64fd1bb85d
This commit introduces a dedicated AI assistant prompt for documentation tasks, located at `ai/rsyslog_doc_assistant/base_prompt.txt`. This prompt standardizes the creation and maintenance of Sphinx-RST documentation, enforcing best practices for AI ingestion such as metadata blocks, summary slices, and consistent anchors. Modifications: - Created `ai/rsyslog_doc_assistant/base_prompt.txt` with specific roles, objectives, and workflow checklists for the rsyslog-doc agent. - Updated the root `AGENTS.md` to include a reference to this new prompt in the "Quick links for agents" section. - Created `doc/ai/AGENTS.md` to serve as a guide for agents working within the `doc/` subtree, explicitly linking to the new prompt and reinforcing the requirements for metadata and structure defined in `doc/ai/authoring_guidelines.md`. These changes ensure that future documentation updates by AI agents will be consistent, technically accurate, and optimized for both human readers and RAG systems. With the help of AI-Agents: Jules
AI and Machine Learning Tooling for rsyslog
This directory contains AI and Machine Learning (ML) tools that
Purpose
The ai directory is designated for a new generation of tooling that will
interface with rsyslog. It will house external AI and ML models and
applications. This approach ensures the rsyslog core remains lean and
robust while allowing for flexible and powerful extensions.
Current Status
No tools exist yet.
This directory and its README.md have been created to provide a
consistent and official location for this work as it progresses.
Active development is ongoing, and tools will be added here once they
reach a stable state.
Vision
Future tools in this directory will leverage artificial intelligence and machine learning for tasks like advanced log analysis, anomaly detection, and intelligent system monitoring. The goal is to enhance rsyslog's capabilities without integrating complex models directly into the core daemon.