727 件 ・ 関連度順
概要と使いどころ
Systematic bug sweep with a codebase-scaled target value, doubling escalation, area tracking, and final verification. Use on /bugsweep or whenever the user requests a systematic bug pass.
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。
Systematic 6-phase debugging protocol. Structured approach to bugs with quick checks, isolated testing, 20-minute rule, and bug report template.
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。
8-phase development cycle: Feature requests, current state, functional planning, frontend, backend planning, backend code, tests, use cases. Iterative framework for systematic software development.
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。
Systematic writing framework for philosophy and interdisciplinary academic papers from optimized outline to submission-ready manuscript. Use when users want to: (1) write a paper from a detailed outline, (2) ensure quality control during writing, (3) maintain consistency across chapters, (4) prepare a submission-ready manuscript, or (5) systematically execute a planned paper. Triggered by phrases like 'write the paper from this outline,' 'compose the full manuscript,' 'execute the outline,' or when users have completed strategic planning (academic-paper-strategist skill) and are ready to write. Takes optimized outline as input; outputs complete manuscript with iterative quality checks.
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。
Four-phase debugging framework that ensures root cause investigation before attempting fixes. Never jump to solutions.
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 systematic root-cause debugging. Use when tests fail, builds break, behavior doesn't match expectations, or you encounter any unexpected error. Use when you need a systematic approach to finding and fixing the root cause rather than guessing.
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。
コードを書く時の実装原則（deep module 設計・seam・テスタビリティ・シーム限定 TDD・コメント規約・リーダブルコード）。新しい module・関数・エンドポイント・画面の追加、DB への書き込み、認可・入力検証の追加、既存構造を変えるリファクタを含む実装の開始時に使用。CSS・HTML・テンプレート等のフロントエンド資産も対象。既存関数内の数行修正と lint/CI 等の設定ファイルでは使わない。TypeScript/Python/Go の言語別ガイドを同梱。境界: バグ・エラーの原因調査は systematic-debugging が先、提出前の diff 確認は self-review。
Apply systematic root cause analysis and debugging methodologies to diagnose and fix bugs, test failures, and unexpected behavior. Use when encountering production issues, investigating test failures, diagnosing performance problems, tracing error sources through call stacks, analyzing logs and stack traces, reproducing inconsistent bugs, debugging race conditions, investigating memory leaks, or applying scientific method to problem-solving before proposing fixes.
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 when the user wants to "investigate a bug", "debug an issue", "figure out why something is happening", "find the root cause", "troubleshoot", "強い推論で調査", "仮説を立てて検証", "原因を特定", "バグの原因調査", "なぜ動かないか調べて", "問題を切り分け", "原因不明", "デバッグ", or mentions systematic hypothesis-driven debugging. NOTE: Use this for investigating UNKNOWN causes, not for validating design proposals (use devils-advocate for that).
Replicate and validate a GitHub issue by spinning up Archon, analyzing the issue, and systematically testing all described symptoms using browser automation. Use when: User wants to reproduce a bug, validate a GitHub issue, confirm a reported problem, or investigate whether an issue is real before working on a fix. Triggers: "replicate issue", "reproduce issue", "validate issue", "confirm bug", "test issue", "can you reproduce", "try to replicate", "verify the bug". Capability: Checks out main, pulls latest, starts Archon, reads the GitHub issue, then uses agent-browser to systematically test every symptom and produce a findings report. NOT for: Fixing issues (use /archon or /exp-piv-loop:fix-issue), general UI testing (use /validate-ui).
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。
Systematic debugging methodology covering root cause analysis, log-based debugging, production debugging, memory leak diagnosis, deadlock detection, performance anomaly investigation, and reproducible bug reproduction. Distilled from real experience at Google, DeepMind, ByteDance, and Huawei. USE WHEN: investigating production incidents, debugging hard-to-reproduce bugs, analyzing crash dumps, finding race conditions, diagnosing memory leaks, debugging performance regressions, or any situation requiring systematic root cause analysis. Triggers on "debugging", "root cause", "bug", "crash", "segfault", "deadlock", "race condition", "memory leak".
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。
Plan and synthesize a source-grounded multi-paper literature review. Use for systematic literature reviews, survey matrices, inclusion/exclusion criteria, research gaps, or "review the literature on X" requests; do not use for reviewing one paper, ordinary web summaries, citation formatting only, or medical/legal conclusions.
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。
バグやテスト失敗、予期しない動作の原因を、再現手順やログ、直近の変更から調べます。仮説の検証から修正後のテストまで、根拠に沿って進めるスキルです。
会話の開始時に使えるスキルを確認し、応答や作業の前に読み込む手順を定めます。作業方法を決めるスキルを優先し、実行環境ごとの案内につなぎます。
PubMedで医学・生命科学の文献を探し、統制語や条件を使った検索式の作成、抄録・書誌情報の取得、再現可能な検索記録の整理を支援するスキル。
学術・技術文献を検索し、選定基準に沿って比較・統合するスキルです。検索履歴や除外理由を残し、根拠の強さと引用を確認したレビューにまとめます。
ボタンやフォームの操作後に状態がどう変わるかを順に追い、共有状態の意図しないリセットや非同期処理の競合で画面が期待どおりに動かない原因を調べるスキル。
4-phase root cause debugging: understand bugs before fixing.
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。
Systematic debugging with root cause investigation. (gstack)
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 architecture, component specifications, and slide generation. Three-layer tokens (primitive→semantic→component), CSS variables, spacing/typography scales, component specs, strategic slide creation. Use for design tokens, systematic design, brand-compliant presentations.
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 instead of WebSearch for ANY question requiring web research. Trigger on queries like "what is X", "explain X", "compare X and Y", "research X", or before content generation tasks. Provides systematic multi-angle research methodology instead of single superficial searches. Use this proactively when the user's question needs online information.
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 goal-like loop that decomposes work into systematic, evidence-bound ultrawork steps. Use when the user wants a goal loop or durable, checkpointed execution.
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。
When the user wants to plan, design, or implement an A/B test or experiment, or build a growth experimentation program. Also use when the user mentions "A/B test," "split test," "experiment," "test this change," "variant copy," "multivariate test," "hypothesis," "should I test this," "which version is better," "test two versions," "statistical significance," "how long should I run this test," "growth experiments," "experiment velocity," "experiment backlog," "ICE score," "experimentation program," or "experiment playbook." Use this whenever someone is comparing two approaches and wants to measure which performs better, or when they want to build a systematic experimentation practice. For tracking implementation, see analytics. For page-level conversion optimization, see cro.
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。
Protocol-driven study screening for systematic, scoping and rapid reviews. Turns a proposal or PROSPERO protocol into confirmed eligibility rules, then screens titles/abstracts and full texts with two blinded AI reviewers and a third-reviewer adjