Find, trial, compare, and govern AI agents before hiring
Prototype, inspect, and improve product UI, UX, and design implementation flows.
Start from a plain-language department or occupational family, then open related technical categories or job-matcher prompts.
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This skill helps initialize memory as a 15-25 file hierarchical structure under system/, guiding agents to organize memory for continuity.
A Python library that bridges meeting platforms with AI agent workflows. It enables AI agents to join, listen, and interact in virtual meetings by providing a unified interface for real-time audio and video streams.
Julius is a community-developed tool for building and running autonomous AI agents. It provides a chat-based interface to define agent behaviors and execute tasks. The tool is designed for users who want to experiment with agentic workflows.
Metatron is a self-hosted system that captures a codebase's real implementation decisions as structured priors. It serves these priors to coding agents over MCP (Model Context Protocol). The goal is to make an agent write code like a senior engineer who already knows the codebase.
Expert guidance for building LangChain agents with proper tool binding, memory, and configuration. Use when creating agents, configuring models, or setting up tool integrations in LangConfig.
This skill helps you build stateful AI agents with graph-based workflows, enabling checkpoints, human-in-the-loop, and subgraph composition.
Expert guidance for designing LangGraph state machines and multi-agent workflows. Use when building workflows, connecting agents, or implementing complex control flow in LangConfig.
Audit a codebase for the 12 leverage points of agentic coding. Identifies gaps and provides prioritized recommendations. Use when improving agentic coding capability, analyzing why agents fail, or optimizing a codebase for autonomous work.
AI-powered customer engagement, support, and sales solutions.
MCP server for MDMA — exposes spec, prompts, docs, and package metadata to AI assistants.
Create meta prompts, meta agents, and meta skills that build other agentic components. Use when scaling agentic layer development, creating generators/templates, or implementing "build the system that builds the system" patterns.
This skill applies anti-over-engineering principles to surgical, minimal changes using existing utilities and conventions to modify code.
Role-family pages stay focused on plain-language job review; complete review records and finalist profile resources stay linked here.
4988 candidates for Design. Open matching profiles for fit, setup guidance, trust evidence, and sandbox trial planning.
Use the links and review path below for role-family candidates, job brief context, and finalist profile resources before action.