1,718 件 ・ 関連度順
概要と使いどころ
Delivers changes incrementally in thin, verifiable slices. Use when implementing any feature or change that touches more than one file, or when picking up the next task from a plan. Use when rolling a change out behind a feature flag, when you're about to write a large amount of code at once, or when a task feels too big to land in one step.
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 Figma Plugin API scripts for canvas writes, inspections, variables, and design-system work. Prerequisite for every other Figma skill in this catalogue.
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 truth scoring, code quality verification, and automatic rollback system with 0.95 accuracy threshold for ensuring high-quality agent outputs and codebase reliability.
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。
Show a chart, diagram, table, report or mockup inline in this Orca chat as an HTML page. Use when a visual would help the user understand your answer. Only available when the ORCA_CHAT_VISUALS_DIR environment variable is set.
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 initial setup, configure global CLI settings, manage environment variables, check for updates, and configure autostart via the CLI setup and config commands.
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。
Step-by-step agent workflow to configure the OpenAI Codex CLI on any machine (Linux, macOS, Windows) to use OmniRoute as an OpenAI-compatible backend. Detects OS and shell, writes config.toml and 7 named profiles, sets environment variables, and verifies the setup.
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 the corpus benchmark — booster locally, optional Gemini/Sonnet/Opus baselines — and persist a verifiable measured-vs-claimed table
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。
Detect and flag personally identifiable information (PII) in text, code, and configurations. Use before committing code, writing logs, storing data, or sending model responses that might contain emails, phone numbers, SSNs, API keys, or passwords.
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 truth scoring, code quality verification, and automatic rollback system with 0.95 accuracy threshold for ensuring high-quality agent outputs and codebase reliability.
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 PWA capabilities, implementing a service worker, or improving the experience for users on unreliable network connections.
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 to connect Plaid and read linked financial accounts: metadata, balances, transactions, recurring transactions, liabilities, and investments.
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。
The HyperFrames composition contract — build one renderable project. Use for composition structure, the `data-*` timing attributes, `class="clip"`, tracks, sub-compositions, variables, framework-owned media playback, deterministic-render rules, and validation. Read before writing composition HTML.
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。
Interacting with Mediabunny
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。
Glass shards fly in through fog and tile themselves into the headline. HyperFrames block, 1920×1080, 12.16s, 19 variables.
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。
A single feature card orbits a dot sphere on approved Blender camera motion. HyperFrames block, 1920×1080, 10s, 4 variables.
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。
The HyperFrames composition contract — build one renderable project. Use for composition structure, the `data-*` timing attributes, `class="clip"`, tracks, sub-compositions, variables, framework-owned media playback, deterministic-render rules, and validation. Read before writing composition HTML.
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。
A tiled headline surface flips cell by cell under a sweeping depth field to reveal the rear headline. HyperFrames block, 1920×1080, 8s, 18 variables.
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。
A wireframe portal bursts open, the title comes through, then its letters swap into a second phrase. HyperFrames block, 1920×1080, 8s, 9 variables.
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。
A chain of bevelled cuboids rides a travelling wave as a content carousel. HyperFrames block, 1920×1080, 6.666666666666667s, 40 variables.
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。
An orbiting camera follows an ice logo as it breaks apart, reforms into two text moments, and fades. HyperFrames block, 1920×1080, 22.5s, 216 variables.
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。
Leaves sweep through the frame and part to reveal the headline. HyperFrames block, 1920×1080, 12s, 11 variables.
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。
When the user wants to generate, iterate, or scale ad creative — headlines, descriptions, primary text, or full ad variations — for any paid advertising platform. Also use when the user mentions 'ad copy variations,' 'ad creative,' 'generate headlines,' 'RSA headlines,' 'bulk ad copy,' 'creative testing,' 'write me some ads,' 'Facebook ad copy,' 'Google ad headlines,' 'LinkedIn ad text,' 'static ads,' 'ad templates,' 'iMessage ad,' 'ChatGPT ad,' 'creative strategy,' 'creative roadmap,' 'creative retro,' 'hook writing,' 'creative review page,' 'motion video ad,' 'faceless video ad,' 'UGC ad,' 'greenscreen ad,' 'TikTok/Reels ad format,' 'Meta ad format tier list,' or 'creative format taxonomy.' Use it to produce or iterate ad copy at scale. Copy avoids AI tells like 'it's not X, it's Y' reveals. For campaign strategy and targeting, see ads. For landing page copy, see copywriting. Test hypotheses must be falsifiable, naming the metric, the comparison, and the expected direction.
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。
Command-line interface for n8n workflow automation platform. Manages workflows, executions, credentials, variables, and tags. Based on n8n Public API v1.1.1 (n8n >= 1.0.0).
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。
Supports multivariate severity assessment and exploratory endpoint-time score forecasting for laboratory animal studies using the RELSA (RELative Severity Assessment) score and ARIMA-based foRcast forecasting. Use when combining welfare readouts — body weight or weight loss, body temperature, clinical or nesting scores, biomarkers, activity, heart rate, burrowing, wheel running — into one severity score per animal per day, when asking which animals are at risk of reaching a humane endpoint at a specified future observation time, when defining attention/danger zones or thresholds on a severity scale by kernel density estimation, or when reporting severity for a 3Rs, refinement, animal-welfare, or EU Directive 2010/63/EU severity-assessment context. Covers directionality ("turned" variables), baseline normalization, reference sets, RELSA weights, ARIMA prediction intervals, and RMSE/PICP/MPIW evaluation.
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。