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ミーミューズ限定の動画投稿しました💜 徐々にファンティアからミーミューズに移行することになったのでよろしくお願いいたします🙇‍♀️‼️ #ミーミューズ# #Mimuse#

こんな感じでもうたくさん投稿してるよ🩷Mimuse限定の写真や動画ばかり！！！！ ぜひ見てくれたら嬉しいです😍🥰 👇👇👇

【独占インタビュー】 希島あいり、表舞台から離れる真相 📸写真 駆け抜けた日々と今後について 「私自身、この15年間、本当に幸せでした」 #ミーミューズ# @airi_kijima @mdpr_mi_muse

Samsung denies wrongfully using Dua Lipa’s image on their packaging following her $15 million lawsuit filing: “The image was used only after receiving explicit assurance from the content partner that permission had been secured, including for the retail boxes. Given this assurance, we deny any allegations of intentional misuse.”

Continuing the series on how I design skills in Waza, this one is about how I built /check, the code review skill. The starting point is simple. A model saying “it’s done” does not mean it is actually done. It can still leave behind broken logic, non-existent pieces, hidden regressions, or unresolved risks. In my experience building agents, giving the model a concrete checklist to verify completion works far better than simply asking it to “double check.” So /check was never designed as one giant all-in-one reviewer. It is a review orchestration system with clear division of responsibility. The main SKILL.md acts as the lead reviewer, handling review levels and process control. Under agents/, there are independent specialists such as a security reviewer and an architecture reviewer, each focused on its own domain. Which specialist gets involved is decided by an activation rule set, not the keyword matching approach many people use. The review tiers are also intentional. For changes under 100 lines, it runs a fast review. For changes between 100 and 500 lines, it brings in specialists when needed. For changes above 500 lines, it activates the full review path and adds an adversarial testing round. That round looks for failure modes from four angles: broken assumptions, problems that appear only under combined failures, errors in cross-layer integration, and abuse or misuse scenarios. Findings are then handled in four levels. Safe and obvious fixes can be applied directly. Issues that are mostly clear but still worth confirming are packaged for you to review. Cases that require judgment are escalated to you. Lower-priority observations are still surfaced, but /check does not interrupt you for every minor issue, and it does not overstep into changing behavioral logic on its own. There is also one hard rule: if verification has not run, the task is not complete. /check includes a probing script that detects project types such as Cargo, TypeScript, and Python, then runs the appropriate validation flow. If it cannot detect the project type, it fails explicitly instead of pretending everything passed. The result is something closer to an experienced technical reviewer: different strategies for different change sizes, explicit specialist involvement, and a stronger definition of what “done” actually means. I just tried to distill those engineering habits into a simple and reusable skill inside Waza. And if you have better ideas for code review workflows, I’d love contributions to Waza. PRs are welcome.

As AI gets better at holding natural conversations, we need to understand how these interactions impact society. We’re sharing new research into how AI might be misused to exploit emotions or manipulate people into making harmful choices. 🧵

Watch out for people who argue against something whenever they can find something--anything-- wrong with it, without properly weighing all the pluses and minuses. Such people tend to be poor decision makers. #principleoftheday#

ミーミューズの雑誌 「GIRLS Graph」の撮影をしてきたよ💕 どんな感じに仕上がってるか 楽しみにしててね🥰😘✨✨ #ミーミューズ# @mdpr_mi_muse

モデルプレスさんのスタジオで ファンクラブ撮影💕 新衣装での投稿楽しみにしててね🫶💖 さきちぃのファンクラブは こちら😘👇入会待ってます😍 #ミーグラム# @mi_glamu @mdpr_Mi_muse