Find the perfect capability for your agent.
Deploy, manage environment variables, view logs, and configure cron jobs with Vercel CLI. Use when deploying to Vercel, managing env vars (add/update/remove), viewing runtime/build logs, or configuring scheduled tasks in vercel.json.
Create and use custom slash commands to automate Claude Code workflows. Learn argument passing, frontmatter configuration, bash integration, and file references for building reusable prompts.
Adapt Claude Code for different use cases beyond software engineering by customizing system prompts for teaching, learning, analysis, or domain-specific workflows.
Deploy, manage services, view logs, and configure Railway infrastructure. Use when deploying to Railway, managing environment variables, viewing deployment logs, scaling services, or managing volumes.
Teaches how to write effective documentation and instructions for LLMs by assuming competence, using progressive disclosure, prioritizing examples over explanations, and building feedback loops into workflows.
Emulate the user's personal writing voice and style patterns. Use when the user asks to write content in their voice, draft documents, compose messages, or requests "write this like me" or "in my style."
Coordinate concurrent task execution through agent delegation. Plan independent work, manage dependencies, and execute multiple agents simultaneously. Use when handling multiple unrelated tasks, research investigations, or layer-based implementations that can run concurrently.
Specialized AI assistants for task-specific workflows with separate context. Learn when to delegate, configure tools, and apply best practices.
Package expertise into discoverable, reusable capabilities that extend Claude's functionality. Use when creating new Skills, understanding how Skills work, or organizing existing capabilities.
Diagnose and fix bugs through systematic investigation, root cause analysis, and targeted validation. Use when something is broken, errors occur, performance degrades, or unexpected behavior manifests.
Maintain project documentation synchronized with code. Keep feature specs, API contracts, and README current with init-project standards. Use when updating docs after code changes, adding new features, or ensuring documentation completeness.
Systematically evaluate code changes for security, correctness, performance, and spec alignment. Use when reviewing PRs, assessing code quality, or verifying implementation against requirements.
Write automated tests for features, validate functionality against acceptance criteria, and ensure code coverage. Use when writing test code, verifying functionality, or adding test coverage to existing code.
Protocol Designer (PD) application architecture, Redux slices, step/timeline system, domain concepts, and dev workflow. Use when working with files in protocol-designer/ or discussing PD features, steps, timelines, or protocol design.
Conventions for the opentrons-ai-client React/TypeScript frontend — project structure, API integration, state management (Jotai), feature flags, types, and testing. Use when working with files in opentrons-ai-client/ or discussing the AI client application.
TypeScript conventions, React patterns, testing, styling, and import rules for the Opentrons monorepo JS/TS packages. Use when working with TypeScript or React files in app/, components/, shared-data/, step-generation/, protocol-designer/, protocol-visualization/, opentrons-ai-client/, or other JS/TS packages.
Component creation checklist and ai-client-specific patterns for React .tsx files in opentrons-ai-client/ and protocol-designer/. Use when creating new React components in these packages.
Execute repeated shell commands as separate tool calls with a delay between each iteration. Use when a user asks to run something N times, wait between runs, increment a counter each cycle, and see each iteration result before the next run.
Write comprehensive literature reviews for medical imaging AI research. Use when writing survey papers, systematic reviews, or literature analyses on topics like segmentation, detection, classification in CT, MRI, X-ray, ultrasound, or pathology imaging. Triggers on requests for "review paper", "survey", "literature review", "综述", "systematic review", or mentions of writing academic reviews on deep learning for medical imaging.
