データ分析、機械学習、LLMアプリ、プロンプト設計（8,843 件）
概要と使いどころ
Isolate the root cause of ML performance drops, inconsistent evaluations, prediction errors, and training-serving mismatches across data, labels, splits, pipelines, models, metrics, and runtime behavior. Use when investigating a reproducible failure or regression, not routine model selection or general performance validation.
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Orchestrate an end-to-end data analysis or machine learning project from decision framing through reproducible handoff. Use when a request spans multiple lifecycle stages or an ambiguous modeling request must become a decision-ready result; use narrower audit or experiment-design skills for isolated reviews.
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。
Route data analysis and machine learning work to the right skill in this suite. Use when starting any analysis, modeling, validation, or reproducibility task and the matching specialized skill is not yet clear; not needed when one specific skill already clearly applies.
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 a prompt to Claude via `claude -p`. Use when the user wants to offload a task to Claude from another agent (Codex, Cursor, another Claude session), get a second opinion, or run a parallel implementation. Default model is opus.
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。
上线前 PR 审查。分析当前分支与基础分支的 diff，检查 SQL 安全、竞态条件、 LLM 信任边界、枚举完整性等测试捕获不到的结构性问题。发现问题直接修复。 触发方式：用户说"review"、"审查代码"、"上线前检查"、"forge-review"，或 forge-dev --full 调度。 与内置 code-review/verify 的分工：forge 工作流内的上线前结构性审查用本 skill；用户点名 /code-review 或 /verify 时用对应内置 skill。
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。
Learns a user's personal writing and speaking style through interactive writing prompts, then generates a reusable voice profile. Use when the user says "learn my writing style," "write like me," "capture my voice," "voice calibration," "mimic my tone," "my writing style," or wants AI to match their personal communication style. Also activates when a .voice-profile.md file exists and the user asks you to write something in their voice.
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。
Guides AI agents through Senzing entity resolution workflows using the Senzing MCP server. Covers data mapping to Senzing format, SDK code generation (Python, Java, C#, Rust, TypeScript/Node.js), documentation search, error troubleshooting, sample data access, reporting and visualization, SDK setup guides, and V3-to-V4 migration. Use when working with entity resolution, record matching, record linkage, deduplication, Senzing SDK integration, data mapping for Senzing ingestion, or troubleshooting Senzing error codes. Also use when the user mentions matching records across data sources, finding duplicate entities, identity resolution, master data management, or needs to resolve who is who across datasets.
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。
Automatically format code files after every edit using Prettier and ESLint. Active in the background whenever Claude edits a file. Formatting is silent — no prompts, no output unless a formatter fails. Use when you want consistent formatting enforced automatically during a coding session.
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。
Re-run the analysis pipeline on all runs matching an RQ, reaggregate metrics, and propose findings updates against the fresh data. Trigger when the user says "reanalyze RQ-N", "reanalyse RQ-N", "Runs neu analysieren", or wants to refresh metrics/findings after a pipeline change (analyze-run.sh fix, adapter added, ESLint config).
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。
Talk to your Garmin data — ask questions about your activities, training load, VO2 Max, heart rate zones.
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。
Query weather data and forecasts for farm fields via the Agronomy module.
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。
Manage DAKboard screens, devices, and push custom display data.
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。
Query and manage GPS travel data from Geomanic — your privacy-first GPS tracking platform.
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。
Query ecobee thermostat data via Beestat API including temperature.
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Track Air France flights using the Air France–KLM Open Data 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。
Expert-level materials informatics covering materials databases, machine learning for property prediction, high-throughput computation, and data-driven materials discovery.
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。
Fetch aviation weather data (METAR, TAF, PIREPs)
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 Arccos Golf performance data including club distances, strokes gained metrics, scoring patterns.
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-level data structures covering arrays, linked lists, trees, heaps, hash tables, graphs, and advanced structures like segment trees, tries, and union-find.
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-level computational biology covering molecular dynamics simulation, protein structure prediction, systems biology, network analysis, and machine learning in biology.
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-level physical chemistry knowledge. Use when working with thermodynamics, chemical kinetics, quantum chemistry, statistical mechanics, spectroscopy, electrochemistry, or surface chemistry. Also use when the user mentions 'Gibbs energy', 'equilibrium constant', 'reaction kinetics', 'rate law', 'activation energy', 'Arrhenius', 'partition function', 'Schrodinger equation', 'molecular orbital', 'electrochemistry', 'Nernst equation', or 'surface adsorption'.
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-level statistics knowledge. Use when working with probability distributions, hypothesis testing, regression, Bayesian statistics, statistical inference, experimental design, ANOVA, or statistical modeling. Also use when the user mentions 'p-value', 'confidence interval', 'hypothesis test', 'regression', 'ANOVA', 'chi-square', 't-test', 'Bayesian', 'maximum likelihood', 'statistical significance', 'correlation', 'normal distribution', or 'sampling distribution'.
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-level bioinformatics covering sequence analysis, structural bioinformatics, database searching, phylogenetic analysis, NGS data processing, single-cell analysis, and machine learning in biology.
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-level linear algebra knowledge. Use when working with vectors, matrices, determinants, eigenvalues, linear transformations, vector spaces, inner products, decompositions, or applications in machine learning and physics. Also use when the user mentions 'matrix', 'determinant', 'eigenvalue', 'eigenvector', 'linear transformation', 'vector space', 'basis', 'orthogonality', 'SVD', 'PCA', 'least squares', 'null space', or 'rank'.
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。