「then」の検索結果

When behavior is emergent across components—fixes elsewhere break, loops/delays dominate—map boundary, stocks/flows, feedback, archetypes, then rank leverage.

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。

When unsure which thinking skill fits, map domain and problem type, then return NONE or one primary skill by default (at most three complementary).

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。

Before rejecting a proposal or reflexively agreeing, build the strongest faithful opposing case, state agreement conditions, then update or reaffirm.

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 longevity of a non-perishable option matters. Treat survival duration as a remaining-life prior, then check domain drift before favoring the proven.

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。

Clone an existing video ad for a different product or offer. Analyzes the source video's style, pacing, camera work, dialogue, and tone, then adapts and generates a new Seedance 2.0 video customized for the user's product. End-to-end workflow: input video → analysis → adapted prompt → generation → delivery. Use when someone says "clone this ad", "make this ad but for my product", "recreate this video for my brand", or provides a video ad and a product image asking for a similar video.

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 upload or publish an Agentlas agent or team. Ask Cloud private vs Agentlas Hub public FIRST, then use the bundled immutable upload gate.

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 types $hephaestus-upload, /hep-upload, or /agentlas-upload, or asks to upload, publish, or list an Agentlas agent or team. Ask Cloud (private) vs Agentlas Hub (public) FIRST, then publish through the bundled Hephaestus gate.

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。

Commit and push changes, then create a new PR or append to an existing one.

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。

Assess and improve the reliability posture of PaaS Applications (Azure Functions and Azure App Service). Scans deployed resources for zone redundancy, ZRS storage, health probes, and multi-region failover. Presents a feature-pivoted checklist, then drives staged remediation (CLI or IaC patches) end-to-end with user confirmation. WHEN: "assess reliability", "check reliability", "zone redundant", "multi-region failover", "high availability", "disaster recovery", "single points of failure", "reliability posture", "resiliency".

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。

Troubleshoot and resolve issues with Azure Messaging SDKs for Event Hubs and Service Bus. Covers connection failures, authentication errors, message processing issues, and SDK configuration problems. WHEN: event hub SDK error, service bus SDK issue, messaging connection failure, AMQP error, event processor host issue, message lock lost, message lock expired, lock renewal, lock renewal batch, send timeout, receiver disconnected, SDK troubleshooting, azure messaging SDK, event hub consumer, service bus queue issue, topic subscription error, enable logging event hub, service bus logging, eventhub python, servicebus java, eventhub javascript, servicebus dotnet, event hub checkpoint, event hub not receiving messages, service bus dead letter, batch processing lock, session lock expired, idle timeout, connection inactive, link detach, slow reconnect, session error, duplicate events, offset reset, receive batch.

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。

Write a YouTube video script from a raw idea - hook options off 21 formulas, scored, then the full spoken script with the retention beats marked. Use whenever the user wants a video script, a hook, an opening line, "what should I say", "write my next video", or is about to record and does not have the first fifteen seconds yet.

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。

Find what is actually working in the user's niche on YouTube and rank it by how far each video beat its own channel, then name the formula. Use for "what's working right now", "find viral videos in my niche", "why did this blow up", competitor research, or a swipe file.

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。

Read a YouTube Studio audience-retention export and find where viewers actually leave, then say what to change. Use for "why do people stop watching", "my retention is bad", a pasted retention chart or CSV, or "fix my pacing".

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。

Routes any game-development request to the right specialized skill(s): it detects the engine (Godot, Unity, Unreal, Bevy, Phaser, PixiJS, three.js, LÖVE, pygame, Roblox) and the task, then reads the chosen skill before acting. Use to make a game or to decide which skill applies — for players, levels, enemies, shaders, art direction, sprites, tiles, textures, 3D assets, UI/UX, cameras, game feel, physics, input, audio, saving, multiplayer, AI, dialogue, procedural generation, or performance, for genres (platformer, roguelike, RPG, FPS, tower-defense, card game, visual novel, survival-crafting, puzzle), and for shipping (game jam, Steam, itch). Start here when unsure which gamedev skill to use.

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。

Find and fix game performance problems methodically — measure with the engine profiler first, reason about the frame-time budget, locate the CPU-vs-GPU bottleneck, then apply the right fix: object pooling, draw-call batching, fewer allocations/GC spikes, and asset budgets. Engine- neutral method that pairs with each engine's profiler. Use when the user mentions performance, optimize, low/dropping FPS, frame drops, stutter, lag, profiler, frame budget, draw calls, batching, garbage collection/GC spikes, object pooling, or "the game runs slow".

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。

Recover the first public timestamp and canonical major coverage for a newsjacking signal, then decide whether newer coverage is the same story, a different story, or a materially new development.

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 eval study's numbers into on-brand, publish-ready figures using the Newsjack chart room (the eval design system), then validate them with Playwright. For producing the charts in a published eval/data study.

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。

Decide which single journalist at one publication to approach first with a pitch. Fit-checks each candidate through journalist-fit-check, then ranks the survivors on the comparative signals that separate colleagues at the same masthead (topic ownership, format match, staff vs. contributor, publishing cadence, recent story types, source-type match), and returns one first pick with tailoring notes plus a held fallback order.

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。

Monitor current news and reaction signals, then decide which are credible newsjacking opportunities for a client. Uses the local monitoring engine for evidence, but the skill owns PR judgment, brand safety, standing, decay, angle fit, and handoff.

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。

Set up a lightweight Google Alerts-style coverage tracker for any number of keywords. Creates a tracker config with each keyword and what it actually means, then hands recurrence to the user's agent harness.

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 headline candidates from a story's raw facts: news-style headlines, press-release headlines, and pitch subject lines. A pure generation skill — it finds the charge in the facts, then runs ten proven moves (consequence, picture, number-as-hero, two-beat turn, naming, reader's-own-story, open question, voice, sound, sized claim), each calibrated by real, verified headlines that made history.

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。

Recover source-bound buyer jobs, struggling moments, desired progress, forces, workarounds, information acts, journey states, criteria, constraints, roles, locales, and authentic language. Use on approved ICP hypotheses plus customer, search, review, forum, procurement, support, or public-market evidence before designing an AI-visibility prompt architecture.

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。

Applies proven testing patterns — Arrange-Act-Assert (AAA), Given-When-Then, Test Data Builders, Object Mother, parameterized tests, fixtures, spies, and test doubles — to help write maintainable, reliable, and readable test suites. Use when the user asks about writing unit tests, integration tests, or end-to-end tests; structuring test cases or test suites; applying TDD or BDD practices; working with mocks, stubs, spies, or fakes; improving test coverage or reducing flakiness; or needs guidance on test organization, naming conventions, or assertions in frameworks like Jest, Vitest, pytest, or similar.

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。

Guides the red-green-refactor TDD workflow: write a failing test first, implement the minimum code to make it pass, then refactor while keeping tests green. Use when a user asks to practice TDD, write tests first, follow red-green-refactor, do test-driven development, write failing tests before code, or phrases like 'make the test pass', 'test coverage', or 'unit tests before implementation'.

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。