「processing」の検索結果

Execute the implementation plan by processing and executing all tasks defined in tasks.md

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 tools for the support agent. Use when adding new capabilities like refund processing, license transfer, knowledge lookup, or any agent action.

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。

Expert payment integration specialist mastering payment gateway integration, PCI compliance, and financial transaction processing. Specializes in secure payment flows, multi-currency support, and fraud prevention with focus on reliability, compliance, and seamless user experience.

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。

Intelligent pattern selection for Fabric CLI. Automatically selects the right pattern from 242+ specialized prompts based on your intent - threat modeling, analysis, summarization, content creation, extraction, and more. USE WHEN processing content, analyzing data, creating summaries, threat modeling, or transforming text.

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。

Emoji reactions and thinking indicators for XMTP agents. Use when adding reactions to messages or showing processing state with thinking emoji. Triggers on emoji reactions, thinking indicator, or message acknowledgment.

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 robust Python automation with full logging and safety checks. Use when tasks need complex data processing, authenticated API work, conditional file operations, or error handling beyond simple shell 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。

Orchestrates AWS data pipelines using @aws-sdk/client-s3 and @aws-sdk/client-sqs. Manages S3 object lifecycle with PutObjectCommand/GetObjectCommand, processes SQS message queues via ReceiveMessageCommand with long polling, and configures S3 event notifications to SQS for event-driven processing.

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。

Extract structured intelligence from audio using the AssemblyAI API with sentiment analysis, entity detection, topic modeling, and auto-chapter generation. Uses the assemblyai Python SDK for transcript processing pipelines.

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。

Separates audio tracks into individual stems (vocals, drums, bass, other) using Meta's Demucs neural network model via the demucs Python package. Supports batch processing of WAV and MP3 files, outputs isolated stems in FLAC or WAV format, and integrates with FFmpeg for format conversion and loudness matching post-separation.

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。

Nature-style materials science manuscript reviewer skill for testing materials design, synthesis, processing, structure-property, mechanism, stability, scalability, computational prediction and application claims against materials evidence chains.

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。

Reference patterns for search, optimization, and greedy algorithms. Covers binary search (classic and on-answer), two pointers, sliding window, greedy strategies, prefix sums, merge intervals, and monotonic stack. Use when solving problems that involve searching sorted data, optimizing over constraints, processing subarrays/substrings, or reducing range 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。

Use ManagedCode.MarkItDown when a .NET application needs deterministic document-to-Markdown conversion for ingestion, indexing, summarization, or content-processing workflows.

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。

Executes distribution calculations through partnership waterfall with preferred return, GP catch-up, and carried interest allocation. Use when calculating distributions, processing waterfall mechanics, or determining carry payments.

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。

Coordinates loan trading with LSTA standard documentation, delayed settlement compensation, and trade settlement mechanics. Use when managing loan trades, processing LSTA documentation, or coordinating trade settlement.

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。

Structures capital call execution with notice preparation, pro-rata allocation, default remedy provisions, and wire coordination. Use when processing capital calls, calculating LP contributions, or managing call logistics.

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。

Assesses critical mineral investments with supply chain mapping, geopolitical risk, and processing infrastructure analysis. Use when evaluating critical minerals, analyzing lithium/cobalt supply, or assessing rare earth 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。

Validate systems and processes against GDPR/CCPA privacy regulations, privacy-by-design principles, ADA/WCAG accessibility standards, data processing agreements (DPAs), and provide compliance checklists with regulatory change monitoring guidance.

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。

Fintech engineering expertise — payment processing (Stripe, Plaid), PCI DSS compliance, financial data modeling (double-entry bookkeeping), fraud detection patterns, bank-grade security (encryption, tokenization), open banking APIs, cryptocurrency/blockchain integration, regulatory compliance (KYC/AML), and idempotent financial transaction design. Use for payment systems, banking apps, trading platforms, and fintech infrastructure.

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。

Data processing expert including parsing, transformation, and validation

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。

Prepare and ship an iOS build to TestFlight — runs the submission pre-flight checks, fixes the config that blocks uploads/processing, then walks internal→external beta review. Use when releasing an iOS build to testers.

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。

Edit images with precision using ImageMagick 7, sips, transparent-background, and Pillow — with intelligent routing to AI semantic editing (Gemini/nano-banana-pro) for content-aware operations. Covers cropping, resizing, compositing, annotating, format conversion, color adjustment, background removal, batch processing, and montage creation. Triggers on image editing, crop, resize, composite, annotate, remove background, format conversion.

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。

Reference WebGPU APIs, TSL syntax, node materials, WGSL integration, compute shaders, and post-processing in Three.js. For complete particle canvases use threejs-particle-canvas; for GLSL shaders use rocaille-shader. Triggers on TSL shader, WebGPU renderer, node material, WGSL, GPU compute, WebGPU 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。

Doctrine ORM best practices for Symfony: entity mapping as source of truth, repositories, DQL/QueryBuilder with parameters, N+1 prevention with fetch joins, relations (cascade/fetch/orphanRemoval), lifecycle events, batch processing, and generated migrations. Apply when: writing or reviewing Doctrine entities, repositories, and queries. Activated automatically by symfony-plugin/stack.md as a convention skill for the development and database phases. Do NOT use this skill for: - PHP language idioms — see php-foundation:php-conventions. - Controllers/services/forms — see symfony-plugin:symfony-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。

Pythonic wrapper around RDKit with a simplified interface and sensible defaults. Preferred for standard drug discovery work — SMILES/SELFIES/InChI conversion, molecule standardization and sanitization, descriptors, ECFP and other fingerprints, Tanimoto distance matrices, Butina clustering and diverse subset picking, Bemis-Murcko scaffolds and scaffold splits, BRICS/RECAP fragmentation, 3D conformer generation, SDF/CSV/Excel and cloud I/O, and parallel processing via n_jobs. Returns native rdkit.Chem.Mol objects, so it composes with RDKit throughout. Also trigger on datamol, `import datamol as dm`, dm.to_mol, dm.standardize_mol, dm.cluster_mols, or dm.pick_diverse. For advanced control or custom parameters, use the rdkit skill directly.

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。