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Show HN: HarnessRouter: Unified interface for agent harnesses Hey HN! We are building HarnessRouter, a canonical API for running Codex, Claude Code, Hermes, and other managed agent harnesses as your product backend.<p>Before building HarnessRouter, I used to build our own agent harness for our products. I tried LangGraph, agent SDKs from different vendors, pydantic, LLM tool use &#x2F; function call, and so on. It&#x27;s a very heavy lifting engineering effort, and I am disappointed about the agent deliveries compared to what Codex, CC can deliver. That changed my mindset. The frontier labs and famous open source communities are already putting so much engineering effort to build the world&#x27;s best harnesses, why not leverage them directly instead of building our own, just like how we call LLM chat completion endpoints instead of training our own models?<p>We provide a docker image to run HarnessRouter locally.<p>----------<p>Quickstart:<p><pre><code> docker pull harnessrouter&#x2F;harnessrouter docker run -d --name harnessrouter -p 127.0.0.1:3000:3000 -v harnessrouter:&#x2F;data harnessrouter&#x2F;harnessrouter docker logs -f harnessrouter Wait for the &quot;ready on :3000&quot; show up, then open the browser at http:&#x2F;&#x2F;localhost:3000. Default username&#x2F;password is harnessrouter&#x2F;harnessrouter Then in Integrations page, add your model provider credentials or API keys. In Harnesses tab, as of today we provide routing to Codex, Claude Code, and Hermes as base harnesses. You can customize any of them and configure harness instruction, MCP tools, and skills. Then go to Tasks and let them do jobs. </code></pre> ----------<p>Every harness has its own request&#x2F;response format and incompatible with each other. We propose Unified Harness Procotol [1] to standardize how an application talks to an agent harness. It covers harness selection and configuration, task execution, event streaming, sessions start cancel and resume, artifact management and delivery, and failure handling. It&#x27;s similar idea like LiteLLM, but for harnesses rather than models.<p>HarnessRouter implements UHP. We provide an AGENTS.md [2] and your coding agent can follow it to integrate your application with the harnesses available.<p>We also provide starter kits [3] to demonstrate some types of agentic products that can be built on HarnessRouter. It currently includes PPT agent, Spreadsheet agent, BI Dashboard agent, and Video generation agent.<p>Can&#x27;t wait to hear what you think!<p>[1] <a href="https:&#x2F;&#x2F;unifiedharnessprotocol.org" rel="nofollow">https:&#x2F;&#x2F;unifiedharnessprotocol.org</a><p>[2] <a href="https:&#x2F;&#x2F;harnessrouter.ai&#x2F;agents.md" rel="nofollow">https:&#x2F;&#x2F;harnessrouter.ai&#x2F;agents.md</a><p>[3] <a href="https:&#x2F;&#x2F;github.com&#x2F;harnessrouter&#x2F;starter-kit" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;harnessrouter&#x2F;starter-kit</a>

Show HN: Visimer – open-source visual editor for Mermaid diagrams Hi HN, Nick here, founder at OpenKnowledge. We built an open source library, Visimer, for editing Mermaid diagrams with a what-you-see-is-what-you-get visual editor. Try the playground at <a href="https:&#x2F;&#x2F;visimer.com&#x2F;playground" rel="nofollow">https:&#x2F;&#x2F;visimer.com&#x2F;playground</a>. You can rename labels, change shapes, add new nodes, etc. by clicking and dragging the visual canvas.<p>We set out to build this originally for OpenKnowledge, our markdown wysiwyg editor, then realized it’d be great to share it as a proper embeddable component library so that other apps can leverage it as well.<p>Our general take is that AI is great for generating content, but whenever you want to tweak fine details, for example to create an artifact sharable with others, point-edit functionality is much better. We built Visimer to bring that to Mermaid diagrams, just like we did for markdown.<p>Some technical bits:<p>- Leverages the native Mermaid.js renderer for visualizing the Mermaid diagram true to how it’s intended. We add point-edit functionality on top.<p>- We tried re-generating the entire file on every edit, but found that it would eat comments and formatting, etc. The final approach maps the rendered SVG elements back to a CST, so we can then edit only the parts of the file that should change.<p>You can pair the visual editor with any text-editor so you can have both visual and code-level editor experiences. The library provides bindings for Monaco and CodeMirror and is extensible. There&#x27;s also a low-level headless version.<p>If you just care about being able to edit your Mermaid diagrams in your markdown, you can try it in the OpenKnowledge app (our OSS markdown IDE, available as Mac&#x2F;Linux&#x2F;Windows apps).<p>Let us know what you think.

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Show HN: Tesana – An AI game engine that builds quality games end-to-end Hey HN! I built <a href="https:&#x2F;&#x2F;tesana.ai&#x2F;en" rel="nofollow">https:&#x2F;&#x2F;tesana.ai&#x2F;en</a>, a game generation platform that allows anyone to create full games with graphics, game logic, and animations from a simple text prompt - without coding.<p>Tesana has three key features 1. describe your game idea and have Tesana write a game plan for you 2. Build the game iteratively with AI, or let AI self-build the game in a build LOOP. 3) Launch the game on the web, without setting up an engine<p>Tesana has 250 000 builders on the platform today<p>I believe the democratization of game making is a good thing, and hopefully Tesana can help more people bring their game ideas to life.<p>Happy to chat about the AI or dev stack behind the product. Let me know if you have any questions&#x2F;comments&#x2F;feature requests!

