SUMMARY AI summary by gpt-5-mini
Effect Harness Agent is an agent-driven engineering framework for TypeScript/Effect projects — an LLM-native, machine-to-machine protocol (not a human-facing framework). It turns natural-language intent into structured, executable tasks for autonomous LLM agents while enforcing engineering discipline. Who uses it: teams or systems that integrate LLM agents to design, implement, test, and maintain TypeScript/Effect code with predictable governance and cost. Key features: - Intent Gateway routing and execution profiles (@patch/@standard/@learn) - 6‑phase Lifecycle State Machine with human-in-the-loop approval and validation gates - Knowledge Graph (LLM Wiki) and budgeted navigation to avoid context bloat - Contract-first OpenSpec and explore_report outputs before coding - Skills Matrix (specialized agent capabilities) and self-correcting guard hooks - Token-cost model and shortcuts to control cost and prevent runaway searches
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| Created on GitHub | 2026-05-09 |
| Last push | 2026-05-09 |
| First seen here | 2026-05-09 |
| Last fetched | 2026-05-09 18:12 |
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