strategic-compact
Enhance workflow efficiency by performing manual context compaction at logical task boundaries instead of relying on unpredictable auto-compaction.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
544 skills found
Enhance workflow efficiency by performing manual context compaction at logical task boundaries instead of relying on unpredictable auto-compaction.
Psychology of conversion for video and sponsored content. Uses emotional triggers, social proof, scarcity, and persuasion principles to optimize scripts and enhance audience engagement.
Diagnose and debug Agent-to-Agent (A2A) communication, including orchestrator routing, transport connectivity, agent status, and log analysis for multi-agent systems.
Expert guidance for Django asynchronous task processing with Celery. Best practices for task design, worker configuration, error handling, periodic tasks, and production monitoring.
Automatically detect code changes and suggest documentation updates. Keeps READMEs, API specs, and configuration guides in sync with your implementation.
Run mutation testing to measure test suite effectiveness by introducing code faults and verifying test failure detection.
A framework for creating reusable Claude Code agent skills, following best practices for directory structure, progressive disclosure, and multi-file patterns.
Systematic project technology stack detection, framework-specific skill auto-loading, and multi-stack analysis for fullstack projects like React + Go.
Discover and install agent skills to extend your DeerFlow capabilities. Use this to find tools, workflows, or specialized knowledge for tasks like coding, testing, and deployment.
Full-stack SDLC agent workflow managing the entire production lifecycle from intake and planning to automated testing, CI/CD, and infrastructure deployment using MCP tools.
Talent Scout is an AI-powered Apify Actor for automated candidate sourcing. It scrapes LinkedIn, GitHub, and other platforms, then uses LLMs to rank and evaluate developer profiles against job requirements.
Operate the btca CLI for source-first code research. Manage git, local, and npm resources to ground AI answers in actual codebase context rather than outdated documentation.