TaskMaster - AI Cost Optimizer

Project manager and task delegation system. Use when you need to break down complex work into smaller tasks, assign appropriate AI models based on complexity, spawn sub-agents for parallel execution, track progress, and manage token budgets. Ideal for research projects, multi-step workflows, or when you want to delegate routine tasks to cheaper models while handling complex coordination yourself.

This skill appears internally coherent and implements what it claims: model triage, sub-agent spawn command generation, and local token-cost tracking. Before installing or running it, consider: 1) Integration is partially manual/stubbed — execute_task prints spawn commands rather than automatically calling sessions_spawn, and track_session_cost is not fully implemented; expect to supply platform session calls or finish integration. 2) Cost/log file (taskmaster-costs.json) will be created/updated locally and may contain task descriptions, token counts, or outputs — treat that as potentially sensitive and store it securely or audit what gets written. 3) The spawn command uses cleanup: "keep" (retains session artifacts); decide whether you want sessions retained. 4) The skill references Anthropic model names — using it will incur model/billing costs when you actually spawn sessions. 5) Because the skill can generate and suggest automated sub-agent work, review and control actual execution (sessions_spawn/session_status) on your OpenClaw instance to avoid unintended automated runs. If you want higher assurance, review the full delegate_task.py and openclaw_integration.py to confirm there are no hidden network calls or logging of full task outputs to external endpoints.

Type: OpenClaw Skill Name: taskmaster Version: 1.0.0 The OpenClaw AgentSkills skill bundle 'taskmaster' is classified as benign. The core script `scripts/delegate_task.py` is designed for intelligent task delegation, model selection, and budget management, which involves generating `sessions_spawn` commands for OpenClaw sub-agents. This is a legitimate use of OpenClaw primitives for orchestrating AI tasks. File I/O is limited to a local `taskmaster-costs.json` for logging, and there is no evidence of data exfiltration, malicious execution, persistence, or prompt injection against the analyzing agent. The documentation and code align with the stated purpose of cost-optimized AI task management.