「format」の検索結果

Fetch and read transcripts from YouTube videos. Use when you need to summarize a video, answer questions about its content, or extract information from it.

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Decide where to save any piece of information — monday.com, local file, daily notes, or MEMORY.md. Use this skill before saving anything to ensure the right destination. Prevents local clutter and ensures the owner can access all relevant content in monday.com.

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MANDATORY parallel execution patterns (30x speedup), monitor metrics aggregation, --output tsv formatting, and common pitfalls

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Use when working with Checkov — checkov infrastructure-as-code security scanning. Covers Terraform, CloudFormation, Kubernetes, and Dockerfile scanning, policy management, custom checks, compliance frameworks, and suppression management. Use when scanning IaC for security misconfigurations, evaluating compliance, managing custom policies, or reviewing scan results.

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Structured decision-making framework for technical proposals and trade-off analysis. When the user faces a choice between multiple approaches (architecture decisions, tool selection, refactoring strategies, migration paths), this skill produces a 1-3-1 format: one clear problem statement, three distinct options with pros/cons, and one concrete recommendation with definition of done and implementation plan. Use when the user asks for a "1-3-1", says "give me options", or needs help choosing between competing approaches.

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Native 4-bit Activations with Hadamard Transformation for 1-bit LLMs Published in arXiv , 2025 Abstract : Efficient deployment of 1-bit Large Language

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Artificial intelligence-driven transformative applications in disease ... — In cancer diagnostics, AI systems have achieved breakthrough performances

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Vollständige Dokumentation des OpenAmer Plugin-API-Systems. Hooks, Events, Lifecycle, manifest.json Format, Config-Integration und Plugin-Manager.

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Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates.

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Analyzes genetic variant effects on gene expression (RNA-seq), chromatin accessibility (DNASE), histone marks (ChIP), and transcription factors using the AlphaGenome API. Use when the user asks about non-coding variant effects, pathogenicity, clinical significance, disease associations, functional effects, gene expression changes, splicing disruption, or regulatory effects in promoters and enhancers. Also use for resolving biological terms to tissue/cell-type ontologies (UBERON/CL) or analyzing variants in chr:pos:ref>alt format.

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Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.

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AiZynthFinder retrosynthetic route planning (CASP) from AstraZeneca Molecular AI. Monte Carlo tree search guided by a template-based neural expansion policy recursively disconnects a target SMILES until precursors are found in a purchasable stock. Covers config.yml (v4 format), aizynthcli batch screening, the AiZynthFinder/AiZynthExpander Python API, one-step disconnections, custom stocks via smiles2stock, scorers, Retro*/breadth-first/DFPN search alternatives, and reading output.json.gz / trees.json. Use for synthesis route planning, synthesizability screening, and building-block/precursor search. For reaction barriers use neb-irc-activation-energy; for 2D reaction scheme drawing use rdkit-chemdraw-cdxml.

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Word (.docx) manipulation via MCP server. Use for reading, creating, editing, formatting Word documents including tables, footnotes, comments, images, headers, styles, and PDF conversion.

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Receive and act on code review feedback with technical rigor, not performative agreement or blind implementation

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Delegate routine work to subagents — boilerplate generation, data transformation, file analysis, documentation drafting. Use when splitting tasks into independent subtasks for parallel subagent execution.

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PowerPoint (.pptx) manipulation via MCP server. Use for creating slides, formatting presentations, managing placeholders, adding images, applying templates, or extracting text from .pptx files.

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Train or fine-tune language and vision models using TRL (Transformer Reinforcement Learning) or Unsloth with Hugging Face Jobs infrastructure. Covers SFT, DPO, GRPO and reward modeling training methods, plus GGUF conversion for local deployment. Includes guidance on the TRL Jobs package, UV scripts with PEP 723 format, dataset preparation and validation, hardware selection, cost estimation, Trackio monitoring, Hub authentication, model selection/leaderboards and model persistence. Use for tasks involving cloud GPU training, GGUF conversion, or when users mention training on Hugging Face Jobs without local GPU setup.

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Trains and fine-tunes vision models for object detection (D-FINE, RT-DETR v2, DETR, YOLOS), image classification (timm models — MobileNetV3, MobileViT, ResNet, ViT/DINOv3 — plus any Transformers classifier), and SAM/SAM2 segmentation using Hugging Face Transformers on Hugging Face Jobs cloud GPUs. Covers COCO-format dataset preparation, Albumentations augmentation, mAP/mAR evaluation, accuracy metrics, SAM segmentation with bbox/point prompts, DiceCE loss, hardware selection, cost estimation, Trackio monitoring, and Hub persistence. Use when users mention training object detection, image classification, SAM, SAM2, segmentation, image matting, DETR, D-FINE, RT-DETR, ViT, timm, MobileNet, ResNet, bounding box models, or fine-tuning vision models on Hugging Face Jobs.

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Excel (.xlsx) manipulation via MCP server. Use for creating workbooks, formatting cells, writing formulas, building charts, pivot tables, data analysis, or any task involving Excel spreadsheets.

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Use this skill whenever the user wants to create, read, edit, or manipulate Word documents (.docx files). Covers polished document output, tracked changes, comments, image updates, XML-level repairs, and safe conversion workflows.

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Use when the task involves reading, creating, or editing `.docx` documents, especially when formatting or layout fidelity matters; prefer `python-docx` plus the bundled `scripts/render_docx.py` for visual checks.

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Documentation quality standards and writing principles. Use when establishing formatting rules, reviewing doc quality metrics, creating writing guidelines, or enforcing consistent documentation style across a project.

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Use only when the user explicitly requests strict code-cell-only output for a Jupyter or undergraduate data-science task, or when an ITX2007 assignment requires that format. Do not activate for ordinary data analysis or explanation requests.

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Templates and structural patterns for API docs, feature docs, config guides, and REST endpoint documentation. Use when structuring docs, applying Markdown templates, or standardizing doc formats.

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。