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espressoplease
smalldocs
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espressoplease / smalldocs

smalldocs

Read, style, and share markdown files - privately. Formerly SDocs.

2Distinct people
15Mentions
0Explicit recommenders
233GitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Read, style, and share markdown files - privately. Formerly SDocs.

GitHub

Where it is used

No documented product use was verified in the last source check.

What people are saying

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No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

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This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 5:04:57 PM UTC.

Claude Whiteboards, Claude Sheets, and Claude Data direct repository linkDebated

The discussion centers on whether Anthropic's launch of Whiteboards, Sheets, and Data represents a strategic move to become a comprehensive SaaS suite or a futile attempt to compete with entrenched incumbents like Microsoft and Google. Participants are sharply divided between those who see these tools as a viable path to vendor lock-in and ecosystem dominance, and those who view them as overly simplified artifacts that will fail to replace professional-grade software.

217 readable replies · Supporting reply 1 · Supporting reply 2 · Supporting reply 3 · Supporting reply 4

Mentions over time

HN mentions by week15 dated mentions

Observed mentions: 2026-07-06 19:01:02 UTC to 2026-10-30 10:00:56 UTC. Weeks start Monday, UTC.

0123452026-07-06 00:00:00 UTC to 2026-07-13 00:00:00 UTC (exclusive): 5 mentions; 0 submissions, 5 commentsJul 62026-07-13 00:00:00 UTC to 2026-07-20 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2026-07-20 00:00:00 UTC to 2026-07-27 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2026-07-27 00:00:00 UTC to 2026-08-03 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-08-03 00:00:00 UTC to 2026-08-10 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2026-08-10 00:00:00 UTC to 2026-08-17 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-08-17 00:00:00 UTC to 2026-08-24 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2026-08-24 00:00:00 UTC to 2026-08-31 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-08-31 00:00:00 UTC to 2026-09-07 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 commentsAug 312026-09-07 00:00:00 UTC to 2026-09-14 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2026-09-14 00:00:00 UTC to 2026-09-21 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-09-21 00:00:00 UTC to 2026-09-28 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-09-28 00:00:00 UTC to 2026-10-05 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-10-05 00:00:00 UTC to 2026-10-12 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-10-12 00:00:00 UTC to 2026-10-19 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-10-19 00:00:00 UTC to 2026-10-26 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-10-26 00:00:00 UTC to 2026-11-02 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsOct 26

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
Jul 62026-07-06 00:00:00 UTC2026-07-13 00:00:00 UTC505
Jul 132026-07-13 00:00:00 UTC2026-07-20 00:00:00 UTC101
Jul 202026-07-20 00:00:00 UTC2026-07-27 00:00:00 UTC101
Jul 272026-07-27 00:00:00 UTC2026-08-03 00:00:00 UTC000
Aug 32026-08-03 00:00:00 UTC2026-08-10 00:00:00 UTC202
Aug 102026-08-10 00:00:00 UTC2026-08-17 00:00:00 UTC000
Aug 172026-08-17 00:00:00 UTC2026-08-24 00:00:00 UTC202
Aug 242026-08-24 00:00:00 UTC2026-08-31 00:00:00 UTC000
Aug 312026-08-31 00:00:00 UTC2026-09-07 00:00:00 UTC202
Sep 72026-09-07 00:00:00 UTC2026-09-14 00:00:00 UTC101
Sep 142026-09-14 00:00:00 UTC2026-09-21 00:00:00 UTC000
Sep 212026-09-21 00:00:00 UTC2026-09-28 00:00:00 UTC000
Sep 282026-09-28 00:00:00 UTC2026-10-05 00:00:00 UTC000
Oct 52026-10-05 00:00:00 UTC2026-10-12 00:00:00 UTC000
Oct 122026-10-12 00:00:00 UTC2026-10-19 00:00:00 UTC000
Oct 192026-10-19 00:00:00 UTC2026-10-26 00:00:00 UTC000
Oct 262026-10-26 00:00:00 UTC2026-11-02 00:00:00 UTC101

