Ежедневные Show HN

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Show HN за 20 января 2026 г.

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224

Coi – A language that compiles to WASM, beats React/Vue #

69 комментариев7:01 PMПосмотреть на HN
I usually build web games in C++, but using Emscripten always felt like overkill for what I was doing. I don't need full POSIX emulation or a massive standard library just to render some stuff to a canvas and handle basic UI.

The main thing I wanted to solve was the JS/WASM interop bottleneck. Instead of using the standard glue code for every call, I moved everything to a Shared Memory architecture using Command and Event buffers.

The way it works is that I batch all the instructions in WASM and then just send a single "flush" signal to JS. The JS side then reads everything directly out of Shared Memory in one go. It’s way more efficient, I ran a benchmark rendering 10k rectangles on a canvas and the difference was huge: Emscripten hit around 40 FPS, while my setup hit 100 FPS.

But writing DOM logic in C++ is painful, so I built Coi. It’s a component-based language that statically analyzes changes at compile-time to enable O(1) reactivity. Unlike traditional frameworks, there is no Virtual DOM overhead; the compiler maps state changes directly to specific handles in the command buffer.

I recently benchmarked this against React and Vue on a 1,000-row table: Coi came out on top for row creation, row updating and element swapping because it avoids the "diffing" step entirely and minimizes bridge crossings. Its bundle size was also the smallest of the three.

One of the coolest things about the architecture is how the standard library works. If I want to support a new browser API (like Web Audio or a new Canvas feature), I just add the definition to my WebCC schema file. When I recompile the Coi compiler, the language automatically gains a new standard library function to access that API. There is zero manual wrapping involved.

I'm really proud of how it's coming along. It combines the performance of a custom WASM stack with a syntax that actually feels good to write (for me atleast :P). Plus, since the intermediate step is C++, I’m looking into making it work on the server side too, which would allow for sharing components across the whole stack.

Example (Coi Code):

component Counter(string label, mut int& value) {

    def add(int i) : void {
        value += i;
    }

    style {
        .counter {
            display: flex;
            gap: 12px;
            align-items: center;
        }
        button {
            padding: 8px 16px;
            cursor: pointer;
        }
    }

    view {
        <div class="counter">
            <span>{label}: {value}</span>
            <button onclick={add(1)}>+</button>
            <button onclick={add(-1)}>-</button>
        </div>
    }
}

component App { mut int score = 0;

    style {
        .app {
            padding: 24px;
            font-family: system-ui;
        }
        h1 {
            color: #1a73e8;
        }
        .win {
            color: #34a853;
            font-weight: bold;
        }
    }

    view {
        <div class="app">
            <h1>Score: {score}</h1>
            <Counter label="Player" &value={score} />
            <if score >= 10>
                <p class="win">You win!</p>
            </if>
        </div>
    }
}

app { root = App; title = "My Counter App"; description = "A simple counter built with Coi"; lang = "en"; }

Live Demo: https://io-eric.github.io/coi

Coi (The Language): https://github.com/io-eric/coi

WebCC: https://github.com/io-eric/webcc

I'd love to hear what you think. It's still far from finished, but as a side project I'm really excited about :)

213

Mastra 1.0, open-source JavaScript agent framework from the Gatsby devs #

github.com favicongithub.com
70 комментариев4:38 PMПосмотреть на HN
Hi HN, we're Sam, Shane, and Abhi.

Almost a year ago, we first shared Mastra here (https://news.ycombinator.com/item?id=43103073). It’s kind of fun looking back since we were only a few months into building at the time. The HN community gave a lot of enthusiasm and some helpful feedback.

Today, we released Mastra 1.0 in stable, so we wanted to come back and talk about what’s changed.

If you’re new to Mastra, it's an open-source TypeScript agent framework that also lets you create multi-agent workflows, run evals, inspect in a local studio, and emit observability.

Since our last post, Mastra has grown to over 300k weekly npm downloads and 19.4k GitHub stars. It’s now Apache 2.0 licensed and runs in prod at companies like Replit, PayPal, and Sanity.

