Inspect production errors recorded in Sentry through read-only API access. Summarize unresolved issues, recent crashes, occurrence counts, and event details to understand what happened and when each problem was last seen.
Measure website performance with Lighthouse, interpret scores and reports, and compare results across builds. Set limits for loading times and resource sizes, then integrate audits into CI, an automated workflow that checks code changes.
Write, review, and refactor React and Next.js code using performance guidelines from Vercel Engineering. Prioritize improvements to data fetching, downloaded code size, server processing, and unnecessary rendering, with rule files providing explanations and code examples.
Improve how search engines discover and understand a website by reviewing titles, descriptions, links, and sitemaps. Add structured data, machine-readable descriptions of page content, and use checklists to identify technical and on-page SEO issues.
Create, audit, and improve pages for AI search engines by checking crawl access, metadata, clear answers, sources, and structured data that describes page content. It produces prioritized fixes and citation-friendly pages without guaranteeing inclusion in AI answers.
Analyze git history to map contributors to security-sensitive files and identify ownership gaps. Estimate bus factor, a measure of dependence on few people, group files that change together, and export CSV or JSON for further analysis.
Explore and configure an Nx monorepo, where multiple projects share one repository. Inspect resolved project settings, identify projects affected by changes, and improve project boundaries, build caching, and CI/CD pipelines.
Turn descriptions or code analysis into Mermaid diagrams for workflows, system architecture, and database relationships. Check diagram syntax and export SVG, PNG, or text-based ASCII output, with themes and batch rendering options.
Plan social selling on LinkedIn through profile improvements, relevant posts, personalized direct messages, and follow-ups. Build a clear path from audience engagement to sales conversations, with metrics to track which activities generate meetings.
Audit and improve website accessibility using WCAG 2.1, guidelines for making web content usable by people with disabilities. Check image descriptions, contrast, forms, keyboard controls, and screen reader support with automated and manual testing.
Review web code for security, browser compatibility, and code quality. Covers HTTPS, dependency vulnerabilities, security headers, outdated APIs, HTML structure, error handling, and cleanup of event listeners, with examples and audit checklists to guide improvements.
Run builds, tests, code checks, and development servers in an Nx workspace. Choose one project, several projects, or projects affected by changes, with options for parallel execution, cached results, and failure handling.
Design processes to retain customers and grow revenue from existing accounts. Use product activity and customer relationships to define risk signals, upgrade opportunities, onboarding steps, renewal schedules, and follow-up plans for previously lost sales opportunities.
Turn AI-assisted coding work into optional, short learning exercises. Predict behavior, compare your approach with the implementation, or explain code in your own words, with feedback that helps clarify how the code works and why design choices were made.
Plan AI sales development systems that qualify prospects, organize outreach, classify replies, and hand opportunities to people. Use customer criteria, budget, CRM setup, and sales goals to shape platform choices and a four-week rollout plan.
Plan a product launch across discovery sites, social media, and communities. Select channels for the intended audience, build a waitlist, prepare launch materials, coordinate launch-day activities, and organize follow-up promotion and measurement.
Plan customer acquisition as a solo founder, from choosing tools and sales channels to assigning work to AI agents. Organize priorities by revenue stage, divide time between building and selling, and assess when hiring makes sense.
Define ideal customers and a clear market position for an AI product. Use customer evidence to separate customer fit from buying intent, turn technical capabilities into business messages, and plan recurring checks of product-market fit.
Create applications, libraries, and feature scaffolding with Nx generators, tools that produce starter code. It discovers suitable generators, prefers workspace-specific options, checks their behavior, and adjusts and verifies the generated files against existing project conventions.
Review a pull request using repository checks, verified code references, and current official documentation. Assess correctness, security, structure, and unnecessary code, then post one consolidated GitHub review with inline findings and an evidence-based verdict.
Fetch design structure, screenshots, variables, and assets from Figma through MCP, a connection between the agent and Figma. Use these references to guide code implementation within an existing project and troubleshoot connection setup.
Collect review threads and comments from the open GitHub pull request for the current branch. Summarize the fixes each comment needs, then apply changes for the comments the user selects using the gh command-line tool.
Evaluate code against a product requirements document, scoring implementation and tests separately for each acceptance criterion. Produce an evidence-backed final grade, identify gaps, and compare implementations using a fixed checklist and scoring method.
Deploy applications to Render by inspecting the code and preparing service settings. Generate a render.yaml configuration or create services through MCP, an agent tool connection, then check deployment status, logs, and basic service health.
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