2,287 件 ・ 関連度順
概要と使いどころ
Implements automated data deletion workflows for GDPR Article 17 right to erasure and retention period expiry. Covers cascading deletion across dependent systems, dependency handling for referential integrity, confirmation logging, and audit trail generation. Activate for automated deletion, erasure automation, data purge, retention expiry queries.
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。
Axesso Data Service - Amazon integration. Manage data, records, and automate workflows. Use when the user wants to interact with Axesso Data Service - Amazon data.
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。
ASIN Data API integration. Manage data, records, and automate workflows. Use when the user wants to interact with ASIN Data API data.
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。
AnonyFlow integration. Manage data, records, and automate workflows. Use when the user wants to interact with AnonyFlow data.
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。
Creates visual representations of system structure including architecture diagrams, data flow diagrams, deployment diagrams, and sequence diagrams. Use when Claude needs to visualize system components, infrastructure, data flows, or interactions. Supports Mermaid (recommended for Markdown/GitHub), PlantUML (for detailed UML), and Graphviz/DOT (for complex networks). Trigger when users request diagrams, visualizations, or ask to "show", "diagram", "visualize", or "map out" system architecture, infrastructure, data flows, or component interactions.
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。
Sync, validate, and apply App Store metadata with the current asc canonical metadata workflow. Use when updating metadata, localizations, keywords, or migrating legacy fastlane metadata.
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。
Read and manipulate Flow Cytometry Standard (FCS) files. Covers loading data, accessing parameters, and basic data exploration. Use when loading and inspecting flow or mass cytometry data before preprocessing.
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。
Reconstructs the workflow behind a past artifact by querying local ax session, recall, and commit history data. Use when a user asks "what made X work", "how was Y shipped/built", "extract workflow from <date|sha>", "workflow around <topic>", "recipe for this feature", or similar. It finds the anchor session or commit, inspects ax sessions, ax recall, and ax sessions show, and returns an ordered read-only narrative with decisions and evidence.
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。
Build database-powered applications with Baserow, the open-source no-code database. Use when a user asks to create spreadsheet databases, build API-connected workflows, manage relational data, or self-host Baserow as an Airtable alternative.
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。
AKF — The AI Native File Format workflow skill. Use this skill when the user needs The AI native file format. EXIF for AI — stamps every file with trust scores, source provenance, and compliance metadata. Embeds into 20+ formats (DOCX, PDF, images, code). EU AI Act, SOX, HIPAA auditing and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
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。
Route data-related requests to the right Monte Carlo skill or workflow. USE WHEN alerts, incidents, data broken, stale, coverage gaps, data quality, or any ambiguous data observability request.
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。
Remix v2 data loading and mutations. Use when writing loaders, actions, deferred data, revalidation logic, or pending state. Triggers on loader, action, useLoaderData, useActionData, json(), defer(), <Await>, shouldRevalidate, useRevalidator, useNavigation, useTransition (v1 holdover).
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。
Deprecated alias. This skill was renamed to `deepline-research`. Use when a user or script still invokes `/deepline-pre-research`: immediately load and follow the `deepline-research` skill instead. Triggers: pre-research, source discovery, provider strategy, research data sources, ScrapeCreators, X/Twitter data, Reddit comments, public and private datasets, CRM data, workflow data, custom language, messaging language, pain language.
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 asked to map or analyze flows, pipelines, processes, or sequences of events in this repo — e.g. "mapa el flujo", "flow", "pipeline", "ciclo de vida", "trace the request", "how does the build/release flow work", "diagrama del flujo". Maps data flows, request lifecycles, CI/CD pipelines, and state transitions with verified file:line evidence. Distinct from analyze-code (which maps code structure); this skill maps movement over time.
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。
Orchestrate end-to-end machine learning pipelines using Prefect or Airflow with DAG construction, task dependencies, retry logic, scheduling, monitoring, and integration with MLflow, DVC, and feature stores for production ML workflows. Use when automating multi-step ML workflows from data ingestion to deployment, scheduling periodic model retraining, coordinating distributed training tasks, or managing retry logic and failure recovery across pipeline stages.
