「what」の検索結果

Verified lookup pack for crouton's schema→CRUD generation domain — the fieldsFile JSON format, the complete field-type catalog with aliases, the naming contract, the exact artifact list one generate run produces, the seed/default-layout pipeline, dialect defaults, and rollback semantics. Use when writing or reviewing a collection schema, when asking "what field types exist / what does `crouton config` actually generate / where did this file name come from / why did I get a pg schema", when a generated file's name or path doesn't match the docs, or when removing/regenerating a collection. Trigger phrases — "what field types are supported", "schema JSON format", "what files does crouton generate", "naming convention for collections", "rollback a collection", "dialect default". The generation WORKFLOW (steps + sign-off gates) lives in the `crouton` skill — this is the reference it doesn't carry.

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。

Show what this NanoClaw instance can do — installed skills, available tools, and system info. Read-only. Use when the user asks what the bot can do, what's installed, or runs /capabilities.

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。

Turns the text of a regulatory change (new regulation, amendment, rule, guidance or standard revision) into a DRAFT impact note: what changed against the prior text where supplied, who is affected as the text scopes it, an obligations table with dates and owners to confirm, and open interpretation questions for legal. States only what the text says; the rest is UNKNOWN. Use when the user asks to "brief legal on this new regulation", "list what we must do by when under this amendment", "compare the new standard with the version it replaces", "turn this directive into an obligations table" or "what does this rule mean for us". Do not use for assessing existing controls against a requirement set, use controls-gap-pack instead; for gapping a policy against a standard, use policy-gap-review. Drafts for human review; never approves, authorises or signs off.

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。

Sweeps the last 24 hours of email, chat messages and meeting transcripts for commitments in both directions, what the user promised others and what others promised the user, reconciles them against a running commitments ledger (open, done, overdue), lists overdue items first and returns the updated ledger plus a proposed task list as Markdown for the user to save. Use when the user asks to "check my commitments", "what did I promise", "what am I owed", "did anything slip" or "run the commitment sweep". Do not use for a general morning summary of mail, calendar and mentions, use custom-daily-brief instead. Drafts for human review; never approves, authorises or signs off.

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。

Refresh WhatsApp text into an Obsidian vault (data layer, dashboard, group labels, contact notes). Text only, never downloads media, and pulls the recent window the live companion bridge exposes rather than a full multi-year archive. Semi-automatic by design: it drives the live bridge and needs the phone nearby. Triggers: "/whatsapp-sync", "pull whatsapp".

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。

Answer 'what happened on that day' instantly from a daily ledger that night robots assemble from free traces (git commits, session logs, vault writes, bus messages), with zero LLM tokens spent on retrieval. Use when asked what was done yesterday, on a given date or during a week. Triggers: /ledger, what did we do yesterday, what happened on <date>, show the day, daily summary.

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 the user asks to "map what our surfaces say today", "inventory our current messaging", or "find the gap between what we say and what we mean"; produces the narrative baseline — a surface-by-surface inventory of what every owned touchpoint (homepage, pricing, docs, decks, social bios, email footers) claims RIGHT NOW, each line labeled Measured / User-provided / Estimated, plus a per-surface gap read vs the intended message and the drift-baseline snapshot the Evaluate phase measures future drift against. Not for authoring the canon — use message-system-architect; not for scoring the surfaces or running the vetoes — use narrative-quality-auditor. 现状叙事盘点/各触点口径/意图差距/漂移基线

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 the user asks about finding the best, top, or recommended model for a task, wants to know what AI model to use, or wants to compare models by benchmark scores. Triggers on: "best model for X", "what model should I use for", "top models for [task]", "which model runs on my laptop/machine/device", "recommend a model for", "what LLM should I use for", "compare models for", "what's state of the art for", or any question about choosing an AI model for a specific use case. Always use this skill when the user wants model recommendations or comparisons, even if they don't explicitly mention HuggingFace or benchmarks.

