The OpenAugi plugin transforms voice transcripts into a structured and self-organizing knowledge system using AI-powered workflows. By parsing voice notes or any freeform text, it breaks content down into atomic notes, extracts tasks, and generates summaries with contextual links. Users can also distill groups of linked notes into concise insights, making it ideal for synthesizing research or complex projects. With support for custom processing instructions, it offers flexibility in how information is extracted and organized. This plugin is especially useful for those who think out loud, prefer voice capture, or want to automate second-brain workflows using OpenAI models.
Release Notes: Unified Context Gathering System + OpenAI Model Selection
This release introduces a powerful Unified Context Gathering System that transforms how OpenAugi discovers, reviews, and processes your notes, plus flexible OpenAI model selection for all AI operations.
✨ New Features
🧠 Unified Context Gathering System
One flexible system, multiple outputs - Instead of separate rigid workflows, you now have a three-stage pipeline that gives you complete control:
- Configure - Choose source (linked notes or recent activity), depth, filters
- Review - See discovered notes in checkbox list, toggle individual notes on/off
- Process - Choose to distill into atomic notes OR publish as a single blog post
New Commands
OpenAugi: Process Notes- Process curated sets of linked notes with link traversal up to 3 levels deepOpenAugi: Process Recent Activity- Weekly reviews and activity summaries with time-based discoveryOpenAugi: Save Context- Gather research without AI processing, create reference documents
Key Capabilities
- 🔗 Link Depth Traversal: Breadth-first search up to 3 levels deep (was limited to 1)
- 📋 Checkbox Review: Preview ALL discovered notes before processing, toggle individual notes
- 📊 Smart Filtering: Character limits (default 100k), folder exclusions, journal section filtering
- 📝 Dual Output Modes:
- Distill: Atomic notes + summary (existing behavior enhanced)
- Publish: Single polished blog post ready for sharing (NEW!)
- 💾 Raw Context Saving: Skip AI processing, just aggregate content
🤖 OpenAI Model Selection
Flexible model configuration for all AI operations:
- Preset Models: Choose from
gpt-5,gpt-5-mini,gpt-5-nano(default:gpt-5) - Custom Override: Specify any OpenAI model name (e.g.,
gpt-4o-2024-11-20) - Settings Integration: Configure in Settings → OpenAugi → OpenAI Model
- No Hardcoded Models: All model references now come from configuration
🚀 Publishing System (NEW!)
Transform your notes into polished, shareable content:
- Single Blog Post Output: Conversational tone preserving your voice
- Markdown Formatting: Headers, emphasis, short paragraphs
- Frontmatter Metadata: Type, date, prompt used, source notes
- Custom Prompts: Use different "lenses" for focused processing
- Ready to Share: Copy-paste directly to blog, Discord, forums
Example Output:
---
type: published-post
published_date: 2025-10-13T14:30:00Z
prompt_used: default
status: draft
source_notes: [[Note 1]], [[Note 2]]
---
# Building a Second Brain That Actually Works
[Polished blog post content ready for publishing]
🔧 Enhanced Settings
Context Gathering Settings
- Default Link Depth: 1-3 levels (was fixed at 1)
- Default Max Characters: 100,000 (prevents token overflow)
- Filter Recent Sections by Default: Journal section filtering toggle
OpenAI Settings
- Model Selection: Dropdown with preset options
- Custom Model Override: Text input for any model name
- Published Folder: Where blog posts are saved (
OpenAugi/Published)
🐛 Bug Fixes
- Journal Section Filtering: Fixed issue where date headers with additional text (e.g.,
### 2025-10-13 - new) weren't being recognized and filtered properly
🔄 Backwards Compatibility
Zero breaking changes! All existing commands still work:
- Legacy commands marked appropriately in documentation
- Existing file structures unchanged
- Settings migration handled automatically
- Old workflows continue to function