Results for “agent-teams”

Interactive agent picker for composing and dispatching parallel teams

Interactive agent picker for composing and dispatching parallel teams

Use when work requires inter-agent communication, cross-layer coordination, or configurable autonomy with Claude Code Agent Teams

Interactive agent picker for composing and dispatching parallel teams

Interactive agent picker for composing and dispatching parallel teams

Unified Agent Teams orchestrator for Diverga v12.0.0. Manages Agent Teams creation, VS Arena debate, and subagent dispatch. Single entry point for all parallel/debate workflows. Replaces research-orchestrator and vs-arena skills. Triggers: orchestrator, agent team, create team, parallel agents, debate, competing, collaborate, VS Arena

Designs collaborative AI agent teams with CrewAI, covering agent roles, task definitions, crew orchestration, and process types.

Designs collaborative AI agent teams with CrewAI, covering agent personas, task definitions, crew orchestration, and process types.

Decompose a task into parallel workstreams, assign agent ownership, run integration at dependency boundaries, and synthesize results.

Creates agent company packages conforming to the Agent Companies specification, either from scratch or by wrapping an existing repository.

Designs collaborative AI agent teams with CrewAI, covering agent roles, task decomposition, crew orchestration, process types, memory, and flows.

Defines the architecture and orchestration primitives for multi-agent teams, covering role allocation, conflict resolution, reward routing, and the operational lifecycle of agent collectives.

Browse available agent personas and compose ad-hoc teams of up to 5 agents to work in parallel on a task, then synthesize their results.

Agent skill for agent - invoke with $agent-agent

Designs collaborative AI agent teams using CrewAI, covering agent roles, task definitions, crew orchestration, process types, memory, and flows.

Designs and orchestrates multi-agent AI teams using the CrewAI framework, covering agent roles, task decomposition, crew processes, memory, and flows.

Defines an inter-agent communication protocol for C-suite agent teams, including invocation syntax, loop prevention, isolation rules, and response formats to coordinate cross-functional analysis and board meetings.

Main agent orchestrator that coordinates a specialized squad of agents

Designs or reviews Agentforce agent actions, covering Flow, Apex invocable, and prompt-template actions, including naming, input/output contracts, confirmation, and error behavior.

Multi-agent collaboration plugin that spawns N parallel subagents competing on the same task via git worktree isolation. Agents work independently, results are evaluated by metric or LLM judge, and the best branch is merged. Use when: user wants multiple approaches tried in parallel — code optimization, content variation, research exploration, or any task that benefits from parallel competition. Requires: a git repo.

Agent skill for challenges - invoke with $agent-challenges

Expert en tests d'agents IA (tests unitaires, intégration, régression, guardrails, red teaming agents)

Design reproducible evaluations for AI agents with representative task sets, explicit rubrics, appropriate graders, baselines, regression gates, and failure analysis. Use when defining agent quality, comparing prompts or models, validating a release, measuring tool-use reliability, investigating regressions, or deciding whether an agent is ready for production.

Simulator.Company digital-twin & actor-agent specialist — talk to an agent AS an agent and delegate work to it. An agent is ANY actor whose `description` holds an "# Agent" competency profile (what it does, what it knows, whether it fits a task). The common case is a person: every workspace user has a 1:1 twin actor (`systemObjType="user"`) carrying that profile. But any actor can be an agent — a service/bot twin, a team or department, an organization, a process. This skill discovers the agent (`findAgent`), loads its profile (`getAgent`), adopts it as the persona, then either does the task, finds a better-suited agent, or hands the decision to the user (for a person: a task or a p2p message; for a non-person: propose another executor or run/trigger it as an actor). It is the actor-analog of `simulator-skills` (the `Skills`-form registry), but the registry is the workspace's agent actors. Use when the user wants to "delegate", "assign this to <someone/something>", "can <X> do this", "who/what should do this",

Inter-agent communication protocol for C-suite agent teams. Defines invocation syntax, loop prevention, isolation rules, and response formats. Use when C-suite agents need to query each other, coordinate cross-functional analysis, or run board meetings with multiple agent roles.

Design and build hosted agent infrastructure with sandboxed execution, warm pools, session persistence, and multiplayer collaboration.

Multi-agent collaboration plugin that spawns N parallel subagents competing on the same task via git worktree isolation. Agents work independently, results are evaluated by metric or LLM judge, and the best branch is merged. Use when: user wants multiple approaches tried in parallel — code optimization, content variation, research exploration, or any task that benefits from parallel competition. Requires: a git repo.

Decision-theoretic framework for agents embedded within the environments they model and act upon

Designs collaborative AI agent teams with CrewAI, covering agent roles, task definitions, crew orchestration, process types, memory, tools, and flows.

Multi-agent collaboration plugin that spawns N parallel subagents competing on the same task via git worktree isolation. Agents work independently, results are evaluated by metric or LLM judge, and the best branch is merged. Use when: user wants multiple approaches tried in parallel — code optimization, content variation, research exploration, or any task that benefits from parallel competition. Requires: a git repo.