site: reviews — ChompSaw, Osaurus (graduate from finds)

daily-finds.log.md

@@ -1563,3 +1563,23 @@ Items referenced:
   - retractable-cable-luggage-lock
 
 No weekly-catch bundle this run: today's shortlist is a fresh capture, not finds languishing for weeks; a week's-catch can run next cycle if shortlisted finds accumulate unbundled. No second cluster run: yesterday (2026-07-03) already ran one, and the shortlisted-unbundled pool is not near the ~25 threshold.
+
+## 2026-07-04 — review: chompsaw-power-tool-for-kids
+
+Graduated from find captured 2026-07-04, source: MoMA Design Store.
+Hero: hero.jpg — copied from the find's clean MoMA studio shot (no better maker/lifestyle shot warranted).
+Category: making (new — no existing category fit a kids' maker/craft power tool).
+Fact-check: Resolved the age discrepancy to ages 3+ per the maker's own current certification (chompshop.com recertified 8+ → 5+ → 3+; MoMA lists 3+). Amazon bundle title still shows the outdated "Ages 5+" — corrected in the review. Verified the oscillating hole-punch nibbler mechanism (metal safety guard, not a blade), the ~3mm cardboard limit (also cuts felt/foam/thin fabric, not metal), $249 (MoMA member $224.10), and safety standards ASTM F963 / CPSIA / CCPSA / EN71 / EN IEC 62115 / AS-NZS ISO 8124. Real product (Shark Tank S16, MoMA-carried) — passes the bar.
+Amazon: carried B0DYRF6D4C.
+
+## 2026-07-04 — review: osaurus
+
+Graduated from find captured 2026-07-04, source: r/macapps.
+Hero: reused find hero.png (dark-mode chat UI screenshot from osaurus.ai) — real and clean, no better shot needed.
+Category: ai (new — local-AI Mac apps are likely to recur for this audience; category pages auto-generate).
+Fact-check: passes the bar; active canonical repo osaurus-ai/osaurus (6.7k stars, v0.21.5). Confirmed MIT, native Swift/MLX on Apple Silicon, the agent layer (memory / tools / schedules + folder watchers), and the on-device privacy filter (OpenAI's open privacy-filter ~1.5B via MLX + regex, stable placeholder substitution, fail-closed). TechCrunch coverage confirmed (2026-05-15). Confirmed the Dinoki "AI-powered Clippy" origin and the dinoki-ai → osaurus-ai repo move. Corrected the find's "Python bindings like Ollama/LM Studio" framing (both wrap llama.cpp; Osaurus is native MLX and can also use them as backends). Canonical link set to osaurus.ai.
+Amazon: n-a (software).
+
+## 2026-07-04 — pick of the day: chompsaw-power-tool-for-kids
+
+Chosen over osaurus for tile legibility and breadth: a bright, clean studio product shot reads instantly at grid size, and the virtue — a power tool a three-year-old can't hurt themselves on — lands in one line for any visitor. osaurus's dark chat-UI screenshot and developer-leaning appeal are narrower; it stays a strong review, just not the homepage hero. (Previous pick, kartell-componibili, has had its day since 2026-07-03.)

src/content/find/2026/07/chompsaw-power-tool-for-kids/index.mdx

@@ -7,6 +7,7 @@ link: "https://store.moma.org/products/chompsaw-power-tool-for-kids"
 linkText: "store.moma.org"
 source: "MoMA Design Store"
 amazonLink: "https://www.amazon.com/dp/B0DYRF6D4C"
+promotedTo: chompsaw-power-tool-for-kids
 topics: [gifts]
 tags: [kids, tools, design]
 description: "A cardboard-cutting power tool for kids 3+ that skips blades and spinning parts for a safe, rapid hole-punch action."

src/content/find/2026/07/osaurus/index.mdx

@@ -6,6 +6,7 @@ shortlist: true
 link: "https://github.com/osaurus-ai/osaurus"
 linkText: "github.com"
 source: "r/macapps"
+promotedTo: osaurus
 topics: [macos-apps]
 tags: [ai, open-source, local-llm, privacy]
 description: "MIT-licensed Swift app that runs local LLMs natively on Apple Silicon with memory, tools, and scheduling, plus an on-device privacy filter for cloud calls."

