「analysis」の検索結果

Use when working with Dynamodb — amazon DynamoDB table analysis, capacity mode evaluation, GSI/LSI usage, item access patterns, and cost optimization.

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 working with Aws Eks — aWS EKS cluster management, nodegroup status, addon management, IRSA configuration, and cluster health analysis. Covers Kubernetes version tracking, nodegroup scaling, addon compatibility, IAM role mapping, and control plane logging.

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。

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.

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 comparable-company valuation workbooks in Excel.

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 for log analysis, error tracking, alerts, and dashboard.

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 for AST/dep graph/complexity analysis of Python 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。

Molecular docking with AutoDock Vina (Python API). Receptor/ligand prep (Meeko + RDKit), grid box, docking, pose and binding energy analysis, and batch virtual screening.

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。

Annotated matrices for single-cell genomics. Stores X with obs/var metadata, layers, embeddings (obsm/varm), graphs (obsp/varp), uns. Use for .h5ad/.zarr I/O, concatenation, scverse integration. For analysis use scanpy; for probabilistic models use scvi-tools.

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。

Plan, execute, and document validation, verification, and transfer of analytical procedures under the governing framework - ICH Q2(R2) and Q14, USP <1220>/<1225>/<1226>, ICH M10 bioanalytical, CLSI EP, or ISO/IEC 17025. Use for HPLC, LC-MS/MS, GC, CE, ICP-MS, dissolution, qNMR, qPCR, NIR, and ligand binding or cell-based assays whenever the question is whether a procedure is fit for its intended purpose. Triggers include "method validation", "analytical method validation", "AMV", "validation protocol", "acceptance criteria", "linearity", "reportable range", "accuracy and precision", "repeatability", "intermediate precision", "recovery", "LOD", "LOQ", "detection limit", "quantitation limit", "specificity", "robustness", "method transfer", "method comparison", "Deming", "Passing-Bablok", "Bland-Altman", "equivalence testing", "OOS investigation", "ICH Q2", "Q2(R2)", "Q14", "USP 1225", "ICH M10", "incurred sample reanalysis", "ISR", "CLSI EP", and any request to show that an assay works.

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。

Understand anti-reversing, obfuscation, and protection techniques encountered during software analysis. Use this skill when analyzing malware evasion techniques, when implementing anti-debugging protections for CTF challenges, when reverse engineering packed binaries, or when building security research tools that need to detect virtualized environments.

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。

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.

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。

Core Python library for astronomy/astrophysics: units with dimensional analysis, celestial coordinate transforms (ICRS/Galactic/AltAz/FK5), FITS I/O, tables (FITS/HDF5/VOTable/CSV), cosmology (Planck18, distance/age), precise time (UTC/TAI/TT/TDB, Julian, barycentric), WCS pixel-world mapping, model fitting. For general tables use pandas/polars; for radio interferometry use CASA.

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。

Retrieve and analyze AlphaFold predicted structures for a protein. Use when the user provides a specific UniProt Accession ID and wants structural confidence metrics (pLDDT), domain boundary analysis, or disorder assessment. Do not use if the user only has a protein name, gene name, or amino acid sequence — ask for a UniProt ID first.

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。

Core Python library for astronomy and astrophysics workflows that need Astropy APIs, including units/quantities, coordinates, FITS I/O, tables, time systems, WCS, and cosmology. Use when implementing or debugging astronomical data analysis code with Astropy.

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 CSV datasets for schema, quality, modeling readiness, and feature 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。

Systematic strategic planning framework for philosophy and interdisciplinary academic papers targeting preprint platforms (PhilArchive, arXiv, PhilSci-Archive). Use when users want to: (1) plan a paper on a specific topic, (2) identify research gaps and assess originality, (3) develop optimized paper outlines, (4) prepare for preprint submission, or (5) understand platform requirements and writing standards. Triggered by phrases like 'plan a paper on,' 'help me design a paper about,' 'identify research gaps in,' 'is this idea original,' or when users need structured research planning. The skill guides through three phases: Platform Analysis (identifying target venue and studying sample papers), Theoretical Framework (AI-driven literature search and gap identification), and Outline Optimization (structured design with reviewer-perspective self-assessment). Each phase includes quality evaluation standards and validation checkpoints.

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。

Run Tavily's multi-source research workflow for comparisons, market analysis, literature-oriented exploration, or detailed cited reports. Use only when bounded search and extraction are insufficient.

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 git repositories to build a security ownership topology (people-to-file), compute bus factor and sensitive-code ownership, and export CSV/JSON for graph databases and visualization. Trigger only when the user explicitly wants a security-oriented ownership or bus-factor analysis grounded in git history (for example: orphaned sensitive code, security maintainers, CODEOWNERS reality checks for risk, sensitive hotspots, or ownership clusters). Do not trigger for general maintainer lists or non-security ownership questions.

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。

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

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。

Review final-assignment materials for requirements, citations, AI-use disclosure, and data-analysis completeness.

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。

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.

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。

Evaluate and improve AI-generated output with explicit rubrics, reflection loops, and stop conditions. Use when building self-critique workflows, evaluator-optimizer pipelines, or acceptance gates for code, docs, analysis, or plans.

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 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.

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-driven growth v3 — experimentation, metrics, dashboards, correlation 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。