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概要と使いどころ
Vet a perf measurement (limiter, tuning, limits, errors, repeatability, relevance, and whether the work happened) before you report or act on it. Use when you run a benchmark or report a speedup or regression you measured.
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Intelligently organizes your files and folders across your computer by understanding context, finding duplicates, suggesting better structures, and automating cleanup tasks. Reduces cognitive load and keeps your digital workspace tidy without manual effort.
日本語の概要は準備中です。原文の説明を表示しています。
Intelligently organizes your files and folders across your computer by understanding context, finding duplicates, suggesting better structures, and automating cleanup tasks. Reduces cognitive load and keeps your digital workspace tidy without manual effort.
日本語の概要は準備中です。原文の説明を表示しています。
Apply before you trust, report, or act on a number you measured: a speedup, a regression, a throughput, a latency, or an eval result. Find what limits it, and rule out that it measured something other than the work you think.
日本語の概要は準備中です。原文の説明を表示しています。
Vet a perf measurement (limiter, tuning, limits, errors, repeatability, relevance, and whether the work happened) before you report or act on it. Use when you run a benchmark or report a speedup or regression you measured.
日本語の概要は準備中です。原文の説明を表示しています。
Use when found gap or repetative issue, that produced by you or implemenataion agent. Esentially use it each time when you say "You absolutly right, I should have done it differently." -> need create rule for this issue so it not appears again.
日本語の概要は準備中です。原文の説明を表示しています。
Extract a written voice profile from your own prior papers, then use it to keep new drafts sounding like you. Reads a corpus one document at a time via subagents, produces a reusable profile on disk (lexicon, sentence rhythm, how you open and close, hedging habits, deliberate quirks), and audits a draft against it. Use when the user says "make this sound like me", "match my voice", "profile my writing", "why does this draft not sound like my papers", or before drafting prose that will carry their name. The positive counterpart to /humanize, which only detects AI tells.
日本語の概要は準備中です。原文の説明を表示しています。
Prove that the file you are about to send, publish, or hand off IS the thing you mean — before it leaves your hands. Rebuild from source, check integrity, diff the derived artifact against its source, and require the recipient to echo what they received. Use before sending a paper/PDF for review, shipping a release or replication package, handing files to a coauthor or collaborator, uploading anything to an external reviewer or model, or publishing. Prevents an entire review/QA cycle from being spent on defects that exist only in the artifact, not in the work.
日本語の概要は準備中です。原文の説明を表示しています。
Turn an incoming set of findings — from an AI reviewer, a referee report, a code review, a linter, or a second model — into verified fixes, without letting a confident misread damage correct work. Every finding is a CANDIDATE until checked against the actual source. Use whenever you receive review comments, audit findings, or a critique you did not write yourself, especially when the reviewer is a model or when the volume is too large to check by feel.
日本語の概要は準備中です。原文の説明を表示しています。
Generate high-CTR YouTube thumbnails using Nano Banana 2 via the Arcads external API. Handles reference image upload, character likeness alignment, proven CTR-tested prompt formulas, and parallel batch generation. Use when the user asks to create a YouTube thumbnail, video thumbnail, A/B test thumbnail variations, or refers to thumbnail design with their face, brand assets, or product photos.
日本語の概要は準備中です。原文の説明を表示しています。
Extract transcripts from YouTube videos via the YouTube caption system
日本語の概要は準備中です。原文の説明を表示しています。
End-to-end orchestrator: from a business idea, app idea, or existing app to running Azure deployment with cost estimates and pre-deploy approval. Analyzes your app, auto-detects the right Azure services, scaffolds infrastructure code, and deploys — tailored to your app, not a template. Handles moving existing apps to Azure without rewriting or with minimal changes. WHEN: bring your app to Azure, plan my app, cost to run, is my code ready to deploy, deploy my app to the cloud, deploy all my services, what Azure services do I need, plan my Azure deployment, deploy my new app to Azure, one-click deploy, I have an app and want it on Azure, migrate my app to Azure, help me get started, build an app, no code yet, starter project. DO NOT USE FOR: use azd for deployment(use azure-deploy), optimizing existing costs (use cost-optimization), code readiness checks only (use azure-app-onboard-prereq).
日本語の概要は準備中です。原文の説明を表示しています。
Fetch existing YouTube transcripts/subtitles or archive spoken video content as text, and download YouTube videos/audio or HLS streams (m3u8) with yt-dlp and ffmpeg. Use for transcript/subtitle retrieval, text-first video archiving, video/audio downloads, protected streams with authentication headers, and download failures including nsig, 403 or browser-cookie issues.
日本語の概要は準備中です。原文の説明を表示しています。
Scan a contract you're about to sign in plain language — surface the clauses that could bite you, what they mean, and what to question or renegotiate. Use when asked to check this contract before I sign, what am I agreeing to, are there red flags in this agreement, or explain this contract's risky bits. Produces a plain-English flag list of the risky/unusual clauses (auto-renewal, lock-in, liability, IP, termination, fees), what each means for you, questions to ask, and suggested changes — flagging when it's important enough for a lawyer. Not legal advice.
