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FridayOS1.0
Markdown knowledge blueprint with an offline setup tool
Organize local knowledge with six Markdown areas: inbox, execution, wiki, skills, evidence and system rules. Includes an Obsidian example vault, offline Python setup tool, bilingual guides and 11 practice prompts. Free, MIT licensed. AI integration requires separate configuration.
I'm Owen, a participant building FridayOS with Robinson AI Lab. We made a reusable starting structure for local knowledge work: keep evidence, interpretations, active tasks and reusable methods separate, then connect them with references.
The public release contains Markdown templates, an Obsidian example using a fictional company, and an offline deployment tool (Python 3.9+, verified on Windows). Start with the repository's bilingual deployment guide.
This is a blueprint and toolkit; the complete Agent OS is a longer-term direction. AI connections need separate setup, and automatic backup or vault migration is not included.
Feedback welcome: are the six areas and first-use steps clear enough?
Writing assistance: OpenAI Codex, based on the public documentation.
About FridayOS1.0 on Product Hunt
“Markdown knowledge blueprint with an offline setup tool”
FridayOS1.0 was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #239 on the daily leaderboard. Organize local knowledge with six Markdown areas: inbox, execution, wiki, skills, evidence and system rules. Includes an Obsidian example vault, offline Python setup tool, bilingual guides and 11 practice prompts. Free, MIT licensed. AI integration requires separate configuration.
On the analytics side, FridayOS1.0 competes within Productivity, Notes, Developer Tools and GitHub — topics that collectively have 1.2M followers on Product Hunt. The dashboard above tracks how FridayOS1.0 performed against the three products that launched closest to it on the same day.
Who hunted FridayOS1.0?
FridayOS1.0 was hunted by Owen Teng. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of FridayOS1.0 including community comment highlights and product details, visit the product overview.
Owen Teng
I'm Owen, a participant building FridayOS with Robinson AI Lab. We made a reusable starting structure for local knowledge work: keep evidence, interpretations, active tasks and reusable methods separate, then connect them with references.
The public release contains Markdown templates, an Obsidian example using a fictional company, and an offline deployment tool (Python 3.9+, verified on Windows). Start with the repository's bilingual deployment guide.
This is a blueprint and toolkit; the complete Agent OS is a longer-term direction. AI connections need separate setup, and automatic backup or vault migration is not included.
Feedback welcome: are the six areas and first-use steps clear enough?
Writing assistance: OpenAI Codex, based on the public documentation.