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linora-u/AgentLoom

Simple, flexible workflow orchestration for multi-agent AI apps, with YAML configuration, runtime safety, observability, and resume support.

Python ⑂ 2 forks GitHub ↗ site ↗
★ 29
stars
70
AI relevance
65
solo dev
0
tool sigs

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.

DETECTED Detected AI stack

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🤝 Agent frameworks (1)
MCP

GitHub Topics

#agent-framework #ai-agent #automation #cicd #code-review #developer-tools #llm #mcp #multi-agent #open-source #orchestration #python #unit-testing #workflow-automation #yaml

Language breakdown (by bytes)

CSS
0.2%
HTML
0.3%
Shell
0.3%
Python
92.5%
Dockerfile
0%
JavaScript
1.4%
Tree-sitter Query
5.3%

Owner

Account
linora-u
Type
User
Followers
1

Dates

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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