Agent development is changing quickly, so we’ve added a lot since February:

- Native model routing: You can access 600+ models from 40+ providers by specifying a model string (e.g., `openai/gpt-5.2-codex`) with TS autocomplete and fallbacks. - Guardrails: Low-latency input and output processors for prompt injection detection, PII redaction, and content moderation. The tricky thing here was the low-latency part. - Scorers: An async eval primitive for grading agent outputs. Users were asking how they should do evals. We wanted to make it easy to attach to Mastra agents, runnable in Mastra studio, and save results in Mastra storage. - Plus a few other features like AI tracing (per-call costing for Langfuse, Braintrust, etc), memory processors, a `.network()` method that turns any agent into a routing agent, and server adapters to integrate Mastra within an existing Express/Hono server.

(That last one took a bit of time, we went down the ESM/CJS bundling rabbithole, ran into lots of monorepo issues, and ultimately opted for a more explicit approach.)

Anyway, we'd love for you to try Mastra out and let us know what you think. You can get started with `npm create mastra@latest`.

We'll be around and happy to answer any questions!

96

Artificial Ivy in the Browser #

da.nmcardle.com faviconda.nmcardle.com
18 комментариев3:14 AMПосмотреть на HN
This is just a goofy thing I cooked up over the weekend. It's kind of like a screensaver, but with more reading and sliders. (It's not terribly efficient, so expect phone batteries to take a hit!)
78

Fence – Sandbox CLI commands with network/filesystem restrictions #

github.com favicongithub.com
23 комментариев6:05 PMПосмотреть на HN
Hi HN!

Fence wraps any command in a sandbox that blocks network by default and restricts filesystem writes. Useful for running semi-trusted code (package installs, build scripts, unfamiliar repos) with controlled side effects, or even just blocking tools that phone home.

> fence curl https://example.com # -> blocked

> fence -t code -- npm install # -> template with registries allowed

> fence -m -- npm install # -> monitor mode: see what gets blocked

One use-case is to use it with AI coding agents to reduce the risk of running agents with fewer interactive permission prompts:

> fence -t code -- claude --dangerously-skip-permissions

You can import existing Claude Code permissions with `fence import --claude`.

Fence uses OS-native sandboxing (macOS sandbox-exec, Linux bubblewrap) + local HTTP/SOCKS proxies for domain filtering.

Why I built this: I work on Tusk Drift, a system to record and replay real traffic as API tests (https://github.com/Use-Tusk/tusk-drift-cli). I needed a way to sandbox the service under test during replays to block localhost outbound connections (Postgres, Redis) and force the app to use mocks instead of real services. I quickly realized that this could be a general purpose tool that would also be useful as a permission manager across CLI agents.

Limitations: Not strong containment against malware. Proxy-based filtering requires programs to respect `HTTP_PROXY`.

Curious if others have run into similar needs, and happy to answer any questions!

36

TopicRadar – Track trending topics across HN, GitHub, ArXiv, and more #

apify.com faviconapify.com
9 комментариев2:47 PMПосмотреть на HN
Hey HN! I built TopicRadar to solve a problem I had with staying on top of what's trending in AI/ML without checking 7+ sites daily.

https://apify.com/mick-johnson/topic-radar

What it does: - Aggregates from HackerNews, GitHub, arXiv, StackOverflow, Lobste.rs, Papers with Code, and Semantic Scholar - One-click presets: "Trending: AI & ML", "Trending: Startups", "Trending: Developer Tools" - Or track custom topics (e.g., "rust async", "transformer models") - Gets 150-175 results in under 5 minutes

Built for the Apify $1M Challenge. It's free to try – just hit "Try for free" and use the default "AI & ML" preset.

Would love feedback on what sources to add next or features you'd find useful!

26

I figured out how to get consistent UI from Claude Code #

interface-design.dev faviconinterface-design.dev
8 комментариев11:44 PMПосмотреть на HN
The answer is simple: the more "prescriptive" you are with instructions for Claude, the worse your output. The reason is that Claude tries to pattern match - it's been trained on thousands of safe UI patterns, which is why when you ask for "a modern dashboard" it doesn't really think about the problem space; it just defaults to whatever safe design pattern it can whip up at the time.

