🛠️ All DevTools

[Build/Deploy] Show HN: AgentSwift – Open-source iOS builder agent I'm working on a coding agent for building iOS apps. It's built on openspec and xcodebuildmcp. It's free and open source.

[Other] Ted Nyman – High Performance Git

[Other] L123: A Lotus 1-2-3–style terminal spreadsheet with modern Excel compatibility

[Other] GitHub is having issues now

[Other] Git-based cache saves 50% on token usage

[Other] GitHub Copilot is moving to usage-based billing

[Other] Show HN: I made a website to clean up recipe websites Hi hn! It has always annoyed me that recipe websites are so cluttered and have so much (in my opinion) useless fluff, so I made a little website to solve that problem! One good thing about SEO for once is that Google has pretty much forced the internet to adopt JSON-LD for recipes so many recipes are directly extractable and for others I have several fall back parsers including an indieweb parser :)<p>If you do find a website that is broken feel free to click the flag button or share it as I would love to fix any edge cases

[Monitoring/Observability] Show HN: Utilyze – an open source GPU monitoring tool more accurate than nvtop The standard GPU utilization metric reported by nvidia-smi, nvtop, Weights &amp; Biases, Amazon CloudWatch, Google Cloud Monitoring, and Azure Monitor is highly misleading. It reports the fraction of time that any kernel is running on the GPU, which means a GPU can report 100% utilization even if only a small portion of its compute capacity is actually being used. In practice, we&#x27;ve seen workloads with ~1–10% real compute throughput while dashboards show 100%.<p>This becomes a problem when teams rely on that metric for capacity planning or optimization decisions, it can make underutilized systems look saturated.<p>We&#x27;re releasing an open-source (Apache 2.0) tool, Utilyze, to measure GPU utilization differently. It samples hardware performance counters and reports compute and memory throughput relative to the hardware&#x27;s theoretical limits. It also estimates an attainable utilization ceiling for a given workload.<p>GitHub link: <a href="https:&#x2F;&#x2F;github.com&#x2F;systalyze&#x2F;utilyze" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;systalyze&#x2F;utilyze</a><p>We&#x27;d love to hear your thoughts!

[Other] Tendril – a self-extending agent that builds and registers its own tools

[Other] Show HN: OSS Agent I built topped the TerminalBench on Gemini-3-flash-preview Scored 65.2% vs google&#x27;s official 47.8%, and the existing top closed source model Junie CLI&#x27;s 64.3%.<p>Since there are a lot of reports of deliberate cheating on TerminalBench 2.0 lately (<a href="https:&#x2F;&#x2F;debugml.github.io&#x2F;cheating-agents&#x2F;" rel="nofollow">https:&#x2F;&#x2F;debugml.github.io&#x2F;cheating-agents&#x2F;</a>), I would like to also clarify a few things<p>1. Absolutely no {agents&#x2F;skills}.md files were inserted at any point. No cheating mechanisms whatsoever<p>2. The cli agent was run in leaderboard compliant way (no modification of resources or timeouts)<p>3. The full terminal bench run was done using the fully open source version of the agent, no difference between what is on github and what was run.<p>I was originally going to wait for it to land on the leaderboard, but it has been 8 days and the maintainers do not respond unfortunately (there is a large backlog of the pull requests on their HF) so I decided to post anyways.<p>HF PR: <a href="https:&#x2F;&#x2F;huggingface.co&#x2F;datasets&#x2F;harborframework&#x2F;terminal-bench-2-leaderboard&#x2F;discussions&#x2F;145" rel="nofollow">https:&#x2F;&#x2F;huggingface.co&#x2F;datasets&#x2F;harborframework&#x2F;terminal-ben...</a><p>It is astounding how much the harness matters, based on this and other experiments I have done.

[Other] Show HN: A terminal spreadsheet editor with Vim keybindings While speccing out this spreadsheet tool, I realized that I never had to think about the keybindings. It all just came naturally from Vim. Normal&#x2F;insert&#x2F;visual modes, hjkl navigation, dd&#x2F;yy&#x2F;p, :w, :q. The usual muscle memory works.<p>It supports CSV&#x2F;TSV import and export, and a native .cell format that preserves formulas. The formula engine handles SUM, AVERAGE, COUNT, MIN, MAX, and IF with range references.<p>The codebase is a Cargo workspace: a pure cell-sheet-core library (no TUI dependency) and a cell-sheet-tui crate on top of ratatui. Early days, but it&#x27;s usable.<p>To try it out: cargo install cell-sheet-tui<p>Feedback of any kind is greatly appreciated!

