alt Hacker NewsLaunch HN: Skillsync (YC W26) – AI chat sessions made portable across agents
Hey HN, we're Nars & Nishant, founders of Skillsync (https://skillsync.com)
Skillsync lets you move your AI chats across every coding agent. Most of our work exists as conversations, which are currently scattered across our agents. Though stored locally, these conversations use different formats. This is annoying because you cannot simply switch between agents without starting over. We get locked into a single provider and their agent as we invest in skills and memories over time. Skillsync acts as a universal converter. It moves the entire session, including all the messages, reasoning and tool calls so you can pick up right where you left off.
Skillsync collects all your sessions in one place and makes them searchable. It breaks down what each session is carrying, including which loaded skills the agent is actually using, making stale context easy to spot. You can also create shared workspaces to sync sessions across your team. You can build your own closed loop systems. Everything runs locally except when you share to workspaces.
The core is an open-source Rust engine called txcript (https://github.com/skillsynchq/txcript). It translates a session from one agent's on-disk format into another's, mapping conversation, reasoning, and tool history. Think ffmpeg or pandoc, but for agent sessions.
On top of that engine is a local-first desktop app. Your agent sessions are normally scattered across different tools' folders in formats you'd never read by hand; the app surfaces them in one place with a UI that makes them actually readable, the conversation, the reasoning, and the tool calls, so you can revisit what happened, move a session into another agent, or share it with a teammate.
Skills and memory are stored as portable, human-readable markdown you own, and exposed to any agent over MCP for search and selective retrieval.
Sessions and translation run locally on your machine. The one thing that leaves is what you explicitly share into a team workspace.
It’s been surprising to us to see how locked-in people already are without realizing it. You don't notice you're trapped in one agent or harness until you try to leave, and by then you've got months of sessions stuck in a format only that tool can read. The lock-in is invisible right up until it's expensive.
Once sessions are portable, they stop being disposable logs and become something you can actually build on, spotting patterns in how you work, handing a session off to someone else, letting a non-technical teammate pick up where an engineer left off. The session turns out to be the unit of collaboration, and right now it's being thrown away.
Before Skillsync, Nars and I built an open-source payment orchestrator that let merchants route across many processors instead of getting locked into one (30k+ GitHub stars). Fighting vendor lock-in by making incompatible systems interoperate was the whole job. We came into YC with a different idea, but the more we lived inside coding agents the more we saw the same problem from the other side: your context is locked into whatever agent you start with, because every agent stores sessions differently and none of it moves.
Some of the things we’re seeing people do with Skillsync are:
- Moving a session between Claude Code, Codex, and Cursor mid-task, including when you hit a usage limit on one and want to keep going on another.
- Thinking through a problem in a browser Claude chat, then handing the whole thread to Claude Code or Codex to build.
- Sharing research sessions with a team. Everyone uploads their sessions, so teammates and their agents can build on each other's work instead of repeating it.
It's available as a Mac app, CLI and MCP. Here's the demo: https://youtu.be/7hVhSnSKGl8. Would love to hear your feedback and answer questions!
Comments
I have made simple macos app to export my claude sessions to markdown(plus ordinal jsonl) and i just continuously sync it to dropbox.
i do the same for apple notes and imessage. so very portable
https://apps.apple.com/us/app/exporter-notes-to-markdown/id6...
I use recall https://github.com/viggy28/recall for the following reasons:
1. It's tightly integrated with Pi 2. Creates context automatically from sessions 3. No external dependencies - sqlite and numpy
Love this. Easily the most annoying thing about modern Agent development across Claude, Codex, etc. One nit: You don't auto-discover "archived" chats from Codex. They have to be unarchived and the app restarted before being found.
Good idea. I’m working on something similar, but for regular AI chats: https://www.vinaa.ai/. Portability and organization are just as important for these conversations, since they become a personal knowledge base you may want to revisit years later.
This is awesome! You solve an immediate need of mine for:
https://github.com/gitsense/chat/tree/readme-scale-knowledge
Since I only support Pi natively, your solution will make it possible for codex/claude/etc. users to discover their conversations in my app. Will definitely include this as workaround for making codex, claude and other sessions available for discovery.
this is awesome! i’ve been working on a tool for cross-harness integration tests - https://dynobox.xyz - and one of the hardest parts has been writing adapters for each harness since their transcript formats are all so different.
really excited to check out txcript… a shared translation layer could make my life sooo much easier!
