「lean」の検索結果

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。

Deploy open models or custom weights from Model Garden to Agent Platform endpoints, check the status of an in-progress deployment operation, or clean up resources by undeploying models and deleting endpoints. Use when asked to actively deploy a model, list the Model Garden CATALOG of available models, check if a specific model is deployable (`gcloud ai model-garden models list-deployment-config`), query deployment cost, troubleshoot deployment errors (like quota limits), or undeploy/clean up endpoints. Also use when copying and deploying a 1P Tuned Model. Don't use for pure listing/discovery questions of the form "is X deployed?", "list my endpoints", or "which regions have models running?" — for those use `agent-platform-endpoint-management`. Don't use for public Vertex AI deployments (use the `vertex-deploy` skill) or for running model evaluations (use the `agent-platform-eval-flywheel` 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。

Land a ready branch - push, PR, pinned CI watch, squash-merge, issue verification, cleanup. Use for every PR landing; encodes the run-ID pinning and cleanup discipline.

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。

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。

Universal platform artifact cleaner: Replit, StackBlitz, CodeSandbox, Glitch

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。

Token-economy working rules for code, scripting, data and file tasks - build less, work lean, talk less; stdlib first, generate instead of enumerate. Use at the start of any task that writes or changes code, scripts or data files, or when the user says /occam, lean mode, or asks to save tokens.

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。

Apply these opinionated .NET 8 architecture conventions whenever structuring or reviewing a backend service: clean architecture layering and which direction dependencies point, when CQRS with MediatR is worth it, cross-cutting concerns as pipeline behaviours, minimal APIs grouped by feature, keeping DbContext in Infrastructure, health checks and structured logging, WebApplicationFactory integration tests, and when AOT pays off.

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。

Implement proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design. Use this skill when designing clean architecture for a new microservice, when refactoring a monolith to use bounded contexts, when implementing hexagonal or onion architecture patterns, or when debugging dependency cycles between application layers.

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。

Commercial and residential cleaning business operations agent. Covers pricing, bidding, staffing, supply costs, insurance, OSHA compliance, quality control, and growth from solo operator to multi-c...

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。

Intelligently organize files across your computer by understanding context, detecting duplicates, suggesting folder structures, and automating cleanup. Maintain a clean digital workspace without manual effort.

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 and reorganize markdown in enriched Jupyter notebooks. Arguments: [target] [--dry-run] [--aggressive] [--hierarchy-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。

ALWAYS invoke this skill before writing, editing, generating, or refactoring ANY code. Do not write or modify code directly without first loading and following these Clean Code guidelines. Use when writing new functions/classes, refactoring existing code, reviewing code, fixing bugs, or any task that produces code output.

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。

A gate before git push / deploy — assembled from your own tools (secret-grep + slop-scan + code-review + build/compile + optional worktree isolation), so AI junk (slop / bugs / secrets / uncompiled code) never reaches a remote or a production server. Turns "I hope it's clean" into a verifiable criterion. Branches: web/OSS (git push/PR) vs deploy-to-server service. Triggers — "check before push", "clean push", "gate before push", "finalize before commit", "run before deploy".

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。

Drafts Brownfields Agreements for contaminated-property transactions under CERCLA, EPA brownfields programs, and state voluntary cleanup programs. Structures BFPP liability protections, All Appropriate Inquiries documentation, remediation obligations, institutional controls, cost allocation, and long-term stewardship covenants. Use when drafting brownfields purchase agreements, prospective purchaser agreements, voluntary cleanup MOAs, or environmental covenant frameworks.

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。

Post-implementation simplification pass. Reduces complexity without changing behavior. Use after Phase 3 (Build GREEN) and before Phase 4 (Review). Catches dead code, unnecessary abstractions, over-engineering, and redundant patterns. Triggers on "simplify", "clean up", "reduce complexity", "too complex". NOT for style/convention enforcement (see mk:clean-code); NOT for reviewing diffs or PRs (see mk:review).

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。

Enforces KISS/DRY/YAGNI during authoring and ad-hoc quality reviews. Pragmatic standards: concise, direct, no unnecessary comments. NOT for post-hoc diff/PR review (see mk:review); NOT for behavior-preserving simplification passes (see mk:simplify).

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。

Take a chosen visual to finished, production-ready state. Runs cleanup + refinement passes (fix artifacts, balance composition, color-grade, sharpen text, conform to spec/aspect) using image edit/regenerate. Use when the user says "polish this", "finalize", "clean up the image", "production-ready", "fix the artifacts", or has a selected visual that needs finishing. Final stage of the Creative Production set.

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。

Corrects the gene-independent copy-number artifact in CRISPR-Cas9 screens (Aguirre 2016 / Munoz 2016 Cancer Discov) where amplified loci appear essential from DNA-damage burden of simultaneous cuts. Covers the gene-independent DNA-damage / G2-arrest mechanism, CRISPRcleanR (Iorio 2018) unsupervised pre-hoc correction, CERES (Meyers 2017) joint CN + gene-effect model, Chronos (Dempster 2021) DepMap-standard population-dynamics + CN model with lowest residual bias, the decision tree by data availability, the Spearman LFC-vs-CN diagnostic, focal-amplification examples (ERBB2 in HER2+, MYC in colorectal, FGFR1 in head and neck), and CRISPRi/a alternatives that bypass the artifact. Use when screening cancer cell lines, diagnosing essentiality at amplified loci, choosing CRISPRcleanR / CERES / Chronos, deciding whether CN correction is needed before MAGeCK / BAGEL2 / drugZ, or switching from Cas9 to CRISPRi.

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。

Workflow Phase 7 — Mechanical cleanup pass over the branch diff, followed by a `code-structure` review pass and a `verify` re-stamp. Shadows the global `simplify` skill at project scope; the cleanup pass is performed inline rather than via Skill self-call.

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。

Automated cleanup of unused AWS resources to reduce costs

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 digital electronics covering Boolean algebra, combinational and sequential logic, FPGA design, HDL programming, timing analysis, and digital system design.

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 discrete mathematics knowledge. Use when working with logic, set theory, combinatorics, graph theory, relations, functions, induction, recursion, boolean algebra, or discrete probability. Also use when the user mentions 'combinatorics', 'permutations', 'combinations', 'pigeonhole principle', 'inclusion-exclusion', 'generating functions', 'recurrence relations', 'graph theory', 'trees', 'logic', 'propositional calculus', or 'boolean algebra'.

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。

Strip designs to their essence by removing unnecessary complexity. Great design is simple, powerful, and clean. Use when the user asks to simplify, declutter, reduce noise, remove elements, or make a UI cleaner and more focused.

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。