「review」の検索結果

Scores backlog items with RICE/WSJF/Kano and files GitHub issues for top candidates. Use when triaging a roadmap or prioritizing features for a sprint.

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。

Searches and navigates stored knowledge in memory palaces. Use when looking for previously stored information or cross-referencing concepts across palaces.

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 validation and evidence before claiming work complete. Use before declaring implementation done, creating a PR, or submitting deliverables for 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。

Makes agent reasoning visible, surfaces tradeoffs, and fades help so humans build judgment. Use when reviewing or learning from agent-written 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。

Inverts burden of proof for code additions. Use when reviewing PRs, planning refactors, or running unbloat to challenge every addition's necessity.

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。

Convenes a multi-LLM expert panel to pressure-test hard-to-reverse decisions. Use when reversibility score is low and adversarial review is warranted.

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 a project skill library in .claude/skills/ via discovery, parallel authoring, and review. Use when packaging tribal knowledge. Do not use for one 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。

Applies KISS, YAGNI, and SOLID principles for clean code with reduced complexity. Use when refactoring or reviewing code for over-engineering.

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 Claude skill quality through auditing. Use when reviewing or auditing skills.

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。

Classify, gate, and review changes. Use when landing a PR, releasing, or amending rules. Do not use for failure triage; use night-market-debugging-playbook.

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 the GeoParquet specification and bundled inspection helpers to author, validate, distribute, or safely review geospatial Parquet data, including GeoParquet 2.0 vector metadata, external writer choices, and the alpha Parquet Raster proposal.

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 you need to design DataDesigner configs, run preview/create/validate workflows, inspect the CLI or agent context, work with plugins or MCP tools, or adapt documented recipes and integrations for synthetic dataset generation.

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 ARIS, the Auto Research in Sleep skill-based research harness, for setup, workflow routing, reviewer backend integration, state recovery, experiment operations, and repository maintenance.

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 search/review to subagents; compressed returns.

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。

Write less code and say less about it. Applies YAGNI and stdlib/native-first so the agent writes the minimum code that needs to exist, and responds tersely — stripping filler, hedging, and pleasantries while keeping code, identifiers, and technical terms exact. Use whenever writing, modifying, refactoring, reviewing, or explaining code, or any response where output volume drives token cost — even if the user never says "minimal" or "concise". Especially in agentic coding, where the volume of generated code and prose runs up the bill.

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 search- and review-heavy work to Honey's read-only subagents so large reads return compressed instead of bloating context.

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。

Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, passive voice, negative parallelisms, and filler phrases.

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。

Refactor and review SwiftUI view files for consistent structure, dependency injection, and Observation usage. Use when asked to clean up a SwiftUI view’s layout/ordering, handle view models safely (non-optional when possible), or standardize how dependencies and @Observable state are initialized and passed.

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。

Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.

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 you have an existing pipeline DOT file that needs review, fixing, or validation. Use when validation produces warnings or errors, when a DOT file was hand-written or generated by another tool, or when you want to verify a pipeline covers 100% of a spec before running it.

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。

Design, generate, review, and revise editable PowerPoint presentations through a rigorous brief-to-PNG workflow using the public pptx-designer Python library.

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 Burp Suite over its MCP server as an AI triage + attack layer - review proxy history for signals, replay via Repeater/send, OOB-gate blind bugs with Collaborator, fuzz via Intruder (RoE-safe), then hand off to the matching vuln-class hunt. Wiki-first, FIND schema 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。

单独运行质量审查, 不走完整开发流程。

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。

Production QA gate for Blender assets using viewport screenshots, validation checklists, naming audits, and ship/no-ship verdicts via MCP.

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。