「when」の検索結果

Use this skill for general PostgreSQL table design. **Trigger when user asks to:** - Design PostgreSQL tables, schemas, or data models when creating new tables and when modifying existing ones. - Choose data types, constraints, or indexes for PostgreSQL - Create user tables, order tables, reference tables, or JSONB schemas - Understand PostgreSQL best practices for normalization, constraints, or indexing - Design update-heavy, upsert-heavy, or OLTP-style tables **Keywords:** PostgreSQL schema, table design, data types, PRIMARY KEY, FOREIGN KEY, indexes, B-tree, GIN, JSONB, constraints, normalization, identity columns, partitioning, row-level security Comprehensive reference covering data types, indexing strategies, constraints, JSONB patterns, partitioning, and PostgreSQL-specific best practices.

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 this skill when working with symbolic mathematics in Python. This skill should be used for symbolic computation tasks including solving equations algebraically, performing calculus operations (derivatives, integrals, limits), manipulating algebraic expressions, working with matrices symbolically, physics calculations, number theory problems, geometry computations, and generating executable code from mathematical expressions. Apply this skill when the user needs exact symbolic results rather than numerical approximations, or when working with mathematical formulas that contain variables and parameters.

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。

Design multi-agent architectures for complex tasks. Use when single-agent context limits are exceeded, when tasks decompose naturally into subtasks, or when specializing agents improves quality.

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 GDScript test suites from the command line with `godot --headless`, using a SceneTree/MainLoop runner script that exits non-zero on failure so CI can gate merges. Use when a Godot project needs unit tests without opening the editor, when wiring a CI job (GitHub Actions or similar) that must fail the build on a failing `.gd` test, or when a `godot --headless` invocation hangs, opens a window, or exits 0 despite failed assertions.

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。

Case studies of American screenwriting (美国电影剧作案例) — Mei Feng's readings of the Hollywood Western (value pairs, four oppositions), screwball comedy (strong heroine, buddy vs adversary two-hander), Billy Wilder (disguise, Lubitsch touch, meet-cute), Hitchcock and his writers, Adaptation, Mildred Pierce (eight drafts, woman's film + noir), Thelma & Louise ("but" method, mirror pair), Fargo (Coen method), Good Will Hunting (five-part structure), American Beauty (POV strategy, genre mix), Eternal Sunshine (1:5:1, image motifs); Walter's American Graffiti; the Hollywood masterclass films (Bourne, Guardians, Zootopia, Thor); Hoxter's Winter's Bone and Jojo Rabbit; Snyder's Miss Congeniality; Field's Chinatown. Use when you want a worked example of how a specific American film's script is built, when analysing a film for structure, character or theme, or when looking for a model to imitate for a Western, screwball, noir, buddy, coming-of-age, black comedy or non-linear romance.

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。

Manages stacked PRs and splits multi-part work into reviewable branches with gh-stack. Use for stack creation, viewing, edits, push, submit, sync, rebase, merge, or checkout; when asked to split or isolate work for review; whenever a user mentions a stack, branch layers, dependent PRs, or gh stack; or when a stack is checked out.

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 gives a topic and wants an automated topic-driven narrated explainer, podcast, or knowledge-summary video (Bilibili / YouTube / Xiaohongshu / Douyin / WeChat Channels), or asks to learn visual design patterns from a reference video/image. Trigger when the user mentions creating a knowledge video, narrated explainer, video podcast, or animated infographic-style video from a topic — even if they don't say "video podcast" explicitly. Also trigger when the user wants to regenerate, re-render, rebuild, update, or iterate on a narrated video this skill already produced — e.g. they edited the script/prompt, changed the visuals, or swapped the background music and want the final video remade (reuse the existing videos/{name}/ directory, never start a new project). Do NOT trigger for generic video editing, trimming, format conversion, color grading, or non-narrative video tasks. Produces 4K video via research → script → TTS → Remotion → MP4 + BGM.

