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cccskills

「batch」の検索結果

1,277 件 ・ 関連度順

概要と使いどころ

Converts heterogeneous documents and selected URIs to Markdown with Microsoft MarkItDown for text analysis, search, and LLM/RAG ingestion. Covers safe local conversion, streams, Office/PDF/data formats, batch workflows, plugins, vision OCR, Azure extraction, and the official MCP server.

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。

K-Dense-AI/scientific-agent-skills4.9万2026年10月12日 更新

modal

無料

Modal is a serverless cloud platform for running Python on demand, including on-demand GPUs. Use when deploying or serving AI/ML models, running GPU-accelerated workloads (training, fine-tuning, inference), serving web endpoints, scheduling batch jobs, or scaling Python code to cloud containers with the Modal SDK.

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。

K-Dense-AI/scientific-agent-skills4.9万2026年10月12日 更新

Searches scientific and technical web content with Exa and extracts page or PDF text from URLs in batches. Supports scholarly discovery with the publication category and academic domain filters. Applies to requests to search the web, look up current research, fetch a page, or extract an article using Exa.

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。

K-Dense-AI/scientific-agent-skills4.9万2026年10月12日 更新

Runs reproducible CellProfiler microscopy pipelines for nuclear segmentation, cell counts, and per-object fluorescence measurements. Supports image/channel manifests, headless batch execution, segmentation overlays, and measurement QC for 2D fluorescence assays.

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。

K-Dense-AI/scientific-agent-skills4.9万2026年10月12日 更新

diffdock

無料

Predicts protein-small-molecule binding poses with DiffDock and DiffDock-L from PDB or sequence plus SMILES/SDF/MOL2. Covers batch docking, pose triage, confidence interpretation, and validation. Use for molecular docking and virtual-screening pose generation, not binding-affinity prediction.

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。

K-Dense-AI/scientific-agent-skills4.9万2026年10月12日 更新

biopython

無料

Provides Biopython workflows for sequence manipulation, file parsing (FASTA/GenBank/PDB), phylogenetics, and programmatic NCBI/PubMed access (Bio.Entrez). Supports batch processing, custom molecular-biology pipelines, BLAST automation, structure analysis, and motif analysis.

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。

K-Dense-AI/scientific-agent-skills4.9万2026年10月12日 更新

Designs experiments and studies BEFORE data is collected — choosing a design, randomizing, blocking, and laying out treatment combinations so results are interpretable. Use whenever someone is planning a study, asks how to assign subjects/samples to groups, mentions randomization, blocking, stratification, controls, factorial or fractional-factorial designs, design of experiments (DOE), screening many factors, response-surface optimization, crossover or repeated-measures or split-plot designs, cluster/group randomization, Latin squares, plate layouts, batch/run-order effects, replication vs. pseudoreplication, or sequential/adaptive/group-sequential designs. Trigger even for informal phrasings like "how should I set up this experiment", "how do I avoid confounding", "what's the best way to test these 6 factors", or "assign these mice to conditions". For computing the sample size or power once the design is chosen, use statistical-power; for analyzing data already collected, use statistical-analysis.

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。

K-Dense-AI/scientific-agent-skills4.9万2026年10月12日 更新

Azure AI Transcription SDK for Python. Use for real-time and batch speech-to-text transcription with timestamps and diarization.

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。

sickn33/agentic-awesome-skills4.8万2026年10月14日 更新

Azure AI Document Translation SDK for batch translation of documents with format preservation. Use for translating Word, PDF, Excel, PowerPoint, and other document formats at scale.

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。

sickn33/agentic-awesome-skills4.8万2026年10月14日 更新

Build production Apache Airflow DAGs with best practices for operators, sensors, testing, and deployment. Use when creating data pipelines, orchestrating workflows, or scheduling batch jobs.

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。

sickn33/agentic-awesome-skills4.8万2026年10月14日 更新

Orchestrate AI/ML pipelines for data ingestion, model training, batch inference, and RAG indexing using Prefect, Airflow, or Dagster.

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。

sickn33/agentic-awesome-skills4.8万2026年10月14日 更新

Replace the manual commit-by-commit classification step in `breeze release-management prepare-provider-documentation` with AI-driven classification. For each provider with pending changes, analyze every PR (batched into one sub-agent per provider, not one per PR), pay special attention to potentially breaking changes by inspecting the actual diff, scope multi-provider PRs to the current provider's slice, ask the release manager when uncertain, and apply version bumps + changelog entries. Use during the regular provider release cycle as an alternative to the interactive breeze prompts.

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。

apache/airflow4.7万2026年10月13日 更新

Manage Sub2API admin APIs for accounts, redeem codes, groups, proxies, error passthrough rules, TLS fingerprint profiles, imports, exports, batch updates, and raw administrator API calls. Use when the user mentions Sub2API, admin API keys, account management, redeem code management, recharge codes, invitation codes, bulk account import/export, keeping or deleting accounts, refreshing accounts, clearing errors, CRS sync, or managing Sub2API backend settings through the admin API.

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。

Wei-Shaw/sub2api4.4万2026年10月13日 更新

Python error handling patterns including input validation, exception hierarchies, and partial failure handling. Use when implementing validation logic, designing exception strategies, handling batch processing failures, or building robust APIs.

