「variants」の検索結果

Generate Isabelle or Coq proofs establishing partial or total correctness of imperative programs from code and formal specifications. Use when users need to: (1) Prove program correctness using Hoare logic, (2) Generate verification conditions from pre/postconditions, (3) Construct loop invariants and termination arguments, (4) Verify imperative programs with assignments, conditionals, and loops. Supports both partial correctness (if terminates, postcondition holds) and total correctness (terminates and postcondition holds) for both Isabelle/HOL and Coq.

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。

Verify that interface and class contracts (preconditions, postconditions, invariants) are preserved across program versions. Use when validating refactorings, checking API compatibility, verifying design-by-contract implementations, or ensuring behavioral contracts remain intact after code changes. Automatically detects contract violations, identifies affected methods and classes, and provides actionable guidance for resolving violations while maintaining program correctness.

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。

Create ACSL (ANSI/ISO C Specification Language) formal annotations for C/C++ programs. Use this skill when working with formal verification, adding function contracts (requires/ensures), loop invariants, assertions, memory safety annotations, or any ACSL specifications. Supports Frama-C verification and generates comprehensive formal specifications for C/C++ code.

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。

Explain why counterexamples violate specifications by analyzing formal specifications (temporal logic, invariants, pre/postconditions, code contracts), informal requirements (user stories, acceptance criteria), test specifications (assertions, property-based tests), and providing step-by-step traces showing state changes, comparing expected vs actual behavior, identifying root causes, and assessing violation impact. Use when debugging test failures, understanding model checker output, explaining runtime assertion violations, analyzing static analysis warnings, or teaching specification concepts. Produces structured markdown explanations with traces, comparisons, state diagrams, and cause chains. Triggers when users ask why something failed, explain a violation, understand a counterexample, debug a specification, or analyze why a test fails.

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。

Automatically complete partial code snippets while satisfying semantic constraints including variable types, invariants, pre/post-conditions, interface contracts, and expected input/output behavior. Use when users provide incomplete code with specific requirements like "complete this function that takes a list and returns sorted unique elements" or "fill in this method body that must maintain the invariant that x stays positive" or "implement this interface method with these type constraints." Produces compilable, executable code with tests and a constraint satisfaction report.

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。

Apple Human Interface Guidelines as structured design values — system colors (incl. increased-contrast variants), the full Dynamic Type ramp, Liquid Glass rules and budgets, layout and hit-target metrics, SF Symbols, and HIG-to-SwiftUI component mappings. Use when styling or reviewing any Apple-platform UI: picking a color, size, spacing, corner radius, or hit target; writing .glassEffect / material code; choosing an SF Symbol; or answering 'what does the HIG say about X'.

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 "upload images to Cloudflare", "implement direct creator upload", "configure image transformations", "optimize WebP/AVIF", "create image variants", "generate signed URLs", "add image watermarks", "integrate with Next.js/Remix", "configure webhooks", "debug CORS errors", "troubleshoot error 5408/9401-9413", or "build responsive images with Cloudflare Images API".

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 a disciplined engineering workflow to any code change. Use whenever implementing a feature, fixing a bug, or refactoring — before writing code, not after. Walks orient → baseline → smallest change → test → verify → self-review, and enforces language-agnostic hard gates (don't mass-reformat, keep the linter and type-checker clean, keep the build and tests green, make interface changes additive, protect security invariants).

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。

Think and work like an expert Computer Scientist. Use when a task calls for Computer Scientist judgment. Reasons from computational models, abstraction contracts, invariants, and measurable complexity through CLRS-grade algorithm analysis, impossibility results (FLP, CAP, NP-hardness), property-based and chaos testing, and formal tools (TLA+, Coq, Z3) while treating partial failure, race conditions, label leakage, and abstraction leaks like GC pauses and clock skew as first-class failure modes.

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。

Provider-independent still-image post-production skill for RAW/rendered intake, nondestructive development, exposure, white balance, tone, color, ICC proofing, masking, repair, compositing, truthful retouching by genre, generative disclosure, sharpening, noise, resampling, variants, metadata, export, QA, rights, and ethical finishing. Use when an agent must plan, perform, direct, or review still photography retouching and finishing for print, web, social, archive, publication, or client delivery; do not use for image-generation APIs, video grading, or campaign-specific production strategy.

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。

Production guidance for converting sourced data and approved claims into truthful, accessible, deterministic animated visualizations with D3. Use for data-driven charts, maps, networks, hierarchies, transitions, annotations, responsive video variants, frame-by-frame browser rendering, and visualization QA; not for generic dashboards, unsourced decorative charts, or ordinary motion graphics without a data contract.

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。

Provider-independent production guidance for deterministic Canvas 2D and p5.js animation. Use for particles, fields, trails, weather, procedural textures, generative geometry, and lightweight 2D simulations that need fixed media dimensions, seeded repeatability, transparent compositing, aspect variants, performance QA, or frame-addressable rendering.