This is good, I like it!! I've been mostly working with Claude and Chatgpt for separate stuff, however sometimes one of them is stuck and I could definitely use this to start a session with the other one and see if it figures it out.
Have you tested to see if there was any degradation happening when switching from one model to the other ? I mean some must be inevitable (maybe not!), but how much?
Very cool! I created something similar (with the same name), but in 2 tools. One to share skills (skillsync) and another to share context (contextsync).
I like to create a design with one model, sync it to another and iterate on it, then potentially go to another to apply/implement.
This looks nice! I tried to tackle the same problem with https://usecontinuo.dev (writing my own translation layer) - but Skillsync looks much more powerful.
If I were you I would look into maybe like analyzing sessions across harnesses? I’m not sure, some way to leverage this shared schema work that is not syncing
Because syncing is trivially solved by just telling the agent to keep a work journal in markdown
This is really cool, especially in a world where you're using Claude as a workhorse, but want to be able to bring the entire session context into Codex so you can draft communications with full context but without Claude-isms. (You can train Claude to spawn e.g. a Codex session, but Codex wouldn't know what to ask for from the broader context, beyond the prompt Claude gives it.)
And shipping sessions to colleagues is critical as well. My team relies heavily on a homegrown /resume skill that forces the harness to read every part of a Claude Code JSONL into context, letting us merge colleagues' sessions into our own.
What I thought this might be from the title, though, is a separate but related problem. The more semi-technical people in a company who start to use agentic systems, the more likely they are to create a vital playbook as a "skill" - but one not designed for easy tracking in a repository, that relies on local state, references their name, references other skills and rules that they've developed for their own work, etc. Cleaning these, figuring out what should be promoted across a team, figuring out when someone makes an update whether that's something that deserves human review, syncing across people who haven't used git/pull requests before - it's a big challenge that's highly context-dependent. If skills are the place where guardrails exist, "who watches the watchmen?"
There's an interesting duality here, because a colleague being able to ship a session where they iterated on such a skill, to a colleague who can understand the context of their change, is incredibly valuable. But it still relies on a human in the loop, and doesn't scale as a result. I think there's a really interesting design space here.
Any word on when you'll add support for antigravity? I often switch between harnesses and models and subscriptions, both for work and personal stuff, this is an awesome idea. One thing I do that I don't think you have support for is running sessions on different machines. Do you have support for, or do you plan on adding support for, syncing across machines?
I was thinking about doing this. If we treat ChatGPT like your local llm server, you basically open up a browser session, intercept all traffic and stick a local OpenAI compatible rest server that mutilates your input upstream through the ChatGPT ui, and then intercepts downstream and pushes it out your server.
API call to server
Then
Server leverages chrome plugin to send your llm call through the plugin , through the ui, wait for response , intercept, repackage and reroute it back out as a server response.
Then that $20 sub stretches to all uses cases for a developer.
kudos making the core open source. if you didnt do it, i wouldve. good luck
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I went the opposite way, and I think it's worth mentioning the cost of that choice. My conversation doesn't carry over. Only what a session explicitly recorded does. This includes decisions, open questions, verified items, and what's left to do. Anything that wasn't recorded is gone, and that's a real loss, not just a small part of the process.
I went with this approach because the transcript doesn't go into a file; it goes into another live session, which messes up its flow. We've already talked about this a bit when we were discussing "how to make reading Markdown cheaper." My answer was different: don't bring it over at all. The next session doesn't need to know how we got there—it just needs to know what we decided and what we've actually verified.
I don't think we've talked about this in this thread yet. Portability is all about a session that's already wrapped up. I often have two sessions open at the same time. One is building an endpoint, and the other is the screen that calls it. They need to ask each other before both build on different assumptions. Moving the transcript around won't fix this. What's needed is a message, not a copy.
I made a small open-source layer for this: a mailbox and a "walkie-talkie" for sessions in the clients you've already opened - https://github.com/automatis-tools/agents-can-communicate. It doesn't transfer memory and doesn't detect discrepancies on its own. The session has to check for those things.