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。

wshobson/agents4.1万2026年10月12日 更新

Build production Apache Airflow DAGs with best practices for operators, sensors, testing, and deployment. Use when creating data pipelines, orchestrating workflows, or scheduling batch jobs.

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。

wshobson/agents4.1万2026年10月12日 更新

Integrate Microsoft Graph SDK into any project — .NET, TypeScript/JavaScript, or Python. Covers auth patterns (client credentials, OBO, managed identity), SDK setup, calling Graph APIs, batching, delta queries, change notifications, throttling, and permission scopes. Use when accessing Microsoft 365 data (users, mail, calendar, Teams, files, SharePoint) from any application 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。

github/awesome-copilot4万2026年10月14日 更新

Converts Excel (.xlsx) workbooks into Markdown so their contents can be accurately analyzed, summarized, searched, or extracted from. Use this skill whenever the user shares, references, or asks about a .xlsx file — even if they don't say "convert" or "markdown" explicitly. This includes requests to "read", "summarize", "review", "extract data from", "compare", "chart", or "analyze" a spreadsheet, workbook, budget, data export, or tracker. Always run the bundled conversion script to produce Markdown first; do not attempt to parse .xlsx content directly or write ad-hoc extraction code. Also use this skill for batch requests involving a whole folder of Excel workbooks. IMPORTANT: When the user references a folder or set of documents containing multiple file types (.pdf, .docx, .xlsx), invoke ALL three sibling skills — convert-pdf-to-md, convert-word-to-md, and convert-excel-to-md — so no file type is silently skipped.

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。

github/awesome-copilot4万2026年10月14日 更新

Converts PDF (.pdf) documents into Markdown so their contents can be accurately analyzed, summarized, searched, or extracted from. Use this skill whenever the user shares, references, or asks about a .pdf file — even if they don't say "convert" or "markdown" explicitly. This includes requests to "read", "summarize", "review", "extract data from", "compare", or "analyze" a PDF report, paper, invoice, form, contract, or scanned document. Always run the bundled conversion script to produce Markdown first; do not attempt to parse PDF content directly or write ad-hoc extraction code. Also use this skill for batch requests involving a whole folder of PDF documents. IMPORTANT: When the user references a folder or set of documents containing multiple file types (.pdf, .docx, .xlsx), invoke ALL three sibling skills — convert-pdf-to-md, convert-word-to-md, and convert-excel-to-md — so no file type is silently skipped.

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。

github/awesome-copilot4万2026年10月14日 更新

Converts Word (.docx) documents into Markdown so their contents can be accurately analyzed, summarized, searched, or extracted from. Use this skill whenever the user shares, references, or asks about a .docx file — even if they don't say "convert" or "markdown" explicitly. This includes requests to "read", "summarize", "review", "extract data from", "compare", or "analyze" a Word document, resume, report, contract, or proposal. Always run the bundled conversion script to produce Markdown first; do not attempt to parse .docx content directly or write ad-hoc conversion code. Also use this skill for batch requests involving a whole folder of Word documents. IMPORTANT: When the user references a folder or set of documents containing multiple file types (.pdf, .docx, .xlsx), invoke ALL three sibling skills — convert-pdf-to-md, convert-word-to-md, and convert-excel-to-md — so no file type is silently skipped.

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。

github/awesome-copilot4万2026年10月14日 更新

intent

無料

Shipyard's internal requirements intake for non-engineer contributors (support/ops) — turn a pasted chat log or verbal problem report into a five-section intent.md through numbered batch questioning with a completion gate, walk it through tracker review with harbor's four records, and hand the accepted intent to /launch as its mission brief. Produces decisions, not 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。

Yeachan-Heo/oh-my-claudecode4万2026年10月13日 更新

Write, calibrate, and debug the prefill-vs-decode logprob (KL) consistency tests in sglang -- the two independent conditions a zero requires (every operator batch-invariant, and the two paths computing the same function), which helper separates them, how to pick a threshold once they hold, and how to localize a divergence to a single operator. Use when adding a KL test to a model, picking or defending a kl_div threshold, or investigating a KL number that is too high.

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。

sgl-project/sglang3.7万2026年10月14日 更新

Trigger the bot-cherry-pick workflow for a batch of merged PRs onto a release branch and monitor each run to completion. Use when an SGLang release manager asks to cherry-pick a list of PRs to a release branch.

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。

sgl-project/sglang3.7万2026年10月14日 更新

Use when the user wants to run a diffusers pipeline from a terminal (one-off generation, batch jobs, smoke-testing a new model), run on HF Sandbox hardware via `--remote`, introspect a pipeline's input schema before calling it, or attach a LoRA at inference time. Prefer this over writing ad-hoc Python scripts for generation tasks.

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。

huggingface/diffusers3.5万2026年10月13日 更新

Detect AI-generated deepfake audio used in voice phishing (vishing) by extracting spectral features (MFCC, spectral centroid, spectral contrast, zero-crossing rate) and classifying samples with machine learning models, supporting batch audio analysis, confidence scoring, and forensic reporting. Use for deepfake voice detection, vishing investigations, AI-generated speech analysis, voice cloning detection, or audio authenticity verification.

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。

mukul975/Anthropic-Cybersecurity-Skills3.4万2026年8月31日 更新