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Found 518 Skills
Agent skill for swarm-pr - invoke with $agent-swarm-pr
Guide for creating properly structured YAML configuration files for MassGen. This skill should be used when agents need to create new configs for examples, case studies, testing, or demonstrating features.
Lance une revue d'issue automatique avec des personas experts sélectionnés automatiquement, analyse la faisabilité, la complétude, les risques et l'architecture, puis publie un rapport structuré directement sur l'issue — le tout sans intervention de l'utilisateur.
2-layer parallel agent hierarchy. Layer 1 deploys 3-50+ agents, each with independent context. Layer 2 adds 2+ sub-agents per member. No upper limit on either layer.
Deep expertise in Hermes Agent architecture, implementation patterns, and extension development
Manus-style context engineering for Agent Teams. Coordinate multiple Claude Code instances with shared planning files. Use when complex tasks need parallel work (code review, debugging, feature development). Requires CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1.
6 pharmaceutical research skills. Trigger: drug discovery, pharmacology, clinical trial design, regulatory filing. Design: end-to-end pipeline from target identification to clinical trials.
Run team-based orchestration for agent squads using work items, ownership, agent Kanban, merge gates, and control pane handoffs.
AI-powered SVG article illustration generator supporting three output modes: dynamic SVG, static SVG, and PNG export. Use this skill when users need to generate illustrations for articles, create SVG graphics, convert SVG to PNG, or mention "article illustration generation" or "create illustrations".
This skill should be used when the user asks to "implement a feature in an isolated worktree", "create a worktree from the current project branch", "open a PR from worktree changes", "merge feature PRs into main", "run multiple agents in parallel worktrees", or "handle worktree merge conflicts and incompatibilities".
Launch an intelligent sub-agent with automatic model selection based on task complexity, specialized agent matching, Zero-shot CoT reasoning, and mandatory self-critique verification
Evaluate solutions through multi-round debate between independent judges until consensus