Best Practices on Recommendation Systems
Skill-Verzeichnis
Wiederverwendbare Skills für AI Agents entdecken.
Jede Empfehlung bleibt mit ihrem Repository, Audit und Installationspfad nachvollziehbar.
Suchergebnisse: explainable-recommendation
Englisches VerzeichnisAI skill for OpenClaw & Claude Code — recommend from 10000+ Nano Banana Pro (Gemini) image prompts. Smart search by use case, content remix, sample images.
PipesHub is a fully extensible and explainable workplace AI platform for enterprise search and workflow automation
AI on the way. An auto deep learning pipe dream. An RDBMS approach to deep learning. Declarative, explainable, scalable, optimizable, easy to deploy, all that good stuff.
Glamorous Toolkit is the Moldable Development Environment. It empowers you to make systems explainable through contextual micro tools.
Semantica 🧠 — AI-native knowledge graph intelligence framework for semantic retrieval, ontology reasoning, context graphs, and explainable AI systems.
A platform-neutral analytical skill that profiles messy data, selects adaptive methods, and produces source-backed visual reports for high-stakes decisions.
Pre-install security scanner and guarded installer for Agent Skills. Quarantine, scan, enforce policy, and verify skills before they reach Codex, Claude Code, Cursor, Gemini CLI, or OpenClaw.
A portable agent skill that makes AI agents research comparable projects, tradeoffs, costs, and failure conditions before giving build advice.
Research a US equity across fundamentals, valuation, technical context, peers, and current market data.
Test Cherry Studio PRs by resolving and checking out a PR, statically inspecting its changes, running interactive UI tests against a safely tracked Electron instance through CDP, producing a structured report, cleaning up only the owned test instance, and restoring the original branch.
A comprehensive monitoring, recommendation, and OpenAI-compatible gateway system for AI API endpoints with layered probing, health scoring, and self-hosted deployment.