[Other] Show HN: I built a reference site for the recurring hard problems in software Hi HN, I&#x27;ve been working on this for a while and it was hard to decide when to stop, either on the way information is presented or when to stop with adding entries. It&#x27;s not meant as a blog, but rather as a reference that keeps growing.<p>Link: <a href="https:&#x2F;&#x2F;thehardparts.dev" rel="nofollow">https:&#x2F;&#x2F;thehardparts.dev</a><p>Currently I&#x27;ve created 4 main section:<p>- Failure Modes: ways project go wrong<p>- Red Flags: early signals that are worth taking seriously<p>- Tech Decisions: common and not so common trade-offs for hard choices<p>- Playbooks - guided approach for situations that repeat<p>I&#x27;ve also focused on creating links between them to show how connected many things are: a red flag usually precedes a failure mode, which might connect to a forced decision, etc.<p>Some entry points to give you an idea:<p>- The Invisible Deadline: a date that exists socially but not explicitly enough to manage honestly<p>- Eveyone Asks The Same Person: when one person becomes the default source of truth<p>- Build a Practical Rollback Strategy: how to build a reliable rollback strategy<p>It has 151 entries across the 4 sections.<p>Curious what you think about the content, format, grouping.

[Other] Show HN: Building a SQL analyst agent from scratch I built a SQL analyst agent based on a simple idea: generating SQL is not the same as doing analysis.<p>Most text-to-SQL tools stop at producing a query. But real analysis is iterative. You explore the schema, run queries, adjust, and refine.<p>This project tries to model that loop instead of treating a query as the final output.<p>I wrote about the approach, challenges, and tradeoffs here: <a href="https:&#x2F;&#x2F;raminmousavi.dev&#x2F;blog&#x2F;building-a-sql-analyst-agent" rel="nofollow">https:&#x2F;&#x2F;raminmousavi.dev&#x2F;blog&#x2F;building-a-sql-analyst-agent</a><p>Github repo: <a href="https:&#x2F;&#x2F;github.com&#x2F;raminious&#x2F;sql-analyst-ai-agent" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;raminious&#x2F;sql-analyst-ai-agent</a>

[Other] The cost math behind routing Claude Code through Ollama (~90% cut)

[Other] The Prompt API

[Testing] EvanFlow – A TDD driven feedback loop for Claude Code

[Other] Show HN: The Unix Magic poster, annotated (updated) This is a site that maps the references on Gary Overacre&#x27;s 1980s UNIX Magic poster to short write-ups with sources. I posted an earlier version about a year ago [1]. Since then I rewrote some of the annotations, added deep-linking to individual markers and a frame&#x2F;sidebar view, gave the site a terminal-style redesign, and fixed historical inaccuracies (daemon etymology, nroff origin, B language vs. Multics, etc.).<p>Contributions and comments welcome; each marker is a GitHub issue.<p>site: <a href="https:&#x2F;&#x2F;unixmagic.net" rel="nofollow">https:&#x2F;&#x2F;unixmagic.net</a><p>[1] <a href="https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=43019136">https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=43019136</a>

[Other] Show HN: Matrirc – run irssi in 2026, talk to people on Matrix This solves no real problem — Element works, there&#x27;s already a Matrix-to-IRC bridge running on half the FOSS networks, and probably nobody under 30 has opened irssi voluntarily this decade.<p>I wrote it anyway because I miss Esc 4 and clunky window-split commands.<p>Matrirc is a local IRC server that speaks Matrix on the back. Point irssi at localhost:6667, log in with Matrix creds, rooms show up as channels.<p>brew tap pawelb0&#x2F;tap brew install matrirc

[Other] Show HN: AI memory with biological decay (52% recall) Most RAG setups fail because they treat memory like a static filing cabinet. When every transient bug fix or abandoned rule is stored forever, the context window eventually chokes on noise, spiking token costs and degrading the agent&#x27;s reasoning.<p>This implementation experiments with a biological approach by using the Ebbinghaus forgetting curve to manage context as a living substrate. Memories are assigned a &quot;strength&quot; score where each recall reinforces the data and flattens its decay curve (spaced repetition), while unused data eventually hits a threshold and is pruned.<p>To solve the &quot;logical neighbor&quot; problem where semantic search misses relevant but non-similar nodes, a graph layer is layered over the vector store. Benchmarked against the LoCoMo dataset, this reached 52% Recall@5, nearly double the accuracy of stateless vector stores, while cutting token waste by roughly 84%.<p>Built as a local first MCP server using DuckDB, the hypothesis is that for agents handling long-running projects, &quot;what to forget&quot; is just as critical as &quot;what to remember.&quot; I&#x27;d be interested to hear if others are exploring non-linear decay or similar biological constraints for context management.<p>GitHub: <a href="https:&#x2F;&#x2F;github.com&#x2F;sachitrafa&#x2F;cognitive-ai-memory" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;sachitrafa&#x2F;cognitive-ai-memory</a>

[Other] Beads - A memory upgrade for your coding agent