Skills
Discover and install skills to enhance Claude Code.
2,058 skills found
filesystem-context
This skill should be used when the user asks to "offload context to files", "implement dynamic context discovery", "use filesystem for agent memory", "reduce context window bloat", or mentions file-based context management, tool output persistence, agent scratch pads, or just-in-time context loading.
seo-content-writer
Writes SEO-optimized content based on provided keywords and topic briefs. Creates engaging, comprehensive content following best practices. Use PROACTIVELY for content creation tasks.
cursor-indexing-issues
Manage troubleshoot Cursor codebase indexing problems. Triggers on "cursor indexing", "cursor index", "cursor codebase", "@codebase not working", "cursor search broken". Use when working with cursor indexing issues functionality. Trigger with phrases like "cursor indexing issues", "cursor issues", "cursor".
1k-state-management
Jotai state management patterns — atoms, globalAtom, contextAtom, and persistence.
ai-elements
Create new AI chat interface components for the ai-elements library following established composable patterns, shadcn/ui integration, and Vercel AI SDK conventions. Use when creating new components in packages/elements/src or when the user asks to add a new component to ai-elements.
cursor-git-integration
Manage integrate Git workflows with Cursor IDE. Triggers on "cursor git", "git in cursor", "cursor version control", "cursor commit", "cursor branch". Use when working with cursor git integration functionality. Trigger with phrases like "cursor git integration", "cursor integration", "cursor".
drug-repurposing
Identify drug repurposing candidates using ToolUniverse for target-based, compound-based, and disease-driven strategies. Searches existing drugs for new therapeutic indications by analyzing targets, bioactivity, safety profiles, and literature evidence. Use when exploring drug repurposing opportunities, finding new indications for approved drugs, or when users mention drug repositioning, off-label uses, or therapeutic alternatives.
memory-sync
Scrape and analyze OpenClaw JSONL session logs to reconstruct and backfill agent memory files. Use when: (1) Memory appears incomplete after model switches, (2) Verifying memory coverage, (3) Reconstructing lost memory, (4) Automated daily memory sync via cron/heartbeat. Supports simple extraction and LLM-based narrative summaries with automatic secret sanitization.
verify-changes
Runs unit tests to quickly verify changes during the development loop.
paprika
Access recipes, meal plans, and grocery lists from Paprika Recipe Manager. Use when user asks about recipes, meal planning, or cooking.
table-extractor
Extract tables from PDFs with high accuracy using camelot - handles complex table structures
pdf-form-filler
Fill PDF forms programmatically with text values and checkboxes. Use when you need to populate fillable PDF forms (government forms, applications, surveys, etc.) with data. Supports setting text fields and checkboxes with proper appearance states for visual rendering.
homeassistant
Control Home Assistant - smart plugs, lights, scenes, automations.
statistics-math
Statistics, probability, linear algebra, and mathematical foundations for data science
ralph-wiggum
Implements the Ralph Wiggum autonomous iteration technique with deliberate context management. Use when building greenfield projects, iterating on well-defined tasks, or when continuous autonomous development is needed. Manages context like memory - tracks allocations, prevents redlining, and knows when to start fresh.
laravel-architecture
Core architectural standards for scalable Laravel applications.
spec-to-backlog
Automatically convert Confluence specification documents into structured Jira backlogs with Epics and implementation tickets. When Claude needs to: (1) Create Jira tickets from a Confluence page, (2) Generate a backlog from a specification, (3) Break down a spec into implementation tasks, or (4) Convert requirements into Jira issues. Handles reading Confluence pages, analyzing specifications, creating Epics with proper structure, and generating detailed implementation tickets linked to the Epic.
pytorch
Building and training neural networks with PyTorch. Use when implementing deep learning models, training loops, data pipelines, model optimization with torch.compile, distributed training, or deploying PyTorch models.