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Show HN: Classifier and browser extension to detect rule violating HN comments I love HN, but lately I have been sick of reading the same dismissive criticisms over and over again. Along with political arguments that have been litigated to death, people&#x27;s issues with smooth scrolling on blogs, etc. Many of these comments do not get flagged for whatever reason. So I made a service to automatically classify whether comments violate (a modified form of) the HN guidelines automatically. In addition there&#x27;s a Chrome extension to collapse these comments (if they violate your score thresholds) so you don&#x27;t have to read them too. You can also just watch guideline violating comments as they are posted on the home page.<p>Here&#x27;s more info on how it works: <a href="https:&#x2F;&#x2F;classify.stylometry.net&#x2F;how-it-works" rel="nofollow">https:&#x2F;&#x2F;classify.stylometry.net&#x2F;how-it-works</a>

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Launch HN: Speko (YC S26) – OpenRouter for Voice AI Hi HN! I&#x27;m Bek, founder of Speko, a platform that finds an optimal combination of speech-to-text, LLM, and text-to-speech models, given your constraints, among all our public benchmarked options, and tells you why.<p>Demo: <a href="https:&#x2F;&#x2F;www.youtube.com&#x2F;watch?v=no2LY2gRh-c" rel="nofollow">https:&#x2F;&#x2F;www.youtube.com&#x2F;watch?v=no2LY2gRh-c</a><p>Typical production voice agent is an ensemble of three models: STT, an LLM, and TTS.<p>Each of those layers offers a dozen credible vendors, and each month there are new models on the market. Almost everyone evaluates once, picks a stack of their choice, and never rechecks because switching from a vendor to another involves yet another integration and arguments about the numbers.<p>The result is that you use voice agents running last quarter&#x27;s models while better and cheaper options are available.<p>Before founding Speko, I spent four years as cofounder and CTO building voice agents for enterprises across Asia in 10+ languages. Each time a new speech model would arrive, we repeated the same ritual: hire native-speaking raters, benchmark it against our existing stack, and update production if it improved. Speko turns this process into an API. A team running thousands of calls a day told us: &quot;we can literally go to this dashboard, switch the model, and it will do it for us.&quot;<p>How it works: you send a request with your optimization criteria (accuracy, latency, cost or balanced), language and region. The router filters to models which we measured for the given combination of constraints, benchmarks them, selects the winner, and returns a response with headers containing provider, model names, and the scores. The gateway prefetches signed session plans, so a new session dials the provider straight from memory; no control-plane round trip while a caller waits.<p>Failover happens only during connection setup stage: if the provider refuses the connection attempt, we start connecting to the runners-up.<p>Some of the customer stories: one founder came to us not knowing what to pick at all: he gave us his use case and now routes everything through the platform. A property management AI runs LiveKit in Python and had not updated STT or TTS since launch: they did not know their STT had high error rates on their calls, better options existed, and swapping always looked like an R&amp;D project. One team did not know which models to pick for Spanish. A medical team did not know which STT handles medical vocabulary best. In every case we helped find the right stack from the benchmarks, and now they route through us.<p>The measuring part is public: we pass the same inputs to every model in one region in different dated runs and we publish the boards, including those where our selections perform worse than alternatives. A launch demo answers which 30-second clip sounds better; production asks which model survives minute eight, so we test spontaneous speech, money and dates, ten-minute takes, and the rankings change. We trained an automatic scorer for TTS naturalness on our blind head-to-head listening votes; on providers it has never seen a vote for, it picks the same winner our raters do about as often as raters agree with each other.<p>We don&#x27;t train or sell models ourselves, that&#x27;s precisely how we keep our rankings impartial.<p>We also open sourced the gateway for teams who want to avoid an extra network hop on the audio path and don&#x27;t want to share keys with our cloud (<a href="https:&#x2F;&#x2F;github.com&#x2F;SpekoAI&#x2F;gateway" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;SpekoAI&#x2F;gateway</a>, MIT): one Go binary, which is running as a sidecar in your agent&#x27;s container, speaks one local protocol over Unix socket, pins provider hosts and attaches your keys. In BYOK mode it doesn&#x27;t communicate with us at all.<p>Notice that the anonymous, content-free telemetry is enabled by default, and one env var disables it.<p>Cost: the gateway and BYOK setup will be free forever, we charge for the hosted router and managed keys with consolidated billing. Since we started the batch in late June, external usage has grown about 25 percent per week on average, front-loaded toward the launch weeks.<p>I would love feedback from the community: how do you pick speech models now, and what makes you trust the third-party benchmark?<p><a href="https:&#x2F;&#x2F;speko.ai&#x2F;">https:&#x2F;&#x2F;speko.ai&#x2F;</a>

Judge relying wholly on AI in order is covered by judicial immunity, court rules

Show HN: Saggar, a Mac terminal that keeps sessions and your attention organized Hi HN, like many of you talented folk, I’ve been building more, faster than ever. I built Saggar after my terminal stopped feeling like a tool and started feeling like a tab-management problem. Let me know you think!