「arize」の検索結果

Use when about to claim work is complete, fixed, or passing, before committing or creating PRs - requires running verification commands and confirming output before making any success claims; evidence before assertions always

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。

作業開始時に使用。mainブランチでの作業禁止。Issue先行作成必須。

git logからCHANGELOGとリリースノートを自動生成する。リリース作業時に使用。

Use when verified implementation is ready for an integration decision or authorized 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。

ログ設計の妥当性チェック。一般的なログ基準と日本国内法的要件（電子帳簿保存法・個人情報保護法等）に基づき、ログ設計・実装を検証する。

PR作成時に使用。実装レポート（計画との対応、品質チェック結果、レビュー指摘対応）をPR descriptionに出力する。

Use when recurring process failures, obsolete rules, or an explicit user request call for harness improvement.

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。

機能・サービス・要件・前提条件などプロジェクトの知識をドキュメント化する。新規機能/サービスを作るとき、または既存機能を変更するときに必ず実行。新規ならドキュメントを作成、既存があれば更新する。

実装前に呼ぶ。High/Medium リスク変更のテストオラクル（期待値の根拠）とファルシフィケーション項目を定義する。

Use when continuing implementation from an existing plan

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。

DON'T USE THAT SKILL. IT'S JUST AN EXAMPLE. Summarize today's Gmail inbox by category with anonymized senders and subjects, then surface the top 3 emails to focus on next. Run only when the user types /email-summary.

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。

AI-powered presentation generation via the 2slides API — create slides from text, match a reference image style, summarize documents into decks, add AI voice narration, and export pages/audio. Use for any "make slides", "create a deck", or "slides from this document" 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。

Summarize existing QA criteria, cases, evidence, defects, limitations, authorization, and verdict without mutation.

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。

Enable, record, query, summarize, or verify the opt-in PWDEV Flow semantic audit trail. Use when the user asks what Flow actions occurred, wants audit integrity checked, or needs a portable JSONL record of workflow gates and artifacts.

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。

Inventory, archive, and summarize PWDEV Flow project history safely. Use when the user asks to find stale artifacts, archive completed work, clean the Flow workspace without deletion, or generate a changelog from verified history.

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。

Produces a compact KPI digest showing how key metrics changed over a period and what's driving the movement. Use this skill when someone asks for a performance summary, a weekly recap, a morning briefing, a KPI update, or any variation of "how did we do this week/month." Also trigger for requests like "give me a performance overview," "what moved in the last 7 days," "pull our KPI report," or "summarize our metrics."

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 a punchy sizzle reel from a video using Adobe Quick Cut. Use this skill whenever a user wants to cut, trim, or shorten a video into highlights — including phrases like "make a sizzle reel", "make a highlight reel", "quick cut this", "cut the best parts", "shorten this video", "make a highlight clip", "summarize this video visually", or any request to produce a shorter edited version of a video. Use this skill for Quick Cut requests before suggesting manual editing in Premiere. Requires the user to upload a video file.

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。

Produces a compact KPI digest showing how key metrics changed over a period and what's driving the movement. Use this skill when someone asks for a performance summary, a weekly recap, a morning briefing, a KPI update, or any variation of "how did we do this week/month." Also trigger for "give me a performance overview," "what moved in the last 7 days," "pull our AA KPI report," or "summarize our metrics."

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。

Summarize authored commits over a user-specified time period into a concise update

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 concise next-agent handoff summaries across sessions, tools, and coding agents. Load when the user says handoff, next agent should know, save context, summarize where we are, switching agents, before ending a meaningful session, or when the user asks to commit, push, commit and push, create a git commit, push to origin, or publish commits — commit/push requests MUST run this skill first to prepare handoff docs, then proceed with git operations.

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。

Inspect GitHub PR checks with gh, pull failing GitHub Actions logs, summarize failure context, then create a fix plan and implement after user approval. Use when a user asks to debug or fix failing PR CI/CD checks on GitHub Actions and wants a plan + code changes; for external checks (e.g., Buildkite), only report the details URL and mark them out of scope.

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Stores and operates on sparse expression matrices for single-cell and large bulk RNA-seq, covering dgCMatrix/dgRMatrix/dgTMatrix when-each-is-fast, the dgCMatrix (CSC, R) <-> CSR (Python) implicit transpose, AnnData (cells-rows) <-> SingleCellExperiment (cells-cols) orientation flip, HDF5/h5ad vs Zarr cloud-native shift, HDF5SummarizedExperiment + DelayedArray for out-of-memory bulk, scanpy backed mode for large h5ad, the ~10-15% density crossover where dense beats sparse, 10X format proliferation (MTX vs CellRanger H5 vs h5ad), the dense-conversion memory blow-up, and Dask + Zarr for consortium-scale matrices. Use when choosing sparse format, working with single-cell-sized matrices, importing/exporting 10X, debugging R/Python interop transposes, processing matrices too large for RAM, or building cloud-native pipelines.

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Reads, inspects, and writes Flow Cytometry Standard (FCS) files from conventional, spectral, and mass cytometry (CyTOF), and parses FlowJo/Cytobank/Diva workspaces. Covers FCS 2.0/3.0/3.1/3.2 internals ($PnE linear-vs-log, $DATATYPE, $SPILLOVER vs SPILL vs $COMP, $TIMESTEP), channel/parameter metadata, the silent linearize/truncate defaults, and R (flowCore, flowWorkspace, CytoML) plus Python (FlowKit, readfcs) readers. Use when loading flow or mass cytometry data, mapping detector channels to antibodies, extracting the event matrix, choosing a reader, or bridging FCS to the scanpy/AnnData ecosystem 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。

Segments the genome into chromatin states from combinatorial histone modification and chromatin factor ChIP-seq data. Uses ChromHMM (multivariate HMM on binarized signal, v1.27), Segway (Dynamic Bayesian Network on continuous signal), EpiSegMix (flexible-distribution HMM with duration modeling, 2024), EpiLogos (multi-biosample visualization), IDEAS (cell-type-aware joint), and full-stack ChromHMM (Vu Ernst 2022) for cross-cell-type segmentations. Handles state-count selection (15 vs 18 vs 25 states), binarization choice, OverlapEnrichment / NeighborhoodEnrichment downstream analysis, and cross-biosample integration. Use when learning chromatin states from a histone mark panel, characterizing learned states by genomic feature enrichment, or comparing chromatin landscapes across cell types.

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。