src/content/reviews/chompsaw-power-tool-for-kids/index.mdx

@@ -0,0 +1,30 @@
+---
+name: "ChompSaw Power Tool for Kids"
+subtitle: "A finger-safe benchtop power tool that nibbles cardboard into 3D builds"
+date: 2026-07-04
+category: making
+tags: [kids, tools, design, cardboard, stem]
+link: "https://store.moma.org/products/chompsaw-power-tool-for-kids"
+linkText: "store.moma.org"
+amazonLink: "https://www.amazon.com/dp/B0DYRF6D4C"
+description: "A kid-safe benchtop power tool that cuts cardboard with an oscillating hole-punch action instead of a blade — certified for ages 3+, and engineered around a child's hands rather than shrunk down from an adult tool."
+source: "MoMA Design Store"
+fromFind: chompsaw-power-tool-for-kids
+---
+
+import { Image } from 'astro:assets';
+import hero from './hero.jpg';
+
+<Image src={hero} alt="The ChompSaw — a compact orange-and-white benchtop power tool with a cutting head, a pull-out dust drawer, and a flat cutting deck, engineered for a child to feed cardboard into." />
+
+*The benchtop unit — a cutting head over a flat deck, with a pull-out drawer that catches the nibbled-out scraps.*
+
+> A benchtop power tool that lets a small child cut cardboard by feeding it into a high-speed hole punch rather than past a blade. It is one of the rare kids' products engineered from scratch around the danger it removes, not scaled down from an adult tool that still has the danger in it.
+
+The ChompSaw is not a scaled-down bandsaw. Where a bandsaw or rotary cutter has an exposed edge that keeps cutting whatever touches it, the ChompSaw works "like a precision hole punch that runs at high speed": a small punch oscillates up and down inside a metal safety guard, nibbling out tiny half-moon bites of cardboard while a pull-out drawer catches the confetti. The trick is that the mechanism only bites material thin and flexible enough to be pushed under the guard — a fingertip, a sleeve, or a lock of hair is too thick and too stiff to be drawn in, so the tool is safe to touch while it's running. That single design decision is the whole product.
+
+The problem it solves is specific and real: cardboard is the best free building material a kid has, and the tools for cutting it are all bad for a child's hands. Scissors can't turn a curve or cut a clean interior window, and box cutters are exactly what you don't hand a five-year-old. The ChompSaw lets a child steer a sheet of corrugated freely in any direction — curves, notches, interior cutouts — at a bench, which is what turns a flat box into an actual 3D structure rather than a taped-together approximation. It ships with a hole-punch attachment and a scoring tool for clean folds, so the same station handles the three operations cardboard building actually needs: cut, pierce, crease.
+
+What earns its place is that the safety is certified, not just claimed. It appeared on *Shark Tank* (Season 16) and is carried by the MoMA Design Store, but the load-bearing detail is the testing: the maker had it independently assessed against ASTM F963 and CPSIA in the US, CCPSA in Canada, EN71 and EN IEC 62115 in the UK and EU (CE and UKCA marked), and AS/NZS ISO 8124 in Australia. It cuts more than boxes, too — felt, craft foam, and thin fabric all go through it — while metal is explicitly off-limits.
+
+The honest limits are worth stating plainly. First, the age rating: the find and the MoMA listing say ages 3+, and that is now correct — the maker recertified the tool from its original 8+, to 5+, and finally to 3+ after testing confirmed it met the youngest-child standard. The Amazon listing for the bundle still carries the older "Ages 5+" label, so ignore that number; the maker's own current certification and MoMA both say 3+ (with adult setup and supervision, as with any power tool). Second, it is genuinely cardboard-scaled: it handles material up to roughly 3mm thick — about two stacked pennies — and thicker double-wall board has to be scored and packed down first, or it won't feed. And third, the price is real: $249 at MoMA (members $224.10), which is a serious sum for a single-material craft tool. It is a lot to spend on something that eats boxes — but there is nothing else that lets a three-year-old do it safely, and that is the entire point.