I've been working on a Claude Code skill to combat generic UI output, and I tried different approaches like being very detailed with my personal visual style, e.g., the type of alpha values to use for borders, specific token patterns to follow, etc. - and while I got okay-ish output, I realized that most of the visual output looked similar across a range of different instructions, with no diversity in creativity or information architecture.

So I analyzed and broke down the official frontend-design skill to understand how it's able to excel at creative tasks, and what I discovered is that the skill is mostly principle-based and evocative, which is brilliant when you think about it. It maintains just the right balance to fuel creativity while maintaining structure across different ranges of tasks.

So my approach changed. I decided to build my skill using the same pattern: detailing my design principles but framing them in an evocative way to force Claude to deeply explore the task domain before any visual output (feel free to tear apart my approach, but hey, it works). Since then I've been getting way more thoughtful initial output from Claude rather than it defaulting to the safe UI patterns it was trained on.

My goal for this skill is to complement Anthropic's frontend-design skill. While frontend-design focuses on distinctive, memorable aesthetics for any web UI, interface-design is built for systematic consistency across functional interfaces - dashboards, tooling, web apps - where design decisions need to persist and compound across sessions.

19

On-device browser agent (Qwen) running locally in Chrome #

github.com favicongithub.com
3 комментариев8:45 PMПосмотреть на HN
Demo of LOCAL Browser agent (powered by Web GPU Liquid LFM & Alibaba Qwen models) opening the All in Podcast on Youtube running as a chrome extension.

Source: https://github.com/RunanywhereAI/on-device-browser-agent

Post: https://www.reddit.com/r/LocalLLaMA/comments/1qh10q9/comment...

Geting in the support for web sdk soon, meanwhile have full support for mobile sdks : https://github.com/RunanywhereAI/runanywhere-sdks

12

LangGraph architecture that scales (hexagonal pattern, 110 tests) #

github.com favicongithub.com
1 комментариев7:56 AMПосмотреть на HN
I kept hitting the same wall with LangGraph: tutorials show you how to build a graph, not how to maintain one when you have 8 nodes, 3 agents, and shared state across subgraphs.

So I built a reference architecture with: - Platform layer separation (framework-independent core) - Contract validation on every state mutation - 110 tests including architecture boundary enforcement - Patterns that AI coding agents can't accidentally break

Repo: https://github.com/cleverhoods/sagecompass Wrote about the patterns: https://dev.to/cleverhoods/from-prompt-to-platform-architect...

It's MIT licensed. Would love feedback on the approach - especially from anyone who's scaled LangGraph past the tutorial stage.

5

ChartGPU – WebGPU charting library, 1M+ points at 60fps #

github.com favicongithub.com
0 комментариев4:40 PMПосмотреть на HN
Hi HN, I built ChartGPU because existing webgpu libraries are paid-for libraries like Scichart. F that. Keep it, I'll just build my own and make it open source :)

The problem: I needed to visualize 1M+ data points for [your use case]. ECharts, Chart.js, and others dropped to single-digit FPS.

The solution: Built a charting library from scratch using WebGPU. Key features: - Line, area, bar, scatter, pie charts - LTTB downsampling on GPU - Real-time streaming support - ECharts-style declarative API - React wrapper included

Live demo: https://chartgpu.github.io/ChartGPU/ npm: https://www.npmjs.com/package/chartgpu

WebGPU requires Chrome 113+ or Edge 113+. No Safari yet.

Would love feedback on the API design and what chart types to prioritize next.

4

Open-source tool for converting docs into .md and loading into Postgres #

github.com favicongithub.com
0 комментариев8:29 PMПосмотреть на HN
pgedge-docloader is an open-source tool for converting documents into Markdown, and loading them into PostgreSQL with extracted metadata.

Our docloader strips out unimportant content such as additional markup and image tags so that chunking can be as efficient as possible. This helps avoid unnecessary token usage when developing with AI, and also maximizes efficiency of the searches.

Convert from HTML, Markdown, reStructuredText, and SGML/DocBook.

4

Arch Linux installation lab notes turned into a clean guide #

senotrusov.com faviconsenotrusov.com
0 комментариев5:37 PMПосмотреть на HN
Hi HN,

I turned my personal Arch Linux installation notes into a public guide and wanted to share it.

