「cases」の検索結果

Recommend suitable prompts from 10,000+ Nano Banana Pro image generation prompts based on user needs. Optimized for Nano Banana Pro (Gemini), but prompts also work with Nano Banana 2, Seedream 5.0, GPT Image 1.5, Midjourney, DALL-E, Flux, Stable Diffusion, and any text-to-image AI model. Use this skill when users want to: - Generate images with AI (any model — Nano Banana Pro, Gemini, GPT Image, Seedream, etc.) - Find proven AI image generation prompts and prompt templates - Get prompt recommendations for specific use cases (portraits, products, social media, posters, etc.) - Create illustrations for articles, videos, podcasts, or marketing content - Browse a curated prompt library with sample images - Translate and understand prompt techniques Also available: "ai-image-prompts" skill — a model-agnostic version of this library for universal image generation.

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Use for parsing structured unit commitment input data from JSON, CSV, benchmark cases, spreadsheets, databases, or nested tables; finding fields for time periods, resources, load, reserve, generator limits, initial conditions, startup data, renewable availability, and production costs without assuming one source-specific schema.

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An overview of the core data API of ObsPy, a Python framework for processing seismological data. It is useful for parsing common seismological file formats, or manipulating custom data into standard objects for downstream use cases such as ObsPy's signal processing routines or SeisBench's modeling API.

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WooYun business logic vulnerability methodology — 22,132 real cases across 6 domains (authentication bypass, authorization bypass, payment tampering, information disclosure, logic flaws, misconfiguration) and 33 vulnerability classes. Use for ANY security testing, auditing, or code review of web apps, APIs, or business systems — even without explicit "security" keywords. Triggers: penetration testing, security audit, vulnerability, bug bounty, payment security, IDOR, password reset, weak credentials, unauthorized access, race condition, parameter tampering, code review, 渗透测试, 安全审计, 漏洞挖掘, 支付安全, 越权, 逻辑漏洞, 业务安全, SRC, 代码审计. Also triggers on implicit intent: "test this endpoint", "find bugs", "can I bypass this", "帮我测测这个接口", "这个参数能不能改", "帮我找bug".

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 failing tests for the TDD red phase to define expected behavior and edge cases.

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。

Derive security requirements from threat models and business context. Use when translating threats into actionable requirements, creating security user stories, or building security test cases.

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。

Worked qupai-system (曲牌体) opera scripts, act by act. Guan Hanqing's three surviving zaju (窦娥冤／救风尘／金线池 — twelve acts, 126 tunes, one mode and one rhyme per act, sung/spoken ratios); Tang Xianzu's 牡丹亭 (55 scenes, ~420 tunes, 集唐 closing quatrains, the 圆驾 south-north composite suite); Kong Shangren's 桃花扇 (44 scenes plus four unnumbered, the 副末 frame line, upper/lower halves, a fan's seven transformations, his sixteen 凡例); 长生殿 (Wang Jilie's fifty-scene staging table); Wei Minglun's 巴山秀才 (1983 Sichuan 高腔, 43 tunes, nine 帮腔 passages). Every case states its edition and collation status, then structure, tunes, stage conventions and transferable devices. Method is in sw-chinese-opera-qupai; this skill holds the worked scripts. Use when you want a real example of how a 传奇 or 杂剧 is assembled, need actual scene counts and tune counts to imitate, are judging where a famous script breaks prosody, or need models for 副末开场, 集唐下场诗, 南北合套 or 帮腔 (曲牌体全本／牡丹亭／桃花扇／窦娥冤／救风尘／长生殿／巴山秀才／唱段表／结构表).

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Worked full-length scripts of banqiang-system Chinese opera with their creation records (板腔体全本语料库). Primary texts; 翁偶虹《锁麟囊》 (the revised score edition, 65 arias, 15 self-account-vs-score checks), 汪曾祺等《沙家浜》 (the 1965 text, not the 1970 one; 36 arias, a 12-row two-version diff), 田汉《白蛇传》 (the 1955 book, not the web revision; 16 scenes, 王瑶卿说腔五条), 杨兰春《朝阳沟》 (1978 revival, 50 arias, 口语入唱, per-scene sung/spoken ratios), 魏明伦《潘金莲》 (跨时空, missing pages), 罗怀臻's 越剧《李清照》《真假驸马》, 淮剧《金龙与蜉蝣》, 甬剧《典妻》; plus index tables of 翁偶虹's 60 创作记 and 范钧宏's seven 改编札记. Use when you want to see how a 唱工戏 lays out its 板式, need real scene counts, aria counts and 辙口 to imitate, want the road from raw material to 审腔, are writing a 现代戏 or colloquial lyrics, or compare one author across two声腔 systems. Method is in sw-chinese-opera-banqiang; this skill holds the worked scripts and their creation records.

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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.

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Applies systematic tracing and isolation techniques to pinpoint exactly where a bug originates in code. Use when a bug is hard to locate, code is not working as expected, an error or crash appears with unclear cause, a regression was introduced between recent commits, or you need to narrow down which component, function, or line is faulty. Covers binary search debugging, git bisect for regressions, strategic logging with [TRACE] patterns, data and control flow tracing, component isolation, minimal reproduction cases, conditional breakpoints, and watch expressions across TypeScript, SQL, and bash.

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Run /test to write a test suite for code you just built or changed, after implementing a feature, route, or fix. Targets uncommitted changes automatically, reads test preferences.json for your framework (asks and saves it if absent), and picks the right strategy per file: happy path, edge cases, error states, accessibility.

