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Decompose an approved implementation plan into self-contained beads issues with zero guesswork. Use when breaking down a plan file into actionable beads 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。

Decompose an approved implementation plan into self-contained Linear issues with zero guesswork. Use when breaking down a plan into actionable Linear tasks via the 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。

Set reminders for events, tasks, and deadlines. Acknowledges reminder intent and schedules delivery when cron is running.

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 backend tasks to the right library skill. Detects intent and returns specific skill file paths to load.

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 API design/implementation tasks to the right library 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。

Route testing tasks to the right library skill. Covers unit, integration, e2e, coverage, and test quality.

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 frontend tasks to the right library skill. Detects React/Vue/CSS intent and returns specific skill file paths.

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。

Drive a real browser from the command line — open pages, snapshot the interactive elements as refs, click and fill by ref, read text, run JS, screenshot. Use when a task needs a live browser: checking a page renders, walking a login or checkout flow, scraping something that only exists after JavaScript runs, or reproducing a UI bug.

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 database tasks to the right library skill. Covers migrations, query optimization, ORM, transactions.

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 deployment tasks to the right library skill. Detects intent and returns specific platform skill file paths to load.

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。

Handle MindIE-SD documentation, governance, contributor workflow, commit or PR conventions, history cleanup, template changes, and version-policy updates with minimal context, fixed review steps, and deterministic output. Use this skill whenever the task touches docs/ 或文档站点内容与配置（Sphinx / Read the Docs / conf.py / index.md / 目录导航 / 首页）、中英文双语配套、治理文档、贡献流程说明、PR/MR 模板或标题正文规范、提交历史整理、版本策略与发布规则。即使用户只说「改个文档」「双语要同步」「commit message 怎么写」「PR 模板加一项」「把提交压一下」「rebase 冲突怎么理」而未提治理规范，也应触发。不负责通用工程实现与仓库默认工作流定义（后者以 AGENTS.md 为准）；Python 格式见 code-standards，Markdown 格式见 markdown-lint。

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。

Trains and applies base-resolution deep learning models on ChIP-seq / ChIP-nexus / CUT&RUN data. Uses BPNet (Avsec 2021 Nat Genet 53:354; soft motif syntax from ChIP-nexus), chromBPNet (Pampari A et al 2024 bioRxiv; bias-factorized base-resolution profiles), EnFormer (Avsec 2021 Nat Methods 18:1196; 196 kb input, ~100 kb effective receptive field), DeepSEA (Zhou 2015; multi-task CNN), and JASPAR 2026 deep-learning collection (1259 BPNet ChIP models). Performs in silico mutagenesis for variant-effect prediction, DeepLIFT/Grad attribution, and TF-MoDISco motif discovery from attribution scores. Use when predicting variant effects on TF binding, discovering soft motif syntax / cooperativity, integrating ChIP-seq with sequence-only predictions, or applying precomputed JASPAR Deep Learning models to new variants.

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。

Define database models with clear naming, appropriate data types, constraints, relationships, and validation at multiple layers. Use this skill when creating or modifying database model files, ORM classes, schema definitions, or data model relationships. Apply when working with model files (e.g., models.py, models/, ActiveRecord classes, Prisma schema, Sequelize models), defining table structures, setting up foreign keys and relationships, configuring cascade behaviors, implementing model validations, adding timestamps, or working with database constraints (NOT NULL, UNIQUE, foreign keys). Use for any task involving data integrity enforcement, relationship definitions, or model-level data validation.

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 and manage database migrations with reversible changes, proper naming conventions, and zero-downtime deployment strategies. Use this skill when creating database migration files, modifying schema, adding or removing tables/columns, managing indexes, or handling data migrations. Apply when working with migration files (e.g., db/migrate/, migrations/, alembic/, sequelize migrations), schema changes, database versioning, rollback implementations, or when you need to ensure backwards compatibility during deployments. Use for any task involving database structure changes, index creation, constraint modifications, or data transformation scripts.

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。

Track complex, multi-session work with dependency graphs using bd (beads) issue tracker. Use when work spans multiple sessions, has complex dependencies, or requires persistent context across compaction cycles. For simple single-session linear tasks, TodoWrite remains appropriate.

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。

Time-blind friendly planning, executive function support, and daily structure for ADHD brains. Specializes in realistic time estimation, dopamine-aware task design, and building systems that actually work for neurodivergent minds.

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。

This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible 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。

Browse the web for any task — research topics, read articles, interact with web apps, fill forms, take screenshots, extract data, and test web pages. Use whenever a browser would be useful, not just when the user explicitly asks.

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。

Autonomously improve a real artifact (code, training recipe, agent harness, data pipeline, prompt) against an objective and an evaluator, using Hypothesis Tree Refinement (HTR) from the Arbor paper. Use this whenever someone wants to iteratively optimize something over many experiments without overfitting — e.g. "get my model's eval score up", "improve this agent/harness", "tune this pipeline", "beat the baseline on this benchmark", "run a search over approaches and keep the best", "do an MLE-bench / Kaggle-style optimization", or any long-horizon "make this artifact better and don't just memorize the dev set" task. Trigger it even when the user doesn't say "Arbor" or "hypothesis tree" but describes repeated experiment-and-evaluate loops, branching exploration of competing ideas, or worries about a dev/test gap. Runs Claude itself as the coordinator with subagent executors in isolated git worktrees; for the standalone `arbor` CLI tool see references/arbor-upstream.md.

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。

Auto-invoked 7-phase workflow for complex-feature intent; fasttrack mode for pre-approved specs. NOT for explicit single tasks (mk:cook), green-field builds (mk:autobuild), or simple fixes (mk:fix).

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。

Coordinate staged or parallel jobs across coding-agent runtimes and subagents: routes by capability/risk, isolates writers in worktrees, arbitrates results. NOT for a single-agent task (mk:cook).

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。

Generate publish-grade SVG+PNG technical diagrams (architecture, data flow, sequence, ER, state-machine, etc.) in 8 styles. Writes to tasks/visuals/. Needs rsvg-convert for PNG; else SVG-only.

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。

Domain-aware complexity routing: scans the task for domain keywords, matches domain-complexity.csv, and returns complexity level, workflow intensity, and execution tier. Extends Phase 0 orchestration.

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 designing UI components, reviewing visual design, building design systems, or checking accessibility. Auto-activates on frontend design tasks and UI 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。