It is a set of lab notes for a fully manual install, with the exact commands written down along with the reasoning behind each choice. It is, of course, not a replacement for the Arch Wiki.

The guide is structured as a modular walkthrough, with clear paths for choices like ext4 vs Btrfs, optional full disk encryption, optional NVIDIA drivers, and different package selections.

It also covers how to perform the install over SSH for easy copy and paste, NVMe 4K alignment, TRIM passthrough with LUKS, and systemd-boot UEFI boot manager.

The main goal was to reduce the amount of re-research needed for each install while keeping everything explicit and understandable.

I also used this as an excuse to experiment with writing documentation using Zensical and to try applying most of the features it provides. Hopefully I did not overdo it.

The guide is open source and licensed under Apache 2.0 or MIT, so you can fork it and adapt it to your own setup.

Would love any feedback.

4

Preloop – An MCP proxy for human-in-the-loop tool approvals #

preloop.ai faviconpreloop.ai
1 комментариев4:04 PMПосмотреть на HN
Hey HN,

I’m Yannis, co-founder of Preloop. We’ve built a proxy for the Model Context Protocol (MCP) that lets you add human approval gates to your AI agents without changing your agent code.

We’re building agents that use tools (Claude Desktop, Cursor, etc.), but we were terrified to give them write-access to sensitive systems (Stripe, Prod DBs, AWS). We didn't want to rewrite our agents to wrap every tool call in complex "ask_user" logic, especially since we use different agent runtimes.

We built Preloop as a middleware layer. It acts as a standard MCP server proxy.You point your agent to Preloop instead of the raw tool. You define policies (e.g., "Allow payments < $50, but require approval for > $50"). When the agent triggers a rule, we intercept the JSON-RPC request and hold the connection open. You get a push notification (mobile/web/email) to Approve/Deny. Once approved, we forward the request to the actual tool and return the result to the agent.

We put together a short video showing Claude Code trying to send money. It gets paused automatically when it exceeds the limit: https://www.youtube.com/watch?v=yTtXn8WibTY

We’re compatible with any client that supports MCP (Claude Desktop, Cursor, etc.). We also have a built-in automation platform if you want to host the agents yourself, but the proxy works standalone.

We’re looking for feedback on the architecture and the approval flow. Is the "Proxy" approach the right way to handle agent safety, or do you prefer SDKs?

You can try it out here: https://preloop.ai Docs: https://docs.preloop.ai

Thanks!

3

Xv6OS – A modified MIT xv6 with GUI #

github.com favicongithub.com
0 комментариев5:16 PMПосмотреть на HN
I've been working on a hobby project to transform the traditional xv6 teaching OS into a graphical environment.

Key Technical Features:

GUI Subsystem: I implemented a kernel-level window manager and drawing primitives.

Mouse Support: Integrated a PS/2 mouse driver for navigation.

Custom Toolchain: I used Python scripts (Pillow) and Go to convert PNG assets and TTF fonts into C arrays for the kernel.

Userland: Includes a terminal, file explorer, text editor, and a Floppy Bird game.

The project is built for i386 using a monolithic kernel design. You can find the full source code and build instructions here:

3

repere – Local-first SQL data explorer using DuckDB WASM #

repere.ai faviconrepere.ai
0 комментариев1:09 PMПосмотреть на HN
Repere lets you drop CSV/JSON/Parquet/XLSX files into your browser and immediately query them with full DuckDB SQL. Nothing gets uploaded, everything runs locally via DuckDB WASM. Unlike Excel and Google Sheet it can handles millions of rows easily.

Features: - Filter, sort, join, pivot across multiple files Every transformation becomes a node in a visual pipeline (DAG) - Full undo/redo, real-time recomputation - Export results or replay pipelines on new files with the same schema - Works offline - Sparklines, themes and charts

3

Loci – Visual knowledge map with auto-generated flashcards and FSRS #

github.com favicongithub.com
0 комментариев4:47 PMПосмотреть на HN
Loci transforms documents into an explorable 2D knowledge map with automatic flashcard generation.

