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Resize, crop, or export any image or video into platform-ready social media assets using Adobe Creative Cloud tools. Use this skill when a user wants to prepare a photo, image, or video for one or more social platforms — Instagram, TikTok, LinkedIn, Facebook, YouTube, Snapchat, Pinterest, Threads, or X/Twitter. Triggers on: "prepare my image for Instagram", "resize for TikTok", "get this ready to post", "make versions for all platforms", "social media sizes", "crop for stories", "export for LinkedIn", "resize my video for social", "make social media assets", or any request to adapt a photo or video for specific platforms. Handles subject-aware cropping, AI canvas expansion, test previews before full runs, and same-ratio video resizing.

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。

[BETA] Expert assistance for the Adobe I/O CLI plugin `@adobe/aio-cli-plugin-aem-rde` — the `aio aem rde` / `aio aem:rde` command tree used to deploy, inspect, log-tail, snapshot, and troubleshoot AEM Rapid Development Environments (RDEs). Activate ONLY when the user explicitly references RDE concepts: 'AEM RDE', 'Rapid Development Environment', `aio aem rde`, `aio aem:rde`, `aem-rde`, RDE snapshots, RDE deploy/install, `rde install`, `rde inspect`, `rde status`, `rde history`, `rde reset`, the `@adobe/aio-cli-plugin-aem-rde` package, or Cloud Manager program/environment configuration that is specifically for an RDE environment. Do NOT activate on generic AEMaaCS phrases like 'deploy to AEM Cloud', 'push my bundle', 'tail the publish log', 'cloud sandbox', or unqualified 'dispatcher-config / frontend / env-config deployments' — those belong to Cloud Manager pipelines, not RDE. This skill is in beta. Verify all outputs before applying them to production projects.

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 a punchy sizzle reel from a video using Adobe Quick Cut. Use this skill whenever a user wants to cut, trim, or shorten a video into highlights — including phrases like "make a sizzle reel", "make a highlight reel", "quick cut this", "cut the best parts", "shorten this video", "make a highlight clip", "summarize this video visually", or any request to produce a shorter edited version of a video. Use this skill for Quick Cut requests before suggesting manual editing in Premiere. Requires the user to upload a video 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。

Obtains a valid Adobe IMS access token for the DA (Document Authoring) API. Use this skill as a prerequisite step whenever another skill needs to call admin.da.live — for example, before pushing HTML content, listing documents, or triggering a DA preview. Do NOT use this skill if you already have a valid DA_TOKEN in scope from a previous step in the same session.

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。

Compare two versions of an AEM Edge Delivery Services page to identify what changed. Fetches preview vs live, or two different URLs, and produces a detailed content diff showing added, removed, and modified content, metadata, and blocks. Use when reviewing changes before publishing, auditing content modifications, or tracking content evolution.

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 and run tests for Adobe App Builder actions and UI components. Scaffolds Jest unit tests, integration tests against deployed actions, contract tests for Adobe API interactions, and React component tests using Testing Library. Provides mock helpers for State, Files, Events SDKs, @adobe/aio-lib-* clients, ExC Shell context (@adobe/exc-app), and UIX Guest SDK (@adobe/uix-guest). Use this skill whenever the user mentions testing App Builder actions, writing unit tests for Runtime actions, creating integration tests, mocking Adobe SDKs, setting up test fixtures, running aio app test, or wants to verify action behavior before deployment. Also trigger when users mention Jest configuration for App Builder, test coverage, CI test setup, React component test, Testing Library, UI test, Provider wrapper, test my page, test my form, test my table, test my component, mock shell context, mock extension context, debug test failures, or fix Jest errors.

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。

Quick repo-hygiene and consistency checks before committing.

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 one bounded adversarial pass when the user explicitly requests a report-style stress test or ROSE identifies a concrete material loophole in an existing strategy, spec, plan, review, or claim; do not trigger for an interactive grill/frontier interview or merely before write-back, implementation, reconciliation, or completion.

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。

Conduct one bounded evidence-grounded code review when the user explicitly requests review or ROSE names a concrete unresolved correctness/quality risk; do not trigger automatically after implementation, before every merge, for every bug fix/refactor, or as a completion 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。

Review a Go design spec before implementation begins - dispatch a subagent that checks a design doc for completeness, consistency, and idiomatic Go (simplicity, small consumer-defined interfaces, explicit wrapped errors, context propagation) plus Cobra/Viper conventions where applicable. Use when a user has a Go spec to review, asks "is this spec ready?", or is about to implement from a written design. Distilled from spf13/go-skills and adapted to this repo's conventions.

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。

Optimizes CI/CD pipeline speed by implementing effective caching for dependencies, Docker layers, build outputs, and test results. Provides before/after performance metrics and best practices. Use for "CI caching", "pipeline optimization", "build speed", or "cache 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。

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 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 designing a Spark feature or writing or materially revising a design proposal that needs repository-first research, user input on unresolved key choices, and an owner-aligned implementation plan before code changes.

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 a complete research workflow — its instructions, skills, data boundaries, and tool connections — must be assessed for portability across AI agents or environments, so each component is explicitly mapped before migration rather than assumed to transfer.

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 for the search-planning stage of a literature review, when database lanes and language layers must be chosen, when DOI coverage policy is unclear, or when inclusion and exclusion criteria need drafting before any source is read; not for running the screening and PRISMA pipeline of a formal review, which is prisma-scoping-review-pipeline.

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 selecting a statistical test with AI consultation, when assumptions need checking against the actual data, when an analysis plan or decision log must be written before running anything, or when results need APA-style reporting with effect sizes.

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 when a study needs a preregistration or a frozen analysis plan, when confirmatory and exploratory analyses must be separated, or when every deviation from the registered plan must be logged before the result is reported.

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 construct, scale, or key term crosses Turkish and English and conceptual equivalence must be audited: translation and back-translation, construct drift, and culturally bound meaning, before measurement or cross-cultural 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 an ethics committee or IRB application involves AI anywhere in the pipeline, when KVKK, GDPR, or EU AI Act duties must be mapped to a study, or when consent and disclosure language about AI use needs drafting before submission.

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 sources must stay traceable across sessions and years, when each reference needs a passport recording where it was found, how it was verified, and where it is cited, or when a draft needs a cited-but-unverified sweep before submission.

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。