context-engineering-collection
A structured repository of Agent Skills for context engineering, multi-agent architectures, and production-grade agent system optimization.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
450 skills found
A structured repository of Agent Skills for context engineering, multi-agent architectures, and production-grade agent system optimization.
Genomic file toolkit for NGS data processing. Read/write SAM/BAM/CRAM alignments, VCF/BCF variants, and FASTA/FASTQ sequences using Pysam with a Pythonic interface to htslib.
Generates minimal macOS Seatbelt sandbox configurations for application isolation and security profiling.
Ziwei Doushu charting and layered interpretation engine. Analyzes natal, yearly, monthly, and daily horoscopes using structured data, offering systematic, evidence-based astrological insights.
Create and manage recurring tasks and one-off reminders using natural time inputs or cron expressions to keep your AI assistant organized.
Expert framework for designing agent-facing tools, optimizing tool descriptions, enforcing contract-based APIs, and implementing architectural reduction for reliable AI agent tool selection.
An automated memory middleware for AI agents, implementing a Retrieve-Respond-Save loop to maintain long-term persistent context across conversations.
Robot perception system design, configuration, and optimization for cameras, LiDAR, and sensor fusion pipelines. Includes camera calibration, 3D reconstruction, and production deployment best practices.
Integrate, fix, and debug Duit/flutter_duit backend-driven UI (BDUI) in Flutter applications. Supports remote/static layouts, custom components, transport managers, and lifecycle debugging.
A precision-focused UX/UI engineering agent for identifying bugs, optimizing usability, and ensuring flawless interface performance in workflow applications.
Automated runtime observability changelog for Claude Code development sessions, tracking file changes, test results, and git commits.
Token-efficient codebase analysis skill for call graphs, semantic search, impact analysis, and data flow. Saves ~95% tokens vs. raw reads.