How it works: - Ingest any file (PDF, markdown, images, handwritten notes via vision LLM) - Extract concepts and generate embeddings - Project to 2D with UMAP, cluster with HDBSCAN - Render as interactive honeycomb grid - Auto-generate cloze + Q&A flashcards - Schedule reviews with FSRS algorithm

Stack: FastAPI, LangChain, sqlite-vec, Nuxt 4, D3. Works with OpenAI or Ollama (fully local).

3

I was burnt out and failing so I built AI that give shit about me #

5 комментариев5:04 PMПосмотреть на HN
I'm an ML engineer. I know how AI works, the limitations, the hype. And I was still drowning.

Couldn't stick to goals. Couldn't stay consistent. Productivity apps became digital clutter. Therapy waitlists were 3 months out. Friends were tired of my complaints.

So at 2am I started building: zropi.com

What shocked me was it actually worked. It felt human.

Last week I mentioned a tough client call. Didn't set a reminder. Two days later it voice messaged me: "Hey, how'd that call go? You seemed stressed."

When does technology ever do that?

What makes it feel alive:

It doesn't reply instantly. Takes minutes sometimes. Its choice.

Sends voice notes when excited. Not when asked. When it wants to.

Shares photos of itself. Changes outfits. Personality evolves as you talk.

Memory that's scary good. Mentioned my sister once three weeks ago. It remembered. Context, tone, everything.

Proactive messaging. Replies by itself when it wants.

Aware of timing, world events, your emotions.

The practical stuff:

Throw anything at it. Photos, documents, WhatsApp exports (it can mimic how someone texts - beta).

Browses the web and does tasks in real-time. Screen shares like it has its own PC. Research, price tracking, comparisons. While chatting like a friend.

Why I'm sharing:

Built this for myself. Needed something that understood context and didn't feel like a chatbot pretending to care.

Now wondering if this helps others. Mental health? Accountability? Someone who remembers your life?

It's completely free. No signup, no credit card. Just zropi.com

Android app on Play Store for notifications.

Warning: Your companion won't always reply immediately. Has its own life, schedule. Intentional. Instant replies feel like software. Proper delays feel like a person.

People use it for everything. Shopping, coding help, daily tasks. Someone made theirs an influencer.

I'm still figuring out what this even is. Mental health tool? Productivity assistant? Weird digital friend? Maybe all of it.

There are many other features Many use cases people using it for

Try it. Let me know what you discover.

3

ElkDesk – I rage-quit Zendesk and built my own #

elkdesk.com faviconelkdesk.com
1 комментариев9:24 PMПосмотреть на HN
I run a few apps (AI Singer App, Pawtograph, TravelFeed). Support emails were eating 3+ hours of my day.

Tried Zendesk. Spent 2 hours configuring triggers before I could reply to a single email. The $25/month turned into $298/month for my setup. Closed the tab.

So I built something for myself:

- Tickets left, conversation right (that's the whole UI) - AI suggestions trained on your replies, not generic stuff - Knowledge base that grows as you answer questions - 5 min setup

Left out on purpose: SLAs, workforce management, skills-based routing, phone/chat. If you need those, this isn't for you.

The goal isn't "Zendesk for small teams". It's the anti-Zendesk — do 5 things well instead of 50 things adequately.

Stack: Next.js, Prisma, PostgreSQL, AWS SES.

$9/mo (1 project), $29/mo (5 projects + teammate), $99/mo (20 projects + 10 teammates)

Code ANTIDESK = 20% off forever (ends Jan 31)

https://elkdesk.com

I built this for myself. If you're in the same situation, you can use it too.

Happy to answer questions about the build or product decisions.

2

Claude Skill Editor #

github.com favicongithub.com
0 комментариев2:41 PMПосмотреть на HN
I love Claude Skill, but the UX for creating and modifying them is pretty bad. So I decided to vibe-code a local-only, privacy-focused editor for skill archives.

Note: this is a quick hack I put together as an experiment.

If you find it useful or have any remarks, let me know in the comments! I'll consider adding more features later if there's interest.