src/content/reviews/osaurus/index.mdx

@@ -0,0 +1,26 @@
+---
+name: "Osaurus"
+subtitle: "Open-source local AI for your Mac — native Swift, with an on-device privacy filter for cloud calls"
+date: 2026-07-04
+category: ai
+tags: [ai, open-source, local-llm, privacy, macos, agents]
+link: "https://osaurus.ai"
+linkText: osaurus.ai
+description: "A free, MIT-licensed native Swift app that runs local LLMs on Apple Silicon through Apple's MLX — plus an agent layer with memory, tools, and scheduling, and an on-device filter that scrubs personal data before any cloud call."
+source: "r/macapps"
+fromFind: osaurus
+---
+
+![Osaurus on macOS: a dark chat window with a model selector and an ongoing conversation.](./hero.png)
+
+*Local by default: a chat that runs on your own machine, no account, no internet required.*
+
+> Osaurus is a free, MIT-licensed Mac app that runs local LLMs natively on Apple Silicon — built directly on Apple's MLX rather than wrapping a cross-platform engine — and layers on an agent runtime the usual local tools skip: persistent memory, native app tools, and background schedules. Its standout is the part the find led with: when you opt into a cloud model, an on-device filter scrubs names, emails, and secrets out of the request before it leaves the Mac.
+
+What Osaurus actually is takes a second to place, because it's two things at once. Underneath is a native local-inference runtime — Swift and SwiftNIO, no Electron — that runs models like Gemma, Qwen, Llama, and GPT-OSS on Apple Silicon and exposes them through OpenAI-compatible endpoints. On top sits what its makers call a harness: a control layer that routes between local and cloud models behind one interface, with shared memory and tools. It comes from Dinoki Labs — founders Terence Pae (ex-Tesla, Netflix) and Sam Yoo — and grew, per TechCrunch's May 2026 write-up, out of Dinoki, a Clippy-style desktop AI companion, once the team decided a private, own-your-tokens assistant was the more interesting product. So the find's "novelty companion origin" framing is real, not folklore. It is MIT-licensed and free, with no subscription or usage caps.
+
+The find pitched it as running "natively in Swift on Apple Silicon rather than through Python bindings like Ollama or LM Studio," and the spirit is right but the detail needs correcting: Ollama and LM Studio aren't Python bindings — both wrap the cross-platform C++ engine llama.cpp. The genuine difference is that Osaurus is built directly on MLX, Apple's own on-device ML framework, and ships a curated library of MLX-optimized quantizations tuned for M-series chips. And it isn't strictly either/or — Osaurus can also connect to Ollama and LM Studio as local backends, or to OpenAI, Anthropic, Gemini, and others in the cloud. What it adds over a plain model server is the agent layer those lack: a three-tier memory (identity, pinned facts, per-session episodes, consolidated by salience), 20-plus native tool plugins spanning Mail, Calendar, Browser, Git, Filesystem, Vision, and spreadsheet/deck formats, and background schedules plus folder watchers that trigger agents on file changes.
+
+The privacy filter is the detail that earns the write-up, and it holds up on inspection. When a request is bound for a cloud model, Osaurus runs it first through an on-device PII detector — OpenAI's open `privacy-filter` model (about 1.5B parameters, run locally via MLX) backed by regex for structured secrets — and rewrites names, emails, phone numbers, addresses, account numbers, SSNs, credit-card numbers, and API keys or tokens into stable placeholders like `[PERSON_1]` before the request leaves the machine; replies come back with the placeholders restored. It's fail-closed: if a post-scrub scan still spots leakage, the send is blocked rather than sent anyway. That's a real, specific mechanism, not marketing — worth stating plainly because the find could have been overselling it, and it isn't.
+
+The honest limits are the ones you'd expect of a young, local-first tool. It is Apple Silicon only — no Intel Macs, no Windows or Linux — and local models cost unified memory: small quantized models run comfortably on a modest Mac but trail frontier cloud models on hard reasoning, while the strongest local models want a lot of RAM. The project is moving fast (it was on 0.21.5 the day before this review, with 400-plus releases behind it), so expect churn and rough edges more than a settled 1.0. And the privacy filter, real as it is, is a mitigation rather than a guarantee — a 1.5B detector can miss context-dependent PII, and it only matters at all when you opt into the cloud; run everything locally and nothing leaves the Mac to filter in the first place. For a Mac user who wants local models with an actual agent around them, and a considered answer to the "but I sometimes need the cloud" problem, it's an unusually complete take on the idea.