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lumina-agentic-mcp

Work on the Python multi-agent pipeline and MCP client in agentic_ai. Use when editing files under agentic_ai/, changing agent orchestration, configuration loading, MCP client connectivity, async execution flow, pipeline startup commands, or cloud deployment wrappers for the Python service.

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SKILL.md
تعليمات المصدر · معاينة للقراءة فقط
name
lumina-agentic-mcp
description
Work on the Python multi-agent pipeline and MCP client in agentic_ai. Use when editing files under agentic_ai/, changing agent orchestration, configuration loading, MCP client connectivity, async execution flow, pipeline startup commands, or cloud deployment wrappers for the Python service.
# Lumina Agentic Mcp ## Overview Use this skill for the Python subsystem under `agentic_ai/`. Keep changes consistent with the existing config-driven, async, multi-agent design rather than turning it into a one-off script. ## Load The Right Reference - Read `references/file-map.md` when you need to locate the pipeline, agent, config, or MCP surface that owns a behavior. - Read `references/commands.md` before finishing so validation and startup commands match the subsystem. ## Preserve The Existing Architecture - Keep pipeline behavior flowing through `core/`, `agents/`, and `mcp_client/` rather than duplicating logic. - Respect async boundaries and existing command entry points in `agentic_ai/__main__.py`. - Keep the MCP server contract explicit when changing tool names, prompt names, or resource URIs. - Preserve configuration-driven behavior through files in `agentic_ai/config/`. ## Validate With What The Repo Actually Supports - Prefer `python -m compileall agentic_ai` for low-friction validation when dependencies or tests are unavailable. - Use targeted CLI smoke checks such as `python -m agentic_ai visualize` or `python -m agentic_ai run --task "..."` only when the environment is ready. - Do not assume `pytest` is runnable just because it appears in `requirements.txt`; verify the test target exists first.
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