Results for “team”

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

AI Safety Specialist IA — Expert en sécurité IA (alignment, guardrails, filtrage de contenu, test de biais, red teaming)

Turn a work-items.md file (produced by /plan-work-items) into Linear issues, one per slice, in a single target Linear team. Use when you want to publish work items as Linear issues, create implementation tickets to track in Linear, or push a broken-down plan into a Linear team. Requires a configured Linear MCP server and a target team. Reads the team's real workflow states, labels, Projects, and members and resolves every option against them before creating anything; defaults each issue to the team's initial state, unassigned, uncategorized, with no parent or Project unless you ask. Links within-file `Depends on` relationships as native Linear "blocked by" relations and annotates the source file so re-runs resume cleanly. Does not produce the work-items file itself — use plan-work-items first. Does not post to Jira — use work-items-to-jira. Does not post to GitHub — use work-items-to-issues.

Manage issues, projects, and team workflows in Linear via the Linear MCP server. Create, update, organize, and track work without leaving the terminal.

Maintain canonical AGENTS.md (open spec). Trigger: 'agents.md', 'update AGENTS.md', or auto-fired by ijfw-team after agent generation.

Expert in CrewAI - the leading role-based multi-agent framework used by 60% of Fortune 500 companies. Covers agent design with roles and goals, task definition, crew orchestration, process types (sequential, hierarchical, parallel), memory systems, and flows for complex workflows. Essential for building collaborative AI agent teams. Use when: crewai, multi-agent team, agent roles, crew of agents, role-based agents.

Expert in CrewAI - the leading role-based multi-agent framework used by 60% of Fortune 500 companies. Covers agent design with roles and goals, task definition, crew orchestration, process types (sequential, hierarchical, parallel), memory systems, and flows for complex workflows. Essential for building collaborative AI agent teams. Use when: crewai, multi-agent team, agent roles, crew of agents, role-based agents.

Expert in CrewAI - the leading role-based multi-agent framework used by 60% of Fortune 500 companies. Covers agent design with roles and goals, task definition, crew orchestration, process types (sequential, hierarchical, parallel), memory systems, and flows for complex workflows. Essential for building collaborative AI agent teams. Use when: crewai, multi-agent team, agent roles, crew of agents, role-based agents.

Expert in CrewAI - the leading role-based multi-agent framework used by 60% of Fortune 500 companies. Covers agent design with roles and goals, task definition, crew orchestration, process types (sequential, hierarchical, parallel), memory systems, and flows for complex workflows. Essential for building collaborative AI agent teams. Use when: crewai, multi-agent team, agent roles, crew of agents, role-based agents.

Bypasses safety filters on API-served LLMs using jailbreak templates, input obfuscation, and multi-model racing.

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.

Developer Experience specialist. Improves tooling, setup, and workflows. Use PROACTIVELY when setting up new projects, after team feedback, or when development friction is noticed.

Use when facing multiple implementation tasks that could benefit from parallelization or when deciding between solo, parallel agent, sequential subagent, or agent team approaches

Orchestrating multi-session parallel execution via Claude Code Agent Teams API and Codex CLI Subagents — launch, manage, coordinate concurrent tasks. Use when parallel work is needed.

Map a current event below the surface into patterns, structures, and mental models. Use when a class or team needs systemic understanding before action.

Orchestrate teams of agents — DAG execution, routing, state sharing, failure recovery. Use when coordinating parallel agents in task pipelines with dependencies or distributing work by capability.

Diverga v12.0 setup wizard. 4-step researcher profile setup. Captures discipline, experience, tools, database access, and Agent Teams + VS Arena preference. Triggers: setup, configure, 설정, install

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

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

Orchestrating specialist AI agent teams as a meta-coordinator: decomposes requests into minimum viable chains, spawns each as an independent session, drives to final output. For multi-domain tasks.

Expert in CrewAI - the leading role-based multi-agent framework used by 60% of Fortune 500 companies. Covers agent design with roles and goals, task definition, crew orchestration, process types (sequential, hierarchical, parallel), memory systems, and flows for complex workflows. Essential for building collaborative AI agent teams. Use when "crewai, multi-agent team, agent roles, crew of agents, role-based agents, collaborative agents, crewai, multi-agent, agents, orchestration, roles, collaborative-ai" mentioned.

Probe RAG applications for prompt injection via poisoned retrieved context and embedding manipulation.

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.

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

Guides a conversation to design a new AI team member, generating agent identity files and optionally setting up performance reviews.

Design a lead routing and SLA model someone can actually implement. The assignment rules, the round-robin or account-based logic, the SLA timers, and the fallbacks when a rep is out or a lead has no owner. Built for B2B RevOps teams, customizable to your CRM and your team shape. Trigger on "design lead routing", "who should get this lead", "build our SLA", "round robin rules", "leads are falling through", or any routing diagnostic.

Build teams of autonomous AI agents that collaborate to solve complex tasks using role-based delegation, memory, and sequential or hierarchical execution.

Orchestrates multi-agent teams using the ClawTeam CLI, enabling task management, inter-agent messaging, git context integration, runtime profiles, and monitoring dashboards.

Produce displace/team/ghost talk tracks for the incumbent on a recompete pursuit. Use when user wants competitive angles saved to the pursuit vault; optional multi-turn LLM for customer-facing phrasing.

Design authentication and authorization strategy for a product or MVP. Use when the team needs sign-in methods, session model, user/workspace membership, roles, tenant boundaries, invitation flows, or permission enforcement plans.

Creates a declarative agent for Microsoft 365 Copilot by integrating an MCP server with authentication, tool selection, and configuration.

Control Claude Code via MCP protocol. Trigger with "plan" to write a precise execution plan then feed it to Claude Code. Also supports direct commands, persistent sessions, agent teams, and advanced tool control.

Orchestrates teams of specialized AI agents with role-based collaboration, memory, and sequential or hierarchical execution for complex multi-step tasks.

Backtests quantitative trading strategies across 9 engines and 25 data sources, analyzes trade journals, and runs multi-agent research teams.