Git
v1.0.0

team-topology

by @Cotal-AI0 pulls
URLopenbooklet.com/s/team-topology
Pinnedopenbooklet.com/s/[email protected]
APIGET /api/v1/skills/team-topology

Define a multi-agent team for ANY task on ANY system as an explicit deployment topology - pick the shape from the task's dominant risk, specify the runtime/communication/trust layers, place model capability by lane, present it as a diagram + table + trust-boundary note + open choices, and deploy ONLY after the user agrees to the proposed shape. Use when the user asks to "define/design/lay out the team", "what topology are we deploying", "how should the agents be arranged", "design the team for <task>", "what formation for <task>", or wants a team expressed as a topology (nodes, edges, models, trust boundaries) rather than spawned ad hoc. Substrate-agnostic - Cotal mesh, harness subagents, Workflow stages, containers, or any orchestration system.

4 skills from this repoCotal-AI/Cotal
team-topologyviewing
cold-review.claude/skills/cold-review/SKILL.md

Write the brief for a single independent cold reviewer and grade what it returns, keeping it isolated from the panel that already graded the change. Read by whoever AUTHORS the brief; the graded seat never loads this file. Covers what the seat is given, what its verdict binds, who may override it, and how the rules degrade when the vendor set is short. Use when a panel has reached consensus and you want a second opinion consensus cannot anchor, when a change is security-sensitive or hard to reverse, or when you are the author and therefore the worst available reader of your own work.

cotal-meshskills/cotal-mesh/SKILL.md

Put an AI agent on a Cotal mesh and coordinate with other agents across vendors and machines. Use when a user runs two or more agents that must hand work to each other, share a durable record, or spawn teammates; covers install, starting a local mesh, joining, messaging peers, and using the cotal.ai site API and MCP server for feedback, the Cotal Cloud waitlist, and the build log.

parallel-feature-managers.claude/skills/parallel-feature-managers/SKILL.md

Run several independent Cotal features concurrently by creating one Git worktree and one spawn-capable mesh manager per feature; each manager staffs a review panel in a dedicated channel, adds one independent cold reviewer briefed under the cold-review skill, owns plan-to-commit delivery, and escalates unresolved product decisions by DM to the coordinator for relay to the user. Use when the user asks to split multiple features across managers/worktrees, run parallel feature teams on Cotal, or have managers create their own review panels.

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