What Hacker News says

15 sources
I went through a period of feeling very tired. For me two things helped: 1. Being okay with being "less" productive. I'm probably still 10x more productive than I was in the pre-AI era, but in the early days of AI I would have eight Claude sessions running. Now it's two or three and I take more advantage of the free time I have between Claude assignments. My bosses are still happy with my output and I'm not being burnt out. 2. Very personal, but building my own tooling really helped. I built https://smalldocs.org / https://github.com/espressoplease/smalldocs (a document creator for AI agents) which allows me to take a lot of work outside of a chat history. E.g. I might make 10 MRs and then say "smalldoc me a list of the MRs" and I have that in my library, or if I'm considering various architectures I'll ask "smalldoc me a simple overview
Read the rest
of the three architectures with mermaid diagrams" and then I can review the agent's thinking in a cleaner way.
In Ask HN: Are you tired too in this AI era?
Because it's hard to find the time to read an academic paper I had an agent summarise it in a few slides: https://smalldocs.org/s/6kEgfy54oclH4KR9HX847w#k=ywVL86PcTCo... It's an interesting result (agents develop biases in their context) which reflects a lot of my experience working with agent, where I observe a lot of, what I kind of call, "context nudging" - where a droplet of an idea in an agent's context pushes its direction/output significantly. When it happens to me it always makes me question the type of intelligence LLMs provide. [I am the developer behind SmallDocs. Source: https://github.com/espressoplease/smalldocs]
In Large language models develop novel social biases through adaptive exploration
(I made a similar comment in a different post by Simon Willison yesterday about GPT Work) I am unsure the direction that AI assisted document creation work will go in. I am opinionated and building something in the space. In this reply I discuss my view + what I have been building. My opinion is: We now have AI, this new amazing flexible tool. We can throw it at any problem. But in terms of document creation we have a choice between old fashioned siloed document formats (.pptx, .pdf, .xlsx, .docx, etc.) and a freshly rendered - slightly randomly styled - html site with some basic javascript within it. I think these combinations are odd and do not maximise the powers of AI. I've been building something called SmallDocs [0][1] which is a new take on work documents. It's all Markdown, but it always renders (100% privately) on the SmallDocs s
Read the rest
ite. This means the SmallDocs renderer can convert recognised Markdown combinations into powerful traditional document formats [2]. For example, we convert a ```cells block into an in-line spreadsheet you can export to Excel. This gives an agent the ability to express itself with a great deal of depth and flexibility. For example, your agent can produce a single data analysis "SmallDoc" with text, charts, spreadsheets, etc. [3] I find that combining formats quickens the speed I can understand a topic. SmallDocs also have standardised and pretty boring styling. This means you spend less time understanding the layout of a flashy HTML page and more time on the content. I also believe a pre-determined rendering engine has a lot of advantages over a freslhy built HTML artifact. It allows you to build in lot's of useful defaults that the agent doesn't have to code from scratch. These can be small things, for example, every time your agent renders a Markdown table in SmallDocs you can instantly copy it as a CSV or a PNG. And these can be bigger things, such as a rich slides DSL with solid styling defaults, which saves your agents a lot of tokens and results in consistently attractive HTML slides [4]. (Slides can also be automatically exported to .pdf and .pptx.) I've been at it for a few months, and am still working on the project. I am looking for feedback and open source collaborators. Thanks for reading! [0] https://smalldocs.org [1] https://github.com/espressoplease/smalldocs [2] https://smalldocs.org/blogs/what-is-a-smalldoc [3] https://smalldocs.org/s/46fWiAyF77T9c7tqYwAQqp#k=j78ZEOOrgo8... [4] https://smalldocs.org/s/QrmeWMsULGS871nXQYOacB#k=ubOHH9QtTWp... (And something totally different, your agent can also use SmallDocs to walk you through code files: https://smalldocs.org/s/JsI_-tWSH0UpSd_YXxVLPm#k=G5jLCYA4JUX...)
In The ChatGPT/Codex app bundles a full copy of LibreOffice