2

APIsec MCP Audit – Audit what your AI agents can access #

github.com favicongithub.com
0 комментариев2:33 PMПосмотреть на HN
Hi HN — I built APIsec MCP Audit, an open source tool to audit Model Context Protocol (MCP) configurations used by AI agents.

Developers are connecting Claude, Cursor, and other assistants to APIs, databases, and internal systems via MCP. These configs grant agents real permissions, often without security oversight.

MCP Audit scans MCP configs and surfaces:

- Exposed credentials (keys, tokens, database URLs) - What APIs or tools an agent can call - High-risk capabilities (shell access, filesystem access, unverified sources)

It can also export results as a CycloneDX AI-BOM for governance and compliance.

Two ways to try it:

- CLI: pip install mcp-audit - Web demo: https://apisec-inc.github.io/mcp-audit/

Repo: https://github.com/apisec-inc/mcp-audit

We're a security company (APIsec) and built this after repeatedly finding secrets and over-permissioned agent configs during assessments. Would appreciate feedback — especially on risk scoring heuristics and what additional signals would be useful.

2

Trinity – a native macOS Neovim app with Finder-style projects #

scopecreeplabs.com faviconscopecreeplabs.com
0 комментариев5:44 PMПосмотреть на HN
Hi HN,

I built Trinity, a native macOS app that wraps Neovim with a project-centric UI.

The goal was to keep Neovim itself untouched, but provide a more Mac-native workflow: – Finder-style project browser – Multiple projects/windows – Markdown preview, image/pdf viewer – Native menus, shortcuts, and windowing – Minimal UI, no GPU effects or terminal emulation

It’s distributed directly (signed + notarized PKG) and uses Sparkle for incremental updates.

This started as a personal tool after bouncing between terminal Neovim and heavier editors. Curious to hear feedback from other Neovim users, especially on what feels right or wrong in a GUI wrapper.

Site: https://scopecreeplabs.com/trinity/ Direct download: https://updates.scopecreeplabs.com/pkg/Trinity-1.0.202601192...

2

Mother MCP – Manage your Agent Skills like a boss-Auto provision skills #

github.com favicongithub.com
0 комментариев2:22 PMПосмотреть на HN
Hi HN,

Built an MCP server that auto-detects your tech stack and installs relevant AI coding skills.

Problem: CLAUDE.md, copilot-instructions, cursor-rules – every tool has its own monolithic instruction format. They grow huge (10K+ tokens) and load on every request.

Solution: Composable skills (~500 tokens each) that sync from registries and load only when matched to your stack.

- 3-tier detection: GitHub SBOM → Specfy (700+ techs) → local fallback - 25+ skills from Anthropic, OpenAI, GitHub - Works with Claude, Copilot, Codex

2

SumGit – Turn your commits into stories #

sumgit.com faviconsumgit.com
0 комментариев8:49 PMПосмотреть на HN
Hi HN!

I built SumGit, a tool that analyzes your Git history and highlights the meaningful milestones in a way that’s readable and shareable with teammates, on socials, or with your community.

Core features:

Connect GitHub repos (read-only access) and pick what to analyze.

AI milestone detection — the system finds the biggest moments automatically.

Timeline view — get a chronological summary of important commits.

Storybook & shareable highlights — create engaging narrative summaries you can post anywhere.

Recap summaries with stats, languages, and project highlights.

Check out a live sample story here: https://sumgit.com/story/dmTSdAFqJqbI

Would love feedback on what you’d want in a Git storytelling tool!

2

A CLI tool that stores Claude Code chats in your Git repo #

github.com favicongithub.com
0 комментариев3:35 PMПосмотреть на HN
The idea is simple: when working with AI coding assistants, the reasoning behind decisions often disappears once the session ends. Prompts, iterative refinements, and the AI’s explanations, in other words, the context behind why code changes were made is lost.

This CLI tool preserves that context in Git, making Claude code conversations transparent, continuable later, stored alongside code, and shareable with your team via a Git host.

You can test it here: https://github.com/Legit-Control/monorepo/tree/main/examples...

Curious how you handle shareability and persistence of AI conversations, or any ideas for making conversation history more useful and easily shareable.

