Explore our collection of Agent Skills to enhance your AI workflow.
Analyzes Claude Code interaction history and Git data through SQL queries to reveal developer productivity patterns.
Conducts comprehensive code reviews focusing on security vulnerabilities, performance bottlenecks, and architectural best practices.
Guides users through the automated setup, project detection, and configuration of the Agentic Loop autonomous coding toolkit.
Scaffolds and guides the development of Screenly Edge Apps using Figma designs and standardized templates.
Analyzes Federal Election Commission campaign finance filings and reports directly within the Claude environment.
Generates distinctive, production-grade frontend interfaces with high design quality and unique creative character.
Automates the end-to-end GitHub pull request process including branch management, rebasing, and PR creation.
Automates the conversion of Vertica DDL into production-ready dbt models optimized for Snowflake Data Cloud.
Debugs and fixes Playwright end-to-end tests for browser extensions while minimizing flakiness in dynamic environments.
Generates comprehensive RTL implementation plans and architectural specifications for SystemVerilog hardware design.
Facilitates interactive SystemVerilog mastery through curriculum-based exercises, automated solution reviews, and guided hints.
Lints SystemVerilog code using Verilator to identify design errors, warnings, and performance bottlenecks with structured feedback.
Maps and documents complex SystemVerilog codebases using parallel AI agents to accelerate hardware design onboarding and architectural analysis.
Automates the entire SystemVerilog hardware design lifecycle, from architecture planning and RTL generation to automated linting and simulation-based verification.
Builds reliable, event-driven background jobs and durable serverless workflows without managing complex infrastructure or queues.
Refines ambiguous SystemVerilog requests through interactive clarification and architectural trade-off analysis.
Simplifies SystemVerilog development by converting complex Verilator lint and simulation outputs into actionable, readable reports.
Compiles and executes SystemVerilog simulations using Verilator with automated file classification and structured result reporting.
Manages Jira tickets, backlogs, and issue lifecycles directly through natural language commands within Claude.
Orchestrates SystemVerilog development workflows by semantically classifying user intent and routing tasks to specialized hardware design agents.
Implements professional-grade SystemVerilog verification patterns and layered testbench architectures for robust RTL validation.
Orchestrates parallel SystemVerilog RTL design and verification by decomposing complex hardware architectures into manageable components.
Evaluates product initiatives using Bezos's decision framework and Shape Up's appetite model to optimize resource allocation and project scoping.
Refines project scope using Shape Up's appetite-first approach to ensure fast, high-quality delivery within fixed time constraints.
Guides product positioning strategy using the Obviously Awesome framework to define differentiation and market categories.
Generates concise, evidence-driven Product Requirements Documents (PRDs) that bridge the gap between product vision and engineering execution.
Structures and executes product launches using a tiered framework to ensure coordinated releases and effective go-to-market strategies.
Prioritizes product backlogs and feature requests using quantitative RICE scoring and the Linear enabler/blocker framework.
Interacts with web pages by remote controlling Chrome or Chromium browsers using the Chrome DevTools Protocol.
Evaluates market demand and problem-solution fit using an evidence-based scoring framework to prevent building products nobody wants.
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