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Write a fair, enforceable community moderation policy. Use when standing up or overhauling moderation for a forum, Discord, Slack, subreddit, or any user community. Produces a clear code of conduct with examples, a graduated enforcement ladder tied to specific triggers, an appeals process, moderator guidelines, and the handling for the severe cases (threats, doxxing, brigading) that need immediate action. Governs member conduct in a user community — distinct from [[community-management-playbook]], which manages a brand's own social-media channels (comments, DMs, tone, response templates).

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Set up a chart of accounts and rules for categorizing transactions. Use when asked how to categorize expenses/transactions, set up a chart of accounts, organize bookkeeping, or sort bank transactions into the right buckets. Produces a practical chart of accounts for the business, categorization rules with examples and edge cases, and a clean-books routine — so the books are consistent and ready for an accountant. Not tax/accounting advice.

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Keep a running brag document of your accomplishments so reviews and promo cases write themselves. Use when asked to start or update a brag doc, log a win, track accomplishments, or prep evidence for a review/promotion. Produces a structured, dated accomplishment log — impact-first entries with metrics, scope, and the evidence link — grouped so it drops straight into a self-review or promo packet.

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Eval and improve a skill against golden cases — run the target skill blind in a fresh, context-free subagent on each example input, grade the artifact against the expected outcome, and let the gaps drive the edits. Use when the user wants to test/eval/improve/harden a skill, says "this skill keeps producing X / keeps missing Y", or hands a skill plus example input→expected-output pairs. Pairs with [write-skills](../write-skills/SKILL.md) (the authoring principles every fix obeys).

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Clean Architecture patterns for Android and Kotlin Multiplatform projects — module structure, dependency rules, UseCases, Repositories, and data layer patterns.

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AI code quality checks. The Big 5: input validation, edge cases, error handling, duplication, complexity. Triggers: quality, big 5, ai code, review, validate.

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Use when extensions, edge cases, or applied robustness checks are missing for an American Economic Journal: Microeconomics (AEJ: Micro) manuscript — covering theory extensions (relaxed assumptions, alternative concepts, perturbations) and applied/experimental robustness. Decides which extensions earn their place; it does not prove the main result (see aejmic-theory-model).

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Use when stress-testing the LOGIC of an Academy of Management Review (AMR) theory manuscript — checking logical coherence, running thought experiments and counterfactuals, addressing alternative explanations and disconfirming cases, and verifying each proposition follows from its argument. This is ARGUMENT DEVELOPMENT, NOT data analysis; AMR publishes no datasets, no statistics, and no empirical results.

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Identify programmatic SEO page patterns worth building for your product — vs/ pages, integrations/, for-{industry}/, alternatives-to/, use-cases/ — and design the template structure, data model, and priority order. Outputs a complete pSEO blueprint with URL patterns, title templates, content frameworks, and data sources per variable.

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Render a two-host podcast ad from a brand config and dialogue script. Includes the working planner, full-frame and split-screen assembly, captions from measured character timings, brand end card, approved paid-step adapters, and 65 quality-check falsification cases. Use for short conversational ads with two stable hosts in one room.

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Import data into the Simulation Data Inspector (SDI) from MAT, CSV, or Excel files, from workspace variables, or from a Simulink simulation. Use when the user wants to view a logged file in SDI, load a bench-test log, or verify what a just-completed `Simulink.sdi.createRun` or `sim(model)` produced. Covers the `'file'`, `'vars'`, and `'namevalue'` sources of `createRun`, the auto-populate behavior after `sim()`, and post-import verification. Not for comparing existing runs (use `Simulink.sdi.compareRuns`); not for streaming data live during a running simulation (use `Simulink.sdi.createRunOrAddToStreamedRun` — a separate API); and not for authoring Gherkin or Simulink Test test cases, assertions, or regression tests (use `testing-simulink-models`). Do not activate on test-authoring or verification prompts even when no test-authoring skill is available — say so and stop.

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Fits structural equation models to GWAS summary statistics using GenomicSEM (Grotzinger 2019), including common-factor models, confirmatory factor models, ESEM, common-factor GWAS with Q_SNP heterogeneity, multivariate Wald tests, and stratified GenomicSEM partitioned heritability. Reconciles results against MTAG multi-trait analysis. Handles sample overlap via the LDSC sampling-covariance matrix, identifies and resolves Heywood cases, and verifies model fit with CFI / RMSEA. Use when modeling latent genetic architecture across correlated traits, running multivariate GWAS on a shared factor, distinguishing factor-mediated from trait-specific SNP effects, or comparing GenomicSEM common-factor results against MTAG when both depend on accurate sampling covariance.

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Creates and maintains the scenarios a LiveKit agent simulation runs, and wires the agent to consume them. Use when the user asks "what should I test", "generate simulation scenarios", "write scenarios for my agent", "add a scenario for X", "organize my scenario files", "my simulations are flaky", "the scenario hits my real database", "seed state per scenario", "it passed but booked the wrong thing", "grade the final state", or wants to stress-test a flow before shipping. Covers generating a baseline with the LiveKit scenario generator and refining it, writing the cases generation misses, phrasing simulated-user instructions so they steer reliably, splitting scenarios into sets across files, and the agent-side code that seeds deterministic state from a scenario and fails a run on its final state. To run them use running-livekit-simulations.

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。