over-engineering.
Perform a structured 8-factor conversion rate optimization (CRO) audit of any landing page to identify friction points and opportunities for growth.
A comprehensive framework for deep analysis of articles, papers, and long-form content using 10+ thinking models like SCQA, First Principles, and Systems Thinking.
Automate Python scripting and Gemini-powered image generation using uv. Ideal for creating art, editing images, and running ad-hoc scripts.
Official Mastra framework guide. Master AI agent and workflow development with local documentation lookup, API verification, and TypeScript-based project management.
Automate booking, search, and reservation workflows via browser automation with screenshot verification and confirmation tracking.
Build modern, composable, and accessible React UI components following the components.build specification. Use for design systems, component libraries, and reusable UI architectures.
A utility skill for testing multi-skill loading and orchestration within the Sheikh-CLI agentic framework.
Transform raw data into compelling, decision-driving narratives using visualization strategies, story frameworks, and persuasive structures for analytics and executive reporting.
A framework for managing the end-to-end LLM project lifecycle, from evaluating task-model fit and pipeline architecture design to implementing structured output parsing and agent-assisted development.