Plan work across several AI agents by defining task owners, deliverables, dependencies, and acceptance criteria. Choose a finite workflow or repeated improvement cycles, then review results before allowing dependent tasks to proceed.
Use when a Leader must choose Project Work boundaries, owners, dependency shape, DAG vs Loop, acceptance criteria, or follow-up strategy. Do not use for Quick Task execution after the mode is already selected.
Review the instructions the agent will receive before you install.
Use this skill when acting as Leader to coordinate several members.
Break work into bounded tasks, assign one owner per task, keep dependencies visible, and avoid asking multiple workers to silently own the same result.
Report accepted outcomes, not every intermediate worker message.
You are the Team Leader. Design context boundaries, task ownership, dependency shape, and acceptance criteria. Do not act as a message router that simply forwards the requester's raw message to Workers.
Before delegation, clarify:
If the goal, acceptance standard, ownership, or safe next step is ambiguous, ask the requester before dispatching work.
TeamHarness Project Work supports DAG and Loop execution modes.
Choose DAG when the work is finite and the dependency graph can be planned now.
DAG fits:
Choose Loop when the work repeats until a stop condition, quality gate, evidence threshold, or maximum iteration count is reached.
Loop fits:
Do not pre-expand repeated Loop rounds into a large DAG. Plan the current iteration, evaluate it, then decide whether to continue, replan, ask the requester, stop successfully, or stop blocked.
A good task has:
shared/tasks/{task-id}/Do not assign multiple Workers to write the same file, directory, final answer, or decision record.
A Worker completion is not automatic project progress. After check_task, decide
whether to:
completedOnly accepted results should unblock downstream dependencies.
Do not:
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Find worker agents in Nacos that match a task, recommend candidates, and import the administrator's chosen worker. It also supports importing a specified nacos package URI, with worker name confirmation and direct reporting of installation failures.
Prepare an existing OpenClaw setup for import as an AgentTeams managed Worker. Analyze tool dependencies, adapt role instructions and scheduled jobs, and build a ZIP package containing the configuration and custom image requirements.
Manage communication channels by identifying senders, maintaining trusted contacts, and setting the administrator's primary notification destination. It also covers first contact on a new channel and contacting the administrator across channels, with rules for handling unknown senders.
Prepare coding tasks for delegation to an authorized agent’s AI command-line tool. Set up and synchronize the workspace, write precise change requests, then review returned changes and run relevant checks before reporting completion.
Run AI coding command-line tools on behalf of worker agents using their prepared prompts and workspaces. Detect available tools, configure delegation, return results, and apply supported execution controls such as time budgets and permission settings.
Guides communication in Matrix agent teams by choosing recipients, rooms, and when to mention someone. It covers task notifications and progress reports, helping agents avoid duplicate assignments and send concrete updates to the appropriate requester.