「lean」の検索結果

Manage git worktrees across any repository with the `gwm` Rust binary (CLI + ratatui TUI). Use when the user asks to create / list / remove / bootstrap / switch / link worktrees, run a command across worktrees (`gwm exec`) or reclaim build artifacts (`gwm clean`), materialise a PR into a worktree (`gwm review`), drive a multi-repo workspace (`--workspace`), run the JSON daemon / statusline (`gwm daemon`, `gwm statusline`), list or pin AI-agent sessions per worktree (`gwm agents`, Claude Code / Codex / opencode / Mistral Vibe detection), seed config from a preset (`gwm init --preset`), diagnose with `gwm doctor`, drive tmux/zellij, or wire `gcd` via `gwm shell-init`. Also covers multi-forge (#419): GitHub via `gh` **or** GitLab via `glab`, the `forge` / `[forge_hosts]` keys, and `gwm trust add`. Triggers on `gwm`, `gwq`, `git worktree`, `.gwm.toml`, `forge`, `forge_hosts`, `glab`, `gwm trust add`, GitLab MR, `gwm create`, `gwm list`, `gwm exec`, `gwm clean`, `gwm review`, `gwm daemon`, `gwm statusline`, `gwm agents`, `gwm note`, `gwm bootstrap`, `gwm doctor`, `gwm switch`, `gwm tmux`, `gwm zellij`, `gwm link`, `gwm status`, `gwm shell-init`, `gcd`, `feat/#`, `fix/#`, GitHub issue/PR linking on a worktree.

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, manage, and cleanup git worktrees with Claude Code agents across all projects. USE THIS SKILL when user says "create worktree", "spin up worktrees", "new worktree for X", "worktree status", "cleanup worktrees", "sync worktrees", or wants parallel development branches. Also use when creating PRs from a worktree branch (to update registry with PR number). Handles worktree creation, dependency installation, validation, agent launching in Ghostty, and global registry management.

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。

Prepare a git repo before new work: review uncommitted changes, fix .gitignore, delete merged branches, end on clean main, or inspect one branch before deciding. Don't use for dead code, commit-and-push, releases, LICENSE files, or git how-tos.

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。

Suede-owned launch packaging and install verification. Use when finished software work needs a clean public package (README, docs page, install command, release note, GitHub Pages update, skill-pack release, MCP server, or launch/social copy) or when a release needs handoff notes, an install fails, a public user cannot add a skill, a raw-vs-blob URL returns HTML, or `@personal` or a local plugin alias leaks into public docs. Verifies the live URL and runs the exact install command from a clean temporary directory before anything is called live. NOT FOR: product, course, or artist campaign launches (use suede-campaign-in-a-box or suede-marketing-plan); writing announcement copy from scratch (use suede-copy); MCP tool-catalog QA (use suede-mcp-qa); landing-page conversion work (use suede-site-alchemy).

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 this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.

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。

Clean up raw interview transcripts while preserving meaning and speaker voice. Use after conducting interviews.

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。

Windows 11 system administration with PowerShell — system info reporting, hardware monitoring, package management (winget/scoop), disk cleanup, performance optimization, environment configuration, PowerShell profile setup with aliases and autocomplete, and Task Scheduler automation. Use when user asks to check system info, install tools on Windows, clean up disk space, set up PowerShell profile, or automate Windows tasks. Do NOT use for Linux administration, cross-platform scripting, or network infrastructure management.

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。

Automate the complete Git development workflow — create feature branches with conventional naming, atomic commits with conventional commit messages, interactive rebase, squash merges, PR body generation from commit history, branch cleanup, and git worktree patterns. Use when user asks to create a branch, commit changes, make a PR, rebase, squash, clean up branches, or follow a Git workflow. Do NOT use for CI/CD pipeline configuration (use ci-cd), code review (use code-review), or GitHub Actions workflows.