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。
Set up systematic data labeling workflows using Label Studio or similar tools. Implement quality controls, measure inter-annotator agreement, manage labeler teams, and integrate labeled data into ML training pipelines. Use when starting a supervised ML project that requires labeled training data, when model performance is limited by insufficient labeled examples, when labeling text, images, audio, or video, or when implementing active learning to prioritize the most valuable examples.
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 themed Mermaid flowchart diagrams from putior workflow data. Covers theme selection (9 themes including 4 colorblind-safe), output modes (console, file, clipboard, raw), interactive features (clickable nodes, source info), and embedding in README, Quarto, and R Markdown. Use after annotating source files and ready to produce a visual diagram, when regenerating a diagram after workflow changes, or when switching themes or output formats for different audiences.
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。
Turn a local talking-head / 口播 video into metadata, transcript, and an AI-composed card-based video where the agent composes cards by cloning styled templates and filling them (designing bespoke only when content needs it), then renders to MP4. Ships with the Interflow AI club sign-off ("Interflow AI 出品"). Use when the user asks for interflow-video-cut, 口播成片, talking-head repurposing, video takeaways, transcript cleanup, or turning a spoken video into a captioned card video.
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。
Build a full feature in this Flutter repository that includes backend or storage data flow: read API schema, create DTOs, map DTOs to entities, add Riverpod use cases, connect feature state, and render UI data. Use when a task goes beyond a screen and needs real data integration.
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 generating or editing diagrams, charts, visual assets, posters, UI mockups, product images, infographics, academic figures, comics, avatars, storyboards, brand boards, or image-edit workflows, especially when exported PNGs need visual QA and bounded self-repair. Prefer deterministic Mermaid/SVG/HTML/canvas sources for text-heavy diagrams; use HTML technical diagrams for browser-ready system blueprints, architecture, deployment topology, agent runtime, memory flow, before-after architecture, workflow, sequence, data-flow, lifecycle, runbook, PII/data-lineage, and state-machine diagrams. Do not use for ordinary UI polish without generated imagery.
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。
Access ENCODE uniform analysis pipelines, generate user-specific Nextflow/WDL pipelines, manage compute resources, and integrate with cloud platforms. Use when the user wants to understand ENCODE pipelines, run pipelines on their own data, generate custom Nextflow workflows from ENCODE pipeline code, check compute requirements (CPU/GPU/memory), run pipelines in background, or integrate with Google Cloud, AWS, or other cloud platforms. Also use when the user asks about ENCODE pipeline outputs, processing standards, software versions, or wants to replicate ENCODE processing. Covers local execution, HPC, and cloud deployment with resource-aware scheduling. Use this skill for ANY pipeline execution, workflow generation, or compute resource management task involving ENCODE data.
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。
Analyze flow metrics to identify delivery bottlenecks and improve throughput. Use when the user says "flow metrics", "why is delivery slow", "cycle time analysis", "WIP analysis", "throughput review", "what's our lead time", "DORA metrics", "where is work getting stuck", "Kanban metrics", or wants to diagnose delivery performance using data - even if they don't explicitly say "flow metrics review". Based on "Making Work Visible" by Dominica DeGrandis (WIP limits, flow blockers, time thieves) and "Accelerate" by Forsgren, Humble & Kim (DORA metrics, delivery performance indicators).
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。
Write a data pipeline design document. Use when the user says "pipeline design doc", "document this pipeline", "pipeline architecture doc", "data flow document", "how does this pipeline work", "design doc for ETL", "pipeline spec", or needs to capture the architecture, data flow, and operational details of a data pipeline - even if they don't explicitly say "design doc".
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 writing, auditing, or troubleshooting Salesforce Validation Rules. Triggers: 'validation rule', 'required field formula', 'rule fires unexpectedly', 'integration failing validation', 'data quality', 'errorConditionFormula', 'errorDisplayField', 'errorMessage 255 characters', 'ValidationRule metadata', 'validationRule-meta.xml', 'deploy validation rule inactive', 'bypass custom permission', 'FIELD_CUSTOM_VALIDATION_EXCEPTION', 'validation rule on custom metadata type', 'compound field validation rule', 'require at least one child record before a stage', 'HasOpportunityLineItem'. NOT for Flow-based validation — use admin/flow-for-admins for that.
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。