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Auto-review pipeline — reads the full CEO, design, eng, and DX review skills from disk and runs them sequentially with auto-decisions using 6 decision principles. Surfaces taste decisions (close approaches, borderline scope, codex disagreements) at a final approval gate. One command, fully reviewed plan out. Use when asked to "auto review", "autoplan", "run all reviews", "review this plan automatically", or "make the decisions for me". Proactively suggest when the user has a plan file and wants to run the full review gauntlet without answering 15-30 intermediate questions. (gstack) Voice triggers (speech-to-text aliases): "auto plan", "automatic 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。

Self-tuning question sensitivity + developer psychographic for gstack (v1: observational). Review which AskUserQuestion prompts fire across gstack skills, set per-question preferences (never-ask / always-ask / ask-only-for-one-way), inspect the dual-track profile (what you declared vs what your behavior suggests), and enable/disable question tuning. Conversational interface — no CLI syntax required. Use when asked to "tune questions", "stop asking me that", "too many questions", "show my profile", "what questions have I been asked", "show my vibe", "developer profile", or "turn off question tuning". (gstack) Proactively suggest when the user says the same gstack question has come up before, or when they explicitly override a recommendation for the Nth time.

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Pull data from a web page. First call on a new intent prototypes the flow via $B primitives and returns JSON. Subsequent calls on a matching intent route to a codified browser-skill and return in ~200ms. Read-only — for mutating flows (form fills, clicks, submissions), use /automate. Use when asked to "scrape", "get data from", "pull", "extract from", or "what's on" a page. (gstack)

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Guide for testing code changes in AEM Edge Delivery projects including blocks, scripts, and styles. Use this skill after making code changes and before opening a pull request to validate functionality. Covers unit testing for utilities and logic, browser testing with Playwright, linting, and guidance on what to test and how

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**Run FIRST (before any other skill or task)** when workspace root has no AGENTS.md and the repo is an AEM Cloud Service project. Creates AGENTS.md and CLAUDE.md (tailored via pom.xml). Applies on every user request until AGENTS.md exists — not only the first chat. Never overwrites existing files.

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Analyze content sequences within a section and provide neutral descriptions for AEM Edge Delivery Services. Invoked per section during page import to identify breaking points between default content and blocks.

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Analyze content sequences and determine authoring approach (default content vs blocks). Validates block selection and section styling for import/migration to AEM Edge Delivery Services.

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, implement, deploy, and debug Adobe Runtime actions with consistent layout, validation, and error handling. Use this skill whenever the user needs to add actions to an App Builder project, understand action structure (params, response format, web/raw actions), configure actions in the manifest, use App Builder SDKs (State, Files, Events, database), deploy and invoke actions via CLI, debug action issues, or implement patterns such as webhook receivers, custom event providers, journaling consumers, large payload redirects, action sequence pipelines, and Asset Compute workers. Also trigger when users mention serverless functions in Adobe context, action logging, IMS authentication for actions, or cron-style scheduled actions.

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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。

Comprehensive dimension analysis and reporting for CJA. Use this skill whenever the user wants to analyze one or more dimensions — including cardinality, distribution/skew, trends, anomalies, data quality errors, comparisons, and forecasting. Also trigger when someone asks "what are the top values for...", "dimension health", "explore this dimension", "dimension dashboard", "dimension statistics", "data quality check on a dimension", "dimension cardinality", "dimension trends", "dimension skew", "dimension anomalies", "compare dimensions", or any similar request to understand what's inside a CJA dimension. Produces an interactive HTML dashboard or a markdown report. Works with the CJA MCP server.

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Resize photos and videos to exact pixel dimensions or aspect ratios using Adobe tools. Use this skill whenever a user wants to resize, scale, or change the dimensions of an image or video file — including phrases like "resize this to 1920x1080", "make this 4K", "scale to 800x600", "change the aspect ratio to 16:9", "resize my video", "make the image smaller", "crop to square", "fit this to a specific size", "resize for print", "resize for web", "make it 300 DPI ready", "change canvas size", "resize a batch of photos", or any request specifying target dimensions (W×H, ratio, or named size like "4K", "HD", "A4"). Also triggers for: "make this fit a specific size", "resize to [any dimension]", "I need this at [WxH]", "scale my video down", "change resolution", "downscale", "upscale". NOT for social media platform sets (use adobe-create-social-variations for that). Uses image_crop_and_resize for photos, video_resize for videos.

