Deep research where agents adversarially fact-check each other's findings instead of one agent confidently citing sources it never verified.
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50 agent skills — instructions the agent loads on demand. 50 of 50 are free. Median context cost 2.1k tokens.
Creates generative and computational art using p5.js with seeded randomness, particle systems, and interactive exploration.
Produce a multi-altitude explainer of a body of work — what it is, why it matters, where it sits, and how it was learned.
Generates and maintains C4 architecture diagrams (Context, Container, Component) as Mermaid in docs/architecture/.
Core patterns for building AI coding agents with tool calling, agent loops, and autonomous code execution — plus expert guidance on agent…
Connected analyze-plan-execute-learn-repeat cycle with persistent memory.
Audit token consumption across all loaded components — skills, agents, MCP tools, rules, hooks
Generate structured alternate timelines for a past decision log entry and write them as a `reflection` entry under your decision wiki's…
Single-pass 3-agent critique for ANY work product — plans, code, designs, architecture.
Creates data visualizations with D3.js including custom charts, network diagrams, geographic maps, and publication-quality interactive…
Multi-agent research swarm that finds existing solutions before you write a single line of code.
Secure cloud sandbox execution for AI coding agents using E2B.
The rest either hold an API key issued by the publisher or ask for nothing.
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