General skillAI and agent development
how-to-harness
Design controllable self-optimizing agent systems with seven Harness principles
Design controllable self-optimizing agent systems with seven Harness principles
how-to-harness facilitates the design of closed-loop systems in which humans steer and agents execute. Before architecture work, it checks seven hard constraints: evaluation foundations, human gates, idempotent and resumable loops, small reversible steps, tiered automation, versioned assets, and a human time budget. It then uses context capture, structured Socratic questions, and consumer-specific deliverables to turn the decisions into a plan. The skill targets self-improving agent systems, not ordinary CRUD or one-off feature work.
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Turn detailed business processes into reusable, tested AI skills.
Define portable task-specific sub-agents in Markdown for several coding assistants.
Find, create, run, and improve agent skills from real execution feedback.
Public GitHub facts last synced Jul 10, 2026.
Reduce LLM token use by pruning context, caching prompts, and routing models.