I am unsure the direction that AI assisted work will go in. I am opinionated and building something in the space. In this reply I discuss my view + what I have been building. My opinion is: We now have AI, this new amazing flexible tool. We can throw it at any problem. But in terms of document creation we have a choice between old fashioned siloed document formats (.pptx, .pdf, .xlsx, .docx, etc.) and a freshly rendered - slightly randomly styled - html site with some basic javascript within it. I think these combinations are odd and do not maximise the powers of AI. I've been building something called SmallDocs [0][1] which is a new take on work documents. It's all Markdown, but it always renders (100% privately) on the SmallDocs site. This means the SmallDocs renderer can convert recognised Markdown combinations into powerful traditiona
Read the rest
l document formats [2]. For example, we convert a ```cells block into an in-line spreadsheet you can export to Excel. This gives an agent the ability to express itself with a great deal of depth and flexibility. For example, your agent can produce a single data analysis "SmallDoc" with text, charts, spreadsheets, etc. [3] I find that combining formats quickens the speed I can understand a topic. I also believe a pre-determined rendering engine has a lot of advantages over a freslhy built HTML artifact. It allows you to build in lot's of useful defaults that the agent doesn't have to code from scratch. These can be small things, for example, every time your agent renders a Markdown table in SmallDocs you can instantly copy it as a CSV or a PNG. And these can be bigger things, such as a rich slides DSL with solid styling defaults, which saves your agents a lot of tokens and results in consistently attractive HTML slides [4]. (Slides can also be automatically exported to .pdf and .pptx.) I've been at it for a few months, and am still working on the project. I am looking for feedback and open source collaborators. Thanks for reading! [0] https://smalldocs.org [1] https://github.com/espressoplease/smalldocs [2] https://smalldocs.org/blogs/what-is-a-smalldoc [3] https://smalldocs.org/s/46fWiAyF77T9c7tqYwAQqp#k=j78ZEOOrgo8... [4] https://smalldocs.org/s/QrmeWMsULGS871nXQYOacB#k=ubOHH9QtTWp... (And something totally different, your agent can also use SmallDocs to walk you through code files: https://smalldocs.org/s/JsI_-tWSH0UpSd_YXxVLPm#k=G5jLCYA4JUX...)
In Understanding ChatGPT Work
You might find my open source project SmallDocs useful. It lets Claude make presentations in Markdown which can be exported to PPT. You can define styles and make them defaults. (You can also share the native SmallDoc presentations by just sending a url.) Homepage: https://smalldocs.org/ Example presentations: https://smalldocs.org/s/mTBw58ut_eTAIlGkYePw6-#k=4MotlKf-sLc... https://smalldocs.org/s/cGRzzCv7LA9Kd8BxZ4bBAP#k=B7_NNXPbpLw... Code: https://github.com/espressoplease/smalldocs
In What's in a PowerPoint File?
How has traction been so far? And are there any valuable cross team/agent use cases you actually have experienced or are they theoretical? I run https://smalldocs.org, which focuses on making Markdown a highly expressive space for agents (think slides, spreadsheets, charts, mermaid diagrams, etc.). I have built a local library which lives in the browser but reflects your local file system - explainer here: https://smalldocs.org/connect?return=%2Flibrary, demo here: https://smalldocs.org/library?demo=1. Which is pretty useful when you want to find local Markdown files. However I am just about to introduce very similar functionality to yours - a cloud + agent access. Right now I don't know if this will actually be useful, but I think it will likely be something I can charge for. I have a few hundred developers that use SmallDocs on a weekly
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basis (https://smalldocs.org/analytics), but right now it's just a free local-first tool. Code available here: https://github.com/espressoplease/smalldocs
In Show HN: OzBrain, a shared brain for knowledge between agents and your team
I've been working on https://smalldocs.org for some time. It as if "Claude Code & Microsoft Office had a baby". It's actually very useful if you develop with a terminal based coding agent and sometimes want to get out of the terminal view to dig deep into a topic. I have had quite a bit of usage: https://smalldocs.org/analytics, which I'm very proud of, with many developers using it week after week. It's free to use by the way. Code is open source at: https://github.com/espressoplease/smalldocs
