Japanese-language skill for startup CTOs, PMs, and contract developers. Drop a one-line app idea — get five aligned definition docs in Japanese: 要求定義書 (Requirements), 要件定義書 (Functional Spec), 技術定義書 (Technical Design), 工程定義書 (Project Plan), 品質定義書 (Quality Plan). Each doc is internally consistent. Mermaid diagrams embedded automatically. Pre-tuned for Cloud Run / Next.js / Python stacks. Output is Markdown, ready to paste into Notion, GitHub, or Cursor. Cuts a week of spec work to under an hour.
Over 5,000 ADA accessibility lawsuits were filed in the US last year. 64% targeted businesses under $25M revenue. Most started with an automated scan — the same kind this agent runs on your site. Enter a URL. Get a risk report: which WCAG 2.2 AA failures a plaintiff's scanner would flag, ranked by lawsuit likelihood, with the exact fix for each. Covers contrast, alt text, labels, ARIA, focus order, and touch targets. Not a compliance certificate. A radar for what's coming.
Finds cultural mistakes, stereotypes, romaji and seasonal errors in Japan-themed English copy, with a fix for each. Works on social posts, blogs, product and marketing copy before you publish. Advisory, not a certification.
Personal JLPT tutor (N5–N1): generates an original daily Japanese practice quiz as interactive HTML, grades your pasted answers, tracks weak points over time, and promotes you level by level. Coaching language auto-matches yours (zh-TW / zh-CN / en / ja).
Paste your work history and the target job description. This agent produces a Japanese resume (職務経歴書), an ATS-optimized English resume, a bilingual cover-letter pair, an ATS Fit Score (0-100) showing how well you match, and the Top 10 missing keywords to add before submitting. Runs locally, no data sent. Like this tool? ExpertPanel gives you a scored review with specific improvement suggestions from 3 AI experts.
Turn incomplete Jira tickets, JSM requests, PRDs, User Stories, and meeting notes into requirements that Engineering can build, QA can test, and Product can accept. Automatically identify requirement gaps, business rules, permissions, validations, UI/API behaviors, exceptions, and edge cases, then generate User Stories, Given/When/Then Acceptance Criteria, PM Checklists, QA Test Cases, risk analysis, and a Requirement Readiness Score based on the selected mode.
Turn factory data into a bottleneck, capacity, and layout-risk decision.
Use when your Japanese draft still reads AI-written. For bloggers, PR teams, marketers, and students: paste the text and get a human-sounding rewrite, plus a diff of every AI tell removed. It replaces vague AI phrasing — 浮き彫りになった, 多面的な, 〜ではないでしょうか, 今後の展開が期待される — with concrete facts and one clear voice. Facts are never invented or changed, only the wording. Output = the rewritten full text + a change log of what was fixed.