6.2万 件 ・ 関連度順
Generates changelogs and release notes from git commits, PR titles, and issue references. Organizes changes by impact type (breaking, features, fixes, improvements), formats according to Keep a Changelog standard, and provides version tagging and semantic versioning suggestions. Use when users request "create changelog", "write release notes", "document version changes", or "prepare release".
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。
Defines caching strategies with cache keys, TTL values, invalidation triggers, consistency patterns, and correctness checklist. Provides code examples for Redis, CDN, and application-level caching. Use when implementing "caching", "performance optimization", "cache strategy", or "Redis caching".
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。
Premium brand-kit image generation skill for creating high-end brand-guidelines boards, logo systems, identity decks, and visual-world presentations. Trained for minimalist, cinematic, editorial, dark-tech, luxury, cultural, security, gaming, developer-tool, and consumer-app brand systems. Optimized for intentional logo concepting, refined composition, sparse typography, strong symbolic meaning, premium mockups, art-directed imagery, and flexible grid layouts.
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。
Brand voice, visual identity, messaging frameworks, asset management, brand consistency. Activate for branded content, tone of voice, marketing assets, brand compliance, style guides.
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。
Sets up end-to-end testing with Cypress or Playwright including page objects, fixtures, and CI integration. Use when users request "E2E testing", "Cypress setup", "Playwright setup", "browser testing", or "integration tests".
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 a working Spark implementation should be simplified without changing its observed behavior, ownership, compatibility, or public 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。
Use when a Spark branch or pull request needs final diff hygiene, validation selection, commit scope, remote topology, and readiness checked before publication.
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 a Spark change needs its authoritative owner, affected boundaries, risks, acceptance criteria, and smallest verifiable slice established before implementation or review.
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 adding or updating Spark AI provider models or their compact and preflight metrics, especially baidu-oneapi, Grok, Claude, GPT, DeepSeek, OneAPI, context windows, output budgets, prices, thinking maps, or transports.
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 a Spark implementation needs an evidence-based review for correctness, ownership, compatibility, failure handling, maintainability, and unnecessary 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。
Use when authoring a new manuscript, thesis chapter, or abstract from scratch in Turkish and English in parallel — building the claim skeleton first, then drafting Turkish and re-authoring English — not for auditing parity between existing versions.
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 a systematic, scoping, or rapid review needs a reproducible pipeline: protocol framing (PICO/SPIDER/PCC), a logged search string, title/abstract and full-text screening with recorded exclusion reasons, and PRISMA flow counts, with the human as the deciding screener.
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 a study's materials, data, code, or preprint need an open-science release: license choice, a persistent DOI (Zenodo/OSF), README and metadata, and an access-and-embargo decision that respects ethics constraints.
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 choosing a journal for a finished or nearly finished manuscript, when index status in Scopus, SSCI, ESCI, or TR Dizin must be confirmed, when a venue looks predatory, or when a cover letter needs drafting from the manuscript's actual claims.
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 a reference list needs APA 7 cleanup, when DOIs must be confirmed real against Crossref or PubMed, when the user asks whether AI-suggested citations actually exist, or when a manuscript needs a citation hygiene pass before submission or defense.
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 before a tag, GitHub release, or Zenodo archive, when README, CATALOG, CHANGELOG, CITATION.cff, the disclosure aggregate, and skill discovery must agree, or when a go or no-go release verdict needs recorded evidence behind it.
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 paired tr.md and en.md files need a parity verdict, when titles, frontmatter, headings, or DOI sets may have drifted between languages, or when a bilingual document is approaching release and its translation coverage needs an audit.
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 adapting academic findings for a public audience (op-ed, social post, podcast) and the simplification must stay evidence-faithful, avoid overclaiming, respect embargoes, and disclose AI assistance.
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 authorship order, CRediT contribution roles, or AI-assistance attribution must be recorded transparently for a manuscript, when an author dispute needs an evidence trail, or before a contributorship statement is required at submission; this skill maintains the human-attribution ledger of who contributed what and in which role (authorship order, CRediT taxonomy, revision responsibilities), which is distinct from the disclosure-metadata audit owned by ai-disclosure-auditor.
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 reviewer comments arrive and each one needs a tracked decision, when a revise and resubmit letter must map every comment to a manuscript change, or when contradictory reviewer demands need evidence-based, editor-facing framing.
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 a researcher asks where to start, which project skill fits the current stage of a study, or in what order literature scoping, source access, vault upkeep, drafting, citation verification, disclosure, and review response should run.
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 a Claude Code session loops, drifts from scope, claims a fix that CI rejects, hits context, PATH, or permission walls, or fails in a way another retry will not solve and a root cause diagnosis is needed 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 when automating research session rituals in Claude Code with hooks, such as session-start context injection, daily research logging, session-end persistence, or pre-commit guards that block secrets and unverified citations.
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 AI contribution metadata must match the actual workflow, when model alias and dated identifiers need auditing, when verified and fabricated citation counts feed a release decision, or when a venue's AI disclosure statement needs evidence behind it.
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。