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。

House style for user-facing documentation — voice, scope, structure, and what to leave out. Use this skill whenever writing, editing, or reviewing anything a user reads to learn how to use a tool — help center articles, getting-started guides, tutorials, feature docs, README usage sections, in-app help, release notes, or FAQ entries. Trigger it even when the request is phrased plainly — "document this feature", "write docs for X", "explain this to users", "write a README for this library", "turn these notes into a guide" — and even when no style guidelines are mentioned. Also use it to review existing docs for tone, bloat, or leaked implementation detail. Do not use it for internal engineering docs, architecture write-ups, RFCs, or code comments.

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。

Distill the current conversation into a structured note (decisions made, open questions, file pointers with line numbers, next 1–3 actions) and save to `quality_reports/session_logs/` before auto-compression. Differs from `/checkpoint` (explicit stop-point snapshot) and from auto-compaction (which truncates rather than distills). Use when context is approaching auto-compact threshold, when a long pipeline has accumulated many decisions, or when the user says "compress", "distil this session", "before we hit auto-compact", "structured handoff before context resets".

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。

Keeps a project's to-do list and memory in GitHub issues — files each finding (from a review, an audit, or the user) as its own issue without duplicates, lists the open issues that bear on the current work, and closes an issue with a comment recording what was wrong, what was tried, what worked, and how it was fixed. Use when review findings or a list of problems should become tracked work (a paper's misleading claims, a codebase's bugs, improvements for later), when starting or resuming work and deciding what to do next, or when a fix has landed and its issue should be closed with a record. Needs the GitHub CLI; warns before posting to a public repository.

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。

视频标题生成与落盘工作流。Use when the user asks to title a finished or planned video, especially 抖音/小红书视频标题, 视频标题.md, 成片同级目录, 对标标题共性, 两段式标题, 基于视频主题起标题, 洗稿后标题, or replacing generic dbs-xhs-title for video titles. It derives the real video theme first, studies benchmark title patterns when provided, generates 8-12 theme-first two-part candidates, recommends/selects one, and writes 视频标题.md next to the final MP4 when requested.

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。

Audit, question, suggest, or fact-preservingly revise a press release, blog post, contributed article, or expert explainer so AI answer systems can more easily retrieve, understand, quote, and cite its useful information. Use when someone asks for AI visibility, AI search, answer-engine, AEO, GEO, AI Overview, or ChatGPT citation optimization of supplied writing; when they want an evidence-aware pre-publication audit; or when another Newsjack workflow needs a prose-level AI-discoverability pass. Do not use as a technical SEO audit, rank tracker, publishing system, or promise of rankings, mentions, citations, traffic, or coverage.

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 premium, realistic soundtracks for code-made videos and animations from real licensed recordings - launch films, product and feature videos, UI walkthroughs, logo stings, explainers, trailers and animated shorts made with Remotion, HyperFrames, three.js, GSAP or any renderer. Use this whenever a video or animation needs sound design, SFX, foley, ambience, music, a soundtrack, a score, UI click / whoosh / riser / impact / logo-sting sounds, or a music edit to picture; whenever a synthesized or "random" sounding soundtrack must be replaced with real recordings; or when the user asks to source, license, credit, mix, master, critique or mux audio for a film. It covers cue lists from the picture, sourcing from Freesound / Mixkit / composer libraries with licence checks, a music edit at bar lines, a JSON sound design rendered by a deterministic mixer, measured QA (clicks, masking, harshness, sync, loudness) plus earshot listening, a multi-agent critique, mastering, credits and the mux.

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 Codex feels slow or bloated, when local sessions/logs/worktrees/config have grown over time, or when a user wants safe maintenance for Codex Desktop/CLI state. Provides a read-only report by default, backs up before applying changes, archives instead of deleting, normalizes Windows extended paths, prunes dead config projects, rotates large logs, and moves stale worktrees.