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。

Start a new prospect's intake, with or without their files in hand — a request naming a new prospect and attaching no documents is a normal starting point, because Step 1 searches the connected tools or asks the advisor to upload. Cleans and normalizes their account files (statements, exports, screenshots) into a consolidated view, then hands back a plain-English prospect summary, a detailed analyst handoff the full proposal gets built from, and a friendly "what to expect" memo, offered as a Gmail draft on approval. Does not produce the proposal, recommend an allocation, or quote fees. Triggers on "prospect intake", "/prospect-intake", "new prospect intake", "clean up [prospect]'s statements", "process [prospect]'s files", "what to expect note for [prospect]" — and on how an advisor raises a new prospect before any file exists: "I met with a potential client/customer", "[name] is interested in becoming a client", "I have a new prospect", "how should I proceed with [name]".

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。

Simplifies recently changed or explicitly scoped code while preserving observable behavior, error semantics, side effects, ordering, and public contracts. Use for readability cleanup, dead-code removal, reducing nesting, eliminating redundant wrappers, or making an implementation easier to maintain. Not for architecture redesign, new behavior, speculative cleanup, or a refactor without an adequate safety net.

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 this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .xltx, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.

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。

Generates RESTful API Controllers with proper routing, versioning, authorization, and MediatR integration. Follows REST conventions and Clean Architecture 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。

Generates CQRS Commands with Handlers, Validators, and Request DTOs following Clean Architecture patterns. Commands represent actions that modify state and return Result types for proper error handling.

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。

Implements the Result pattern for explicit error handling without exceptions. Provides Result, Result<T>, and Error types for clean, predictable control flow in domain-driven applications.

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。

Operations management and lean production techniques for turning inputs into outputs under variability. Covers the Toyota Production System, seven wastes, just-in-time, kanban, jidoka, single-minute die exchange, 5 Whys, value stream mapping, bottleneck theory, and the distinction between mass production and flexible production. Use when diagnosing operational waste, designing production flows, setting up quality systems, or comparing batch-and-queue to one-piece flow.

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 cleaning, transformation, reshaping, joins, missing data handling, and tidy data principles. Covers the full pipeline from raw ingestion to analysis-ready datasets -- type coercion, deduplication, outlier detection, normalization, melting/pivoting, regex extraction, and reproducible transformation chains. Use when preparing, cleaning, or transforming data for 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。

IMO Gold Medal level Lean4 theorem proving via Harmonic 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。

Runs structured Python cleanup and modernization — static analysis via prek/ruff, smell investigation to root cause, typed-boundary hardening by inventorying Any usage, and modernization within the project's requires-python lane. Use when refactoring Python code, removing dead code, hardening type boundaries, or running a modernization pass on a file or scope.

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。

Modern Git workflows, best practices, and commands. Use when the user asks about Git branch management (git switch vs checkout), file restoration (git restore), fixup commits, autosquash rebasing, git worktrees, rerere, force-with-lease, repository cleanup (git clean, stale branches, bloat analysis), history navigation (revision syntax, range notation, pickaxe search), recommended global git config, or GitButler and the but CLI.

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。

Clean Architecture patterns for Android and Kotlin Multiplatform projects — module structure, dependency rules, UseCases, Repositories, and data layer 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。

Designs conjoint and factorial-vignette experiments, covering attribute architecture and randomization restrictions, effective-N power, treatment realism, the choice among AMCE, marginal-mean, and AMIE estimands, forced-choice versus rating designs, and PAP tiers. Use when the user is planning a conjoint, drafting or critiquing an attribute table, asking how many respondents or tasks are needed, whether to report AMCEs or marginal means, or how to test interactions. Reviewing an existing design goes to conjoint-diagnostics, cleaning the export to conjoint-cleaning.

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。

Turns a raw Qualtrics conjoint export into an analysis-ready long-format dataset, covering export settings, identifying the implementation, package or manual wide-to-long reshaping, choice-profile alignment, ratings, reference categories, pilot exclusion, and subgroup merges. Use when the user has a conjoint CSV to clean, reshape, or debug, cannot align choices with profiles, or asks what the data must look like before AMCE estimation. Design goes to conjoint-design, validity review to conjoint-diagnostics.

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。

Turns a raw Qualtrics conjoint export into analysis-ready long-format data: implementation identification, reshaping, choice-profile alignment, reference categories, and pilot exclusion. Use when a conjoint CSV needs cleaning, reshaping, or debugging before AMCE estimation.

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 PR and automatically cleanup the worktree. Keeps local and remote branches intact.

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。