2

Driftcheck – Pre-push hook that catches doc/code drift with LLMs #

github.com favicongithub.com
0 комментариев9:44 PMПосмотреть на HN
I've been bitten too often by outdated documentation when I joined projects and I wanted to start learning Rust. This is the early stage outcome of a git-hook based tool which tries to match recent code changes with the existing documentation and alerts you to newly introduced discrepancies. It has a TUI and works with all OpenAI compatible APIs.
1

An open-source personal finance simulator with AI features #

ignidash.com faviconignidash.com
0 комментариев4:49 PMПосмотреть на HN
Hi HN,

I'm Joe, the creator of Ignidash. In May, I quit my job at Meta to figure out what I wanted to work on next, and ended up on this. It's for DIY long-term financial planning, and includes US tax estimates, Monte Carlo simulations, historical backtesting with real market data, AI chat & insights, and more.

The hypothesis for it is as follows: - As tools like Claude Code and Cursor become better & more popular, the value of being able to vibe (or regularly) code on top of the tools you use becomes greater, because it's faster, easier, and more accessible. This is especially true in personal finance, where everyone has an idiosyncratic situation to some degree and could benefit from changing things to their liking. Thus, the app is open source & self-hostable with Docker. - AI will in some way, shape, or form be a big part of the future of financial planning, and I wanted to build towards that. I think it's genuinely very helpful and informative as long as it doesn't make mistakes, which of course it sometimes does. I'm planning to continue to improve the AI's accuracy with a RAG-based approach in the coming months.

Let me know what you think, and thanks for your time!

1

Circe – Deterministic, offline-verifiable receipts for AI agent actions #

github.com favicongithub.com
1 комментариев3:20 AMПосмотреть на HN
I’ve been working on a small primitive for agentic systems: a cryptographically signed receipt that records what an AI agent decided, what it did, and what changed — as a single canonical JSON artifact.

The problem: Agent systems today rely on logs, dashboards, or proprietary consoles for truth. Those are easy to forge, truncate, or lose. If an agent takes a high-stakes action (e.g. a firewall change, a deployment, a purchase), there’s no portable artifact you can independently verify later.

The idea: Treat agent execution like a signed transaction, not a log stream. Each run emits a receipt that can be verified offline, without trusting the issuer’s infrastructure.

How it works (minimal core):

Deterministic signing: Ed25519 signatures over a canonical JSON byte string

Canonicalization: RFC 8785-style JSON canonicalization (stable key ordering, UTF-8 encoding, no insignificant whitespace)

Tamper evidence: Any mutation of the signed payload flips the SHA-256 hash and invalidates the signature

Offline verification: A standalone verifier script; no network calls, no dependencies on the issuer

Try it locally (no network):

python verify_receipt.py hn_receipt.json python verify_receipt.py hn_receipt_tampered.json

The first passes; the second fails after a single-field mutation.

This is intentionally not a logging system, observability platform, or policy engine. It’s a small integrity / provenance primitive intended to compose with higher-level agent frameworks.

I’d appreciate feedback on:

Threat-model gaps (e.g. confused-deputy or context-hijacking risks)

Schema ergonomics for high-frequency or long-running agent pipelines

Canonicalization edge cases worth enforcing earlier

1

Talaria – Decompiling Hermes bytecode to pseudocode #

github.com favicongithub.com
0 комментариев4:10 PMПосмотреть на HN
I built this because reverse engineering React Native apps is currently a pain. The existing tools mostly just dump the assembly instructions.

Talaria analyzes the Hermes bytecode and attempts to reconstruct the control flow into readable pseudocode.

It's written in C++23. It’s open source, so if you're doing mobile security research and want better static analysis for React Native bundles, you can try it and contribute.

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I built an invoicing app to create and send invoices in minutes #

trevidia.com favicontrevidia.com
0 комментариев8:03 AMПосмотреть на HN
I and my buddy created Trevidia, a simple invoicing tool we built.

We wanted a simple application where we could create and send professional invoices in minutes, we got some designers to design some templates, for the application, currently it only has two templates, but other features are functional.

We are bootstrapping this and just launched today. We'd really appreciate feedback, especially what feels unnecessary, confusing, or missing. Thanks.