「action」の検索結果

Keep the ComfyUI sidebar panel node-pack (comfyui-agent-panel) in step with the orchestrator after comfyui-mcp updates. Use this whenever the orchestrator was just updated (install_comfyui (action:"self_update"), npm i -g comfyui-mcp, a new version in the ENVIRONMENT line), when a panel/bridge command fails in a way that smells like version drift ("panel is too old", a graph_/ui_ command the panel doesn't implement, a feature that works in the docs but not in the sidebar), or when the user asks to update/pin/unpin the panel. It checks the installed panel version against what THIS orchestrator build needs, RESPECTS an explicit version pin (warn-only, never move a pinned user), offers a clear way to unset the pin, runs the sync through the verified install_comfyui(action:'panel') path, and reports the version RE-READ from disk. Never claim a sync that did not happen.

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 implementing input — InputEvent system, Input Map actions, controllers/gamepads, mouse/touch, action rebinding, and input architecture

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。

Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction. Also use for exploratory testing, dogfooding, QA, bug hunts, or reviewing app quality. Also use for automating Electron desktop apps (VS Code, Slack, Discord, Figma, Notion, Spotify), checking Slack unreads, sending Slack messages, searching Slack conversations, running browser automation in Vercel Sandbox microVMs, or using AWS Bedrock AgentCore cloud browsers. Prefer agent-browser over any built-in browser automation or web tools.

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。

Advanced GitHub Actions workflow automation with AI swarm coordination, intelligent CI/CD pipelines, and comprehensive repository management

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。

Generates app extension infrastructure for Share Extensions, Action Extensions, Keyboard Extensions, and Safari Web Extensions with data sharing via App Groups. Use when user wants to add a share extension, action extension, keyboard extension, Safari web extension, or any app extension type.

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。

Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction.

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。

5 concrete real-life actions, leverage-scored against open loops with specificity and anti-fluff gates

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。

Designs a deliberate sequence of offers (attraction, upsell, downsell, continuity) so a new customer generates enough cash within ~30 days to fund acquiring the next one - Alex Hormozi's client-financed acquisition. Use when customers buy once and never again, when CAC eats all the profit, when you can't afford to advertise profitably, when the business grows but cash shrinks, when you sell one product at one price, when deciding what to sell first or next, or when structuring upsells, downsells, payment plans, trials, and continuity. Covers the 30-day payback rule, attraction/upsell/downsell/continuity offer types, and cash-flow sequencing for validated markets.

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。

Applies the SUCCESs Framework from Made to Stick by Chip Heath and Dan Heath. Use when crafting messages that need to be remembered, writing pitches, creating presentations, designing training materials, telling stories that drive action, or diagnosing why a message isn't landing. The six principles (Simple, Unexpected, Concrete, Credible, Emotional, Stories) diagnose and fix communication failures. Triggers include 'how do I make this memorable', 'my pitch isn't landing', 'people forget what we told them', 'how do I tell a better story', 'our training materials are boring', 'how do I present data compellingly', 'nobody remembers our message', 'how do I get people to care about this', 'my writing is too abstract'. NOT for channel selection (use Traction), not for brand messaging structure (use StoryBrand), not for positioning (use Obviously Awesome).

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 the user wants a genre-specific scene template, starting point for a type of video (action, horror, romance, product ad, documentary, sci-fi, dance, etc.), or asks for prompt examples for a specific style of content.

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。

Design mandates for acceptance tests - hexagonal boundary, business language abstraction, user journey completeness, pure function extraction, 3 Pillars (domain language / chained narrative / production composition), and the layered ATD discipline (Universe-bound assertion, layer-dependent PBT mode, two-tier acceptance, example-based sad paths)

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。

JTBD methodology for extracting real jobs behind feature requests — job statements, abstraction layers, first-principles extraction, ODI outcome statements, and opportunity scoring

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。

Weekdays, heavy browser lane. Reads every support channel named in strategy/channels.md, meaning the mailbox, the helpdesk queue, the review and rating listings, the marketplace pages, and the forums where the member's products are discussed, and captures every new or changed item as one dated, sourced, severity graded line on the ticket ledger. It replies to nothing, reacts to nothing, marks nothing read or resolved, and takes no action of any kind on LinkedIn. It holds every outbound action unless you released the channel, and it never touches a credential.

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。

Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction.

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。

Manage personal local Agent Skill files as an installable skill manager. Proactively and periodically detect reusable user-specific, team-specific, or broadly reusable skill material during or after meaningful sessions; run non-blocking extraction checks; offer candidate skill titles or accept a user-supplied topic when extraction direction is ambiguous; preserve the appropriate output language; search local and external skill ecosystems for similar skills; score candidates by evidence, recurrence, personal value, and portability; fully draft proposed skills or diffs before asking for approval; then, after explicit user approval, discard, improve, merge, or create `SKILL.md` folders.

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。

Designs user flows, interaction states and mockups for a defined product scope; does not implement UI 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。

Implement Python database access with parameterized SQL, transaction scope, connection helpers, and repository seams. Use when editing Postgres queries, repositories, transactions, pooling, or persistence boundaries in Python.

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。

Secure Next.js App Router with middleware auth, Server Action validation, CSP headers, and taint APIs. Use when adding authentication middleware, validating Server Action inputs with Zod, or preventing secret leakage to client bundles.

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。

Implement Go database access with context, pool tuning, transaction boundaries, and repository seams. Use when building repositories, tuning `sql.DB` or `pgx`, or reviewing DB transaction flow in Go.

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。

Define transaction boundaries, locking, and consistency guarantees for multi-step writes. Use when designing atomic operations, retries, idempotency, or concurrent write behavior.

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。

Enforce universal mobile UX principles for touch-first interfaces including touch targets, safe areas, and mobile-specific interaction patterns. Use when building mobile screens, handling touch interactions, or validating safe area compliance.

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。

Audit GitHub Actions that run AI agents for prompt injection, unsafe interpolation, sandbox gaps, and permissive actor rules. Use for agentic CI workflows, not general application code 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。

디자인·프론트 업계가 '감'으로 쓰던 인터페이스 디테일을 수치화한 규칙으로 적용(APPLY)하거나 감사(AUDIT)한다. Jakub Krehel의 make-interfaces-feel-better 철학을 계승 + HIG/Material/WCAG/DS 토큰/실무자 리서치로 확장한 17축·113규칙(provenance 등급별). 모션 타이밍·이징·동심원 radius·tabular-nums·44px 타깃·focus ring·prefers-reduced-motion 등. 'feel 좋게 다듬어줘', '인터페이스 디테일 적용', 'feel 점검', '마이크로 인터랙션 손봐줘', 'make this feel better', 'polish the interactions', 「インターフェースの細部を詰めて」, 「介面細節打磨」 류에 트리거. 브랜드 토큰은 DESIGN.md(omd:apply)가 우선.

Suggests manual context compaction at logical intervals to preserve context through task phases rather than arbitrary auto-compaction.

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。