SUMMARY AI summary by gpt-5-mini
AgentLoom is a runtime and framework for assembling, running, and operating complex multi‑agent applications from simple YAML and minimal Python glue. It targets developers building supervisor/worker-style multi‑agent workflows who need resumability, observability, runtime safety, and scalable batch execution for long‑running or production-like tasks. Key features: - YAML workflow and worker declarations; generate Python entry scripts or embed via run_app(). - Worker agents exported as callable tools with validated signatures and .batch(task) concurrency. - Two execution modes (structured tool_call and flexible code_act), plus hooks and reusable Skills. - Pre/post processing, retries, caching, progress persistence, and artifact writing. - Per-agent model/context control, multi-endpoint support, prompt customization, and LLM token metrics. - Checkpoint/resume, heartbeat detection, error recovery, sandboxing, path/policy controls, and shell audits. - Observability: structured terminal and file logs, per-step durations, token usage, archived runs, web UI (SSE) and TUI dashboard. - Built-in tools: file, shell, search, code edit, git, local Codex Exec, and LSP/code intelligence.
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| Created on GitHub | 2026-05-04 |
| Last push | 2026-05-09 |
| First seen here | 2026-05-09 |
| Last fetched | 2026-05-09 14:22 |
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