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。

Bulk-retouch a folder of portrait photos using Adobe tools — designed for wedding photographers and event photographers who need fast, walk-away batch processing. Use this skill when the user says "retouch my photos", "batch process these portraits", "process my wedding photos", "clean up this folder of images", "run my headshots through Adobe", or uploads/selects a folder of photos and wants them polished and ready to review. Automatically applies auto-straighten, auto-tone, and auto-light to every image. Outputs a preview grid and download folder. Access: 🔐 Signed-In required | Gen AI: ❌

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。

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。

Produces a compact KPI digest showing how key metrics changed over a period and what's driving the movement. Use this skill when someone asks for a performance summary, a weekly recap, a morning briefing, a KPI update, or any variation of "how did we do this week/month." Also trigger for requests like "give me a performance overview," "what moved in the last 7 days," "pull our KPI report," or "summarize our metrics."

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 code for AEM Edge Delivery Services projects. Use at the end of development (before PR) for self-review, or to review pull requests. Validates code quality, performance, accessibility, and adherence to EDS 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。

Review, commit, push, and create a pull request through the current branch's configured upstream. Use when you want to ship deliberate changes end-to-end without assuming a particular remote or base branch.

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。

Babysit a GitHub pull request during a user-approved monitoring window by polling review comments, CI checks/workflow runs, and mergeability state. Diagnose failures, retry likely flaky failures up to 3 times, auto-fix/push branch-related issues when appropriate, and report fresh review feedback. Use when the user asks Codex to monitor a PR, watch CI, handle review comments, or keep an eye on failures and feedback on an open PR.

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Use when implementing or debugging ANY network request, API call, or data fetching. Covers fetch API, React Query, SWR, error handling, caching, offline support, and Expo Router data loaders (`useLoaderData`).

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Forces the laziest solution that actually works, simplest, shortest, most minimal. Channels a senior dev who has seen everything: question whether the task needs to exist at all (YAGNI), reach for the standard library before custom code, native platform features before dependencies, one line before fifty. Supports intensity levels: lite, full (default), ultra. Use on ANY coding task: writing, adding, refactoring, fixing, reviewing, or designing code, and choosing libraries or dependencies. Also use whenever the user says "ponytail", "be lazy", "lazy mode", "simplest solution", "minimal solution", "yagni", "do less", or "shortest path", or complains about over-engineering, bloat, boilerplate, or unnecessary dependencies. Do NOT use for non-coding requests (general knowledge, prose, translation, summaries, recipes).

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End-to-end Solana development playbook (Jan 2026). Prefer Solana Foundation framework-kit (@solana/client + @solana/react-hooks) for React/Next.js UI. Prefer @solana/kit for all new client/RPC/transaction code. When legacy dependencies require web3.js, isolate it behind @solana/web3-compat (or @solana/web3.js as a true legacy fallback). Covers wallet-standard-first connection (incl. ConnectorKit), Anchor/Pinocchio programs, Codama-based client generation, LiteSVM/Mollusk/Surfpool testing, and security checklists.

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Generate Mermaid diagrams from code, architecture, or concepts. Use when you need to visualize code flow, system architecture, data relationships, state machines, sequences, class structures, or any other diagrammable concept.

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Triage issues through a state machine driven by triage roles. Use when user wants to create an issue, triage issues, review incoming bugs or feature requests, prepare issues for an AFK agent, or manage issue workflow.

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Overrides default LLM truncation behavior. Enforces complete code generation, bans placeholder patterns, and handles token-limit splits cleanly. Apply to any task requiring exhaustive, unabridged output.

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Whole-repo audit for over-engineering. Like ponytail-review, but scans the entire codebase instead of a diff: a ranked list of what to delete, simplify, or replace with stdlib/native equivalents. Use when the user says "audit this codebase", "audit for over-engineering", "what can I delete from this repo", "find bloat", "ponytail-audit", or "/ponytail-audit". One-shot report, does not apply fixes.

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。