In Ask HN: What are you working on? (August 2026)
I empathise with this. I run a little open source project called SmallDocs [1][2] which Claude/Coding Agent invokes to generate easily human readable Markdown documents (and render code files). You can ask Claude to "sdoc me an annotated code walkthrough of this MR" and it will produce something like this: https://smalldocs.org/s/Ju9GOmWZ0JXTtzqCVfgt1q#k=6HBrpcCjIu7... I use this a lot to stay in touch with the code the LLM is producing. [1] https://smalldocs.org [2] https://github.com/espressoplease/smalldocs
In Prevent cognitive debt by manually retyping LLM-generated code
I've been building SmallDocs [1], a fairly fully functional office suite (text, formatting, presentations, spreadsheets) which is based in markdown (and mainly written by agents). Given my experience building this, I think the idea of "a truly independent document": > one that displays identically on any system, in any country, for any user, regardless of the software used Will be very difficult to achieve in practice. Building software is an expression of opinions. And one of the main drivers of building an app is to innovate or improve the user experience vs. what exists today. These things combine to result in new features, and new features breaks the open standard. If I wanted to build a new Excel, I might want to add something to spreadsheets which a basic open source reader cannot, or even Excel itself, might not be able to handle.
Read the rest
With SmallDocs, I built on the standard rendering of markdown, but then added a bunch of properties which traditional markdown renders would ignore. For example, styles front matter: --- styles: fontFamily: Lora baseFontSize: 17 h1: { fontSize: 2.3, fontWeight: 700 } p: { lineHeight: 1.9, marginBottom: 1.2 } ... --- Which means you can create colorful files like: https://smalldocs.org/s/v_CHCaQHdGNVlsQtk6skEY#k=ZajP0oeiW86... And slide blocks like: ~~~slide grid 100 56.25 bg=#0b1220 r 6 9 82 4 text=caption color=#fbbf24 align=left | LAUNCH REVIEW - Q2 2026 r 6 18 84 16 text=title color=#f8fafc align=left | Atlas 2.0 shipped to every customer r 6 37 78 6 text=subtitle color=#94a3b8 align=left | What changed, what it cost, and what we learned l 6 47 24 47 stroke=#fbbf24 strokeWidth=0.2 ~~~ Which means you can generate slides like: https://smalldocs.org/s/EKnIk-YdUBZeDA9yQs97mh#k=Eo-p46k-k6Q... All this means SmallDocs markdown files only render correctly through our rendering engine - but this enables me to add something new to an existing document format. [1] https://smalldocs.com; https://github.com/espressoplease/smalldocs
In How proprietary formats have become Microsoft’s main tool for lock-in
The charts are very nice, and I think the visualisation layer for LLMs is a very interesting problem. I’ve been building https://smalldocs.org for this exact reason. It’s an office suite for AI agents - but my main use case is giving a cli based LLM the canvas to express itself - charts, mermaid diagrams, etc. I’ve extended it a bit further to be a format for all types of work so the agent can embed slides and spreadsheets in a document. Sample document: https://smalldocs.org/blogs/what-is-a-smalldoc Source: https://github.com/espressoplease/smalldocs
In Show HN: Microsoft releases Flint, a visualization language for AI agents
Hey, I'm building something a bit like that - please checkout https://smalldocs.org if you have time. I say it’s as if “Claude Code & Microsoft Office had a baby...” Code available: https://github.com/espressoplease/smalldocs Discord: https://discord.gg/txjATTsDaq Sample document: https://smalldocs.org/blogs/what-is-a-smalldoc Invoked via Claude Code by saying stuff like: “sdoc me the plan for this feature”, or “dig into our logs and sdoc me a report on our latency"
In Show HN: Docx-CLI: agents read/edit Word docs using 1/2 the time and tokens
I went in the opposite direction and built https://smalldocs.org/, which is an office suite AI agents (and humans - including SWEs!) like to use. I say it’s as if “Claude Code & Microsoft Office had a baby...” Code available: https://github.com/espressoplease/smalldocs Discord: https://discord.gg/txjATTsDaq Sample document: https://smalldocs.org/blogs/what-is-a-smalldoc Invoked via Claude Code by saying stuff like: “sdoc me the plan for this feature”, or “dig into our logs and sdoc me a report on our latency”
In OfficeCLI: Office suite for AI agents to read and edit Microsoft Office files

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