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Multi-agent Orchestration
Frameworks and tools for coordinating multiple agents, teams, roles, swarms, or AI workforces.
Which technical function should the agent perform?
Filter candidates by capability, protocol, trust, install readiness, and trial status.
- Coordinate several agents around one outcome.
- Assign specialist roles and handoffs.
- Inspect launch packets before running a team.
Recommended trials and bundles
This skill helps you design and deploy production-grade LLM apps, RAG systems, and intelligent agents with robust safety and observability.
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill helps AI agents detect and generate contextually appropriate humor using 12 bisociation patterns with ethical gating.
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
Operational patterns for LLM inference: latency budgeting, tail-latency control, caching, batching/scheduling, quantization/compression, parallelism, and reliable serving at scale. Emphasizes production-grade performance, cost control, and observability.
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill turns raw data and questions into validated, documented models ready for production:
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
End-to-end data science and ML engineering workflows: problem framing, data/EDA, feature engineering (feature stores), modelling, evaluation/reporting, plus SQL transformations with SQLMesh. Use for dataset exploration, feature design, model selection, metrics and slice analysis, model cards/eval reports, experiment reproducibility, and production handoff (...
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
Operational patterns, templates, and decision rules for time series forecasting (modern best practices): tree-based methods (LightGBM), deep learning (Transformers, RNNs), future-guided learning, temporal validation, feature engineering, generative TS (Chronos), and production deployment. Emphasizes explainability, long-term dependency handling, and adaptiv...
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
Production MLOps and ML/LLM/agent security skill for deploying and operating ML systems in production (registry + CI/CD, serving, monitoring/drift, evaluation loops, incident response/runbooks, and governance), including GenAI security (prompt injection, jailbreaks, RAG security, privacy, and supply chain).
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill generates a Chinese AI news digest from multiple sources, deduplicates items, and traces origins for easy reference.
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill delivers real-time AI news briefings from AI News Oracle, summarizing top sources for autonomous agents without manual browsing.
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill enables AI agents to access and utilize AI-friendly, GitHub-hosted notes for quick lookup, understanding, and knowledge sharing.
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
Operational prompt engineering for production LLM apps: structured outputs (JSON/schema), deterministic extractors, RAG grounding/citations, tool/agent workflows, prompt safety (injection/exfiltration), and prompt evaluation/regression testing. Use when designing, debugging, or standardizing prompts for Codex CLI, Claude Code, and OpenAI/Anthropic/Gemini AP...
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
Review links
Technical category pages stay focused on job browsing; complete review records and finalist profile resources stay linked here.
Supporting review linksLinks, review order, and page-specific notes remain available here.
4955 matching candidates for Multi-agent Orchestration. Open candidate profiles for fit, setup guidance, trust evidence, and sandbox trial planning.
- 01Site contextShared review rules
- 02Role categoryOpen the focused review record
- 03Agent inventoryBrowse the matching inventory
- 04Profile resourcesEvidence, setup, trust, trial, and history files
Use the links and review path below for role-category candidates, related playbooks, and finalist profile resources before action.