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。

Survey the whole tdmcp project and produce a prioritized list of NEW features it could implement — across artist controls, CLI/DX, AI/LLM integration, and TouchDesigner depth. Use whenever the user wants to brainstorm, discover, survey, list, or audit what features/tools/effects/controls/commands/prompts/capabilities tdmcp *could* add, asks 'what could we build / what's missing / what are the opportunities / ideas for the project', or wants a feature backlog or gap analysis. Also for follow-ups: re-run, refresh, update, re-survey, deepen, or re-prioritize the backlog, or survey just one surface (e.g. 'CLI ideas only'). This is the IDEATION harness — it produces a list to decide from; it does NOT build. When the user has already chosen a feature and wants it implemented/shipped/added, use tdmcp-pipeline instead.

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 whenever a question is about what the specification says or does — "what happens if", "can X do Y", "which errors can this return", "what does the screen show for", "what fields does this command take", "is there an operation for". Answers by running the Lean executable spec (scenarios, commands,

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。

Help the user understand the current topic visually with concise diagrams, code-shape sketches, and focused HTML artifacts. Use when the user asks to show / diagram / visualize / sketch / illustrate what is going on, asks "what does this look like", "how does this flow", "show me the structure", or in Japanese 図で見せて / 図解して / 図にして / 構造を見せて / フローを見せて / 全体像を見せて / どうつながってるか見せて. Also use it proactively when an explanation is running long and a call tree, file tree, component tree, diff, Mermaid diagram, or a small HTML artifact would land faster than prose.

Help users discover what to build on Stellar. Use when a user says "what should I build on Stellar", "Stellar app ideas", "I want to build on Stellar but don't know what", "Stellar startup ideas", "find me a Stellar project idea", "I'm new to Stellar and want to build something", or "what's hot on Stellar right now". Interviews user sharply, then proposes ranked ideas grounded in real ecosystem gaps from the LumenLoop 728-project database and current SCF funding patterns.

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 ideas that don't sound logical, then validate them with cheap behavioural experiments — Rory Sutherland's 'the opposite of a good idea can be a good idea' plus revealed-preference testing. Use when the obvious/logical solution is saturated and the user wants genuinely different options, asks 'what's a creative/unconventional angle', 'how do we stand out', 'should we run a test/experiment', 'how do we know what people actually want', or is about to trust a survey/focus group. Covers deliberate inversion of the obvious move, why stated preferences lie, and designing small reversible experiments that watch behaviour. Inspired by Rory Sutherland's *Alchemy*. Routed to from psycho-logic. 日本語の相談（「競合と同じ案しか出ない」「アンケートは好評なのに売れない」「思い切った案を安く試したい」）にも使う。中文咨询（“只能想出和竞品一样的方案”“问卷好评却卖不动”）也适用。

Change what something MEANS before you change what it IS — Rory Sutherland's cheapest lever. Use when a product, price, feature, or message is objectively fine but feels cheap, generic, boring, overpriced, or unjustified; when the user says 'how do we make this feel more premium/valuable/exciting', 'people don't get why it's worth it', 'how do we reposition/rename/repackage this', or wants to raise perceived value without changing the product or cutting the price. Covers renaming, recategorising, mental accounting (price framing), creating artificial value, and context-shifting. Inspired by Rory Sutherland's *Alchemy*. Routed to from psycho-logic. 日本語の相談（「高いと言われる」「安っぽく見える」「値下げせずに高級感を出したい」）にも使う。中文咨询（“被说太贵”“显得廉价”“不降价也想显得高级”）也适用。

日本語と英語の文章を ukwhatn 本人の文体で書く・下書きする・推敲する。PR 概要欄、レビュー指摘・返信、Slack メッセージ、チーム内ドキュメント、対外ビジネスメール、コミュニティのフォーラム告知とその合意形成の投稿、記事・レポート・議事録・提案書等の長文を日本語で書く時、本人の代わりに文章を書く時、国際的なコミュニティの運営間チャットに英語で投稿する時に使用。AI 特有の冗長さ・難語・翻訳調を排し、相手と媒体に応じて敬体/常体と敬語の重さを切り替える。雑談・times の投稿は対象外。境界: 実装修正を伴う PR コメント対応は pr-comment（本スキルは文章作成のみ）。