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Handle a dispute with a contractor — unfinished work, poor quality, overcharging, or a no-show — with a path that protects your money and your options. Use when asked to deal with a contractor dispute, my contractor did bad work / won't finish / overcharged, or how to get a builder to fix their work. Produces a read on your position (contract, payments, evidence), a firm-but-professional communication and demand path, documentation and payment-leverage guidance, and escalation options (mediation, licensing board, chargeback, small claims) — flagging that it's not legal advice.
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Spot a bad client before you sign — the warning signs of the projects that turn into unpaid, scope-creeping nightmares, and how to screen, price, or decline them. Use when asked is this client a red flag, should I take this client, screening a difficult client, or how to avoid bad clients. Produces a read on the warning signs present (haggling, vagueness, disrespect, urgency, unrealistic expectations), what each predicts, screening questions to ask before committing, protective terms if you proceed anyway, and how to decline gracefully — so you avoid the clients who cost more than they pay.
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Work out whether you're eligible for a class-action settlement or refund program — and actually file the claim before the deadline. Use when asked am I owed money from a settlement, is there a class action for [product/company], how do I claim a settlement, or did I qualify for that refund. Produces a way to check for relevant settlements, an eligibility read against the class definition, the proof you need and how to file, deadline tracking, and honest expectations on payout size — plus how to avoid fake-settlement scams. Not legal advice.
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Respond to a brand or executive impersonation incident — deepfaked executives, cloned support lines, fake apps, spoofed domains, or AI-generated scam content wearing your name. Use when a deepfake of a leader is circulating, customers report a fake version of your product or support channel, or to prepare the impersonation playbook before it happens. Produces an incident response: verification protocol, takedown sequencing by platform, customer and public communications, and the hardening plan. For general crisis comms use press-release/pm-crisis skills; for security incidents inside your systems use security-incident-response.
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Build a realistic plan to change careers — mapping your transferable skills, the real gaps, and a bridge that doesn't require torching your income overnight. Use when asked to help me change careers, career pivot plan, how do I switch to [field], or I want a new career but don't know how. Produces a transferable-skills map, an honest gap analysis to the target role, a staged bridge (skill-building, positioning, side-door entry), a financial-runway reality check, and a narrative that reframes your background as an asset — not a starting-from-zero story.
日本語の概要は準備中です。原文の説明を表示しています。
Surface the hidden assumptions a plan or belief rests on, then test what happens when each one is wrong. Use when asked what am I assuming here, check my assumptions, what if I'm wrong about, or stress-test my thinking. Produces the unstated assumptions your conclusion depends on (ranked by how load-bearing they are), a flip of each to see which one breaking would change everything, and the cheapest way to check the riskiest ones — because the assumption you didn't know you were making is what sinks plans.
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Publish 'how to work with me' as a literal API spec — endpoints (what to ask me for and what you'll get back), rate limits (meeting and interrupt tolerance), error codes (what happens when you surprise me Friday 5pm), auth (how to earn trust), and a changelog. Use when onboarding to a new team, when a new manager or report arrives, for a team working-styles session, or 'write my README/user manual'. Produces a personal API spec that's genuinely funny and secretly the best onboarding doc on the team.
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Act as a body-double for a work session — a present, low-pressure companion that keeps you accountable and moving through the task without doing it for you. Use when asked be my body double, keep me company while I work, help me focus on this task, or I work better with someone there. Produces a session structure (goal, time block, check-in cadence), gentle presence and momentum nudges at intervals, distraction rescue when you drift, and an end-of-session acknowledgment — recreating the focus that comes from someone just being there.
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Check whether a raise, more hours, or a new job could cost you more in lost benefits than you gain — the 'benefits cliff' — before you accept it. Use when asked will a raise hurt my benefits, benefits cliff, if I make more will I lose my food stamps or medicaid, or should I take more hours. Produces a plain map of which benefits phase out at what income (and which cut off suddenly vs. taper), a rough read on whether a specific income change helps or hurts net, the ones with hard cliffs to watch (childcare, Medicaid, housing), the moves that soften a cliff, and where to get a real benefits screening. Not financial/benefits advice; points to a benefits counselor.
日本語の概要は準備中です。原文の説明を表示しています。
Build the context an AI needs to do a task well — the background, constraints, examples, and format it can't guess — so you get a great result on the first try instead of a generic one you have to keep correcting. Use when asked why does AI give me generic answers, how do I give AI better context, my AI results are mediocre, or how do I get it right the first time. Produces the specific context this task needs (who/what/constraints/examples/format), a reusable primer you can paste ahead of the request, the difference between a starved prompt and a well-briefed one, and what to leave out — turning vague back-and-forth into a strong first result.
日本語の概要は準備中です。原文の説明を表示しています。