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。

Provider-independent production workflow for recutting long talking-head, podcast, interview, webinar, panel, lecture, livestream, founder call, or customer-call footage into short clips, highlight reels, trailers, audiograms, captioned vertical videos, and social cutdowns. Use when an agent must ingest source recordings, transcribe and diarize speakers, select quotes without misrepresentation, preserve context, handle consent/rights/disclosures, clean jump cuts and audio, add captions, graphics, lower thirds, b-roll, platform variants, synthetic-media boundaries, review packets, delivery specs, and recut QA.

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。

Provider-independent production guidance for AI agents creating or retouching appetizing food and beverage images, recipe videos, restaurant/menu visuals, CPG ads, ecommerce product images, beverage pours, packaging/lifestyle shots, and social food clips, including truthfulness, labeling/claims discipline, styling, prompt translation, platform variants, accessibility, rights, alcohol, and QA.

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。

Provider-independent explainer video production for AI agents creating educational, product, concept, nonprofit/public-service, onboarding, training, animated, mixed-media, and short social explainers. Use when an agent must turn a topic, brief, research corpus, product, process, policy, dataset, or complex idea into a factual, accessible, narrated, captioned, storyboarded, generated-media-ready explainer video with claim review, localization, pacing, variants, and QA.

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。

Provider-independent asset continuity and version management for generated-media production. Use when an agent must track generated or reference assets, prompts, seeds, model/tool versions, manifests, approvals, edit decisions, derivatives, localization variants, metadata/provenance, and continuity QA across image, video, audio, avatar, product-ad, social, explainer, or film-style pipelines.

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。

Provider-independent production workflow for AI agents creating music videos, lyric videos, visualizers, performance/narrative/dance videos, social cutdowns, album or single launch assets, and generated-media clips synchronized to songs. Use when planning, directing, prompting, editing, reviewing, or delivering video content built around a recorded song, artist performance, lyrics, beat timing, choreography, platform variants, music rights, likeness consent, accessibility, or synthetic-media disclosure.

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。

Production guidance for reusable layered 2D character rigs in browser-rendered and video media. Use for SVG hierarchies, pivots and constraints, FK/IK planning, pose and facial libraries, acting, cycles, deterministic handoff, crop variants, and rig QA; not for character concept continuity, 3D armatures, or motion-capture solving.

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。

Provider-independent real estate media production for listing photos, virtual staging, property videos, walkthrough reels, floor-plan explainers, neighborhood clips, renovation concepts, agent ads, and generated or retouched property visuals. Use when creating, editing, reviewing, prompting, packaging, or approving real estate marketing content where property truthfulness, listing/MLS compliance, fair-housing risk, staging disclosure, privacy, accessibility, platform variants, or real-estate QA matter.

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。

Provider-independent workflow for producing UGC-style paid and social ads, creator testimonials, product demos, hooks, before/after concepts, app walkthroughs, TikTok/Reels/Shorts variants, synthetic-persona or avatar UGC, ad-policy checks, disclosure planning, rights/consent review, delivery specs, and QA.

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。

Provider-independent workflow for producing SaaS and software product demo videos, including app walkthroughs, feature launches, sales demos, onboarding clips, help-center explainers, website hero demos, and PLG assets. Use when an agent must plan, script, capture, synthesize, edit, localize, review, or QA privacy-safe software demo videos with substantiated claims, accessible captions, screen/cursor direction, CTA variants, and stakeholder approval.

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。

Provider-independent workflow for producing terminal, IDE, documentation, browser, desktop, and application demonstration videos. Use when choosing authentic capture, browser automation, synthetic UI, or hybrid treatment; scripting actions and narration; resetting demo state; protecting secrets and personal data; directing cursor/callouts; creating crop variants; and reviewing workflow truth, readability, accessibility, and provenance.

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。

Provider-independent workflow for AI agents producing documentary-style montages, archive-driven timelines, interview-supported sequences, nonprofit or advocacy shorts, historical explainers, and hybrid generated/archive edits. Use for editorial thesis development, research/source logs, fact-checking, archive rights, synthetic reenactment disclosure, chronology, interview selects, lower thirds, generated b-roll direction, music restraint, captions, sensitive subjects, review escalation, delivery variants, and documentary QA.

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。

Resolves GWAS associations to candidate causal variants and credible sets via SuSiE, susie_rss, FINEMAP, CAVIAR, DAP-G, PAINTOR, PolyFun, SuSiEx, MultiSuSiE, and FOCUS. Use when narrowing a GWAS lead SNP to a 95 percent credible set, choosing between in-sample and reference LD, calibrating non-sparse loci with SuSiE-inf or FINEMAP-inf, integrating functional priors via PolyFun, fine-mapping across ancestries with SuSiEx, diagnosing LD mismatch via estimate_s_rss and kriging_rss, handling HLA or long-range LD, or feeding credible sets into coloc.susie for colocalization.

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。