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。

Execute Azure deployments for ALREADY-PREPARED applications that have existing .azure/deployment-plan.md and infrastructure files. DO NOT use this skill when the user asks to CREATE a new application — use azure-prepare instead. This skill runs azd up, azd deploy, terraform apply, and az deployment commands with built-in error recovery. Requires .azure/deployment-plan.md from azure-prepare and validated status from azure-validate. WHEN: "run azd up", "run azd deploy", "execute deployment", "push to production", "push to cloud", "go live", "ship it", "bicep deploy", "terraform apply", "publish to Azure", "launch on Azure". DO NOT USE WHEN: "create and deploy", "build and deploy", "create a new app", "set up infrastructure", "create and deploy to Azure using Terraform" — use azure-prepare for these.

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。

Self-coaching analysis of your own behavior across meetings — talk-time ratio, filler words, hedging language, monologue length, energy patterns, and (when meetings are tagged via /minutes-tag) what your behavior in winning meetings looks like vs losing ones. Use this whenever the user says "how did I do", "review my last meeting", "mirror", "self-review", "show my patterns", "coach me", "where am I weak", "talk time", "am I improving", "what do I do in meetings I win", "feedback on me", or asks for any kind of personal feedback on their own meeting behavior. This is the rare skill that gives the user a mirror to their own habits — surface it whenever they show curiosity about their own performance, even if they don't use the word "mirror".

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。

Fast non-interactive briefing before any meeting — auto-detects your next calendar event, pulls relationship history, surfaces open commitments, and produces a one-page brief in under 30 seconds. Use this whenever the user says "brief me", "give me a quick brief", "what's coming up", "background on my next call", "who am I meeting next", "brief me on Sarah", "I have a call in 10 min", "quick rundown", or right before walking into a meeting. Different from /minutes-prep — brief is the fast hook-fireable version that doesn't ask questions and doesn't set goals. Use brief when speed matters; use prep when the user wants to think hard about goals first.

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。

Coordinates parallel investigation threads to simultaneously explore multiple hypotheses or root causes across different system areas. Use when debugging production incidents, slow API performance, multi-system integration failures, or complex bugs where the root cause is unclear and multiple plausible theories exist; when serial troubleshooting is too slow; or when multiple investigators can divide root-cause analysis work. Provides structured phases for problem decomposition, thread assignment, sync points with Continue/Pivot/Converge decisions, and final report synthesis.

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。

Diagnoses and designs safe Terraform releases, provisioners (remote-exec/local-exec/file, cloud-init, Compose, Caddy), multi-environment isolation, and fresh-host bootstrap. Use when writing or reviewing plan/apply wrappers or provisioners; when staging/production config may differ; when a rollout can mutate a shared gateway; or debugging drift, TLS, container restarts, DNS duplication, or snapshot contamination.

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 and send technical status notifications through WeCom (Enterprise WeChat) webhooks. Use this skill whenever the user needs to send notifications, alerts, backup completion reports, or status updates via WeCom; when they mention 企业微信, 企微机器人, webhook, or alerting; or when a message needs to be clear, unambiguous, and technically precise rather than vague or condescending.

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。

Keep Claude Code sessions productive across resets with output filtering, session logging, and auto-resume. Use when starting a long or complex coding session, when previous sessions lost context mid-task, or when you need Claude to resume exactly where it left off after a reset. Produces a session.log at the project root, filtered command output that preserves context, and automatic resume of in-progress tasks after any reset.

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 sincere condolence or sympathy message when someone has died or a friend is grieving — warm, personal, and free of the clichés that hurt more than help. Use when asked what to say when someone dies, write a sympathy/condolence message, my friend lost their [person], or I don't know what to say. Produces a heartfelt message tuned to your relationship and the situation, drawn from a specific memory or quality where possible, an honest acknowledgment (not toxic-positive platitudes), an offer of concrete support, and guidance on what to avoid saying.

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。

Simplify code that works — remove speculative abstraction, dead flexibility, and needless indirection while keeping behaviour identical and verified. Use when a feature has just landed ('now simplify it'), when AI-generated code arrives over-engineered, when a file has grown hard to follow, or as the cleanup pass before review. Produces a smaller, flatter version with identical behaviour, plus a ledger of what was removed and why it was safe. For finding bugs use code-review-checklist / ai-code-review — this skill assumes it works and makes it simple.

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。