Genera tickets profesionales de soporte para Meta Business Suite / WhatsApp Business API optimizados para recibir prioridad URGENTE 24hr resolution. Úsala SIEMPRE que el usuario mencione crear un ticket a Meta, escalar un caso WABA, apelar un ban o restricción, reportar un false positive, abrir caso de soporte WhatsApp Business, problema de onboarding, rechazo de template, errores de Cloud API, OTP delivery, verification stuck, BM restricted, display name rejection, o cualquier issue de una WhatsApp Business Account. También activa cuando el usuario dice frases como "ayúdame a redactar un caso para Meta", "necesito reportar esto a soporte", "hay que escalar esto a WhatsApp", "ticket para Meta", o describe un problema de una cuenta de cliente de Vambe sin pedir ticket explícitamente pero claramente necesita uno. También activa ante preguntas del tipo "¿cómo apelar esto?" o "¿qué hago si Meta dice X?" relacionadas con WABA, BM o verificación.

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。

Identifies which items (pages, campaigns, products, channels, regions) had the biggest increases or decreases for a key metric between two time periods. Use this skill when someone asks "what's up and what's down," "which campaigns moved the most," "top gainers and losers," "what pages are trending," "show me what changed by channel," or any variation of identifying the biggest movers and decliners for a metric.

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。

Identifies which items (pages, campaigns, products, channels, regions) had the biggest increases or decreases for a key metric between two time periods. Use this skill when someone asks "what's up and what's down," "which campaigns moved the most," "top gainers and losers," "what pages are trending," "show me what changed by channel," or any variation of identifying the biggest movers and decliners for a metric.

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。

Code review focused exclusively on over-engineering. Finds what to delete: reinvented standard library, unneeded dependencies, speculative abstractions, dead flexibility. One line per finding: location, what to cut, what replaces it. Use when the user says "review for over-engineering", "what can we delete", "is this over-engineered", "simplify review", or invokes /ponytail-review. Complements correctness-focused review, this one only hunts complexity.

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。

Run the full on-track check on a conversation, project, or keyword the owner names: find the sessions, extract exactly what he typed, dispatch independent judges who go to the live product as him and report what was missed, plan the remedy, and return one page — what he will see, what is missing, the plan. Use when told to check whether work is on track, to audit a project that has drifted, on 'run the on-track check on X', or when a long campaign is about to freeze, hand off, or claim done.

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。

This skill should be used when the user asks to "このファイルを変えたら何が壊れる？", "what depends on this function", "影響範囲を調べて", "show me what imports this module", or wants to understand the blast radius before modifying a shared utility, exported type, or public API. Traces import/require references up to two levels deep and lists affected test files.

Identifies which items (pages, campaigns, products, channels, regions) had the biggest increases or decreases for a key metric between two time periods. Use this skill when someone asks "what's up and what's down," "which campaigns moved the most," "top gainers and losers," "what pages are trending," "show me what changed by channel," or any variation of identifying the biggest movers and decliners for a metric.

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。

Identifies which items (pages, campaigns, products, channels, regions) had the biggest increases or decreases for a key metric between two time periods. Use this skill when someone asks "what's up and what's down," "which campaigns moved the most," "top gainers and losers," "what pages are trending," "show me what changed by channel," or any variation of identifying the biggest movers and decliners for a metric.

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。

How to design contextual inputs for an always-on AI agent with episodic memory. Covers what data to feed the agent, how to structure observations and triggers, ambient context capture (screen, audio, calendar), context window budgeting, and retrieval strategies that keep the agent grounded in what's actually happening. Activate on: "what should the agent observe", "context inputs for agent", "ambient context capture", "agent triggers", "agent input design", "screenpipe integration", "context window budget", "what data to feed my agent", "/always-on-agent-inputs". NOT for: memory architecture and storage (use always-on-agent-architecture), application ideas (use always-on-agent-applications), safety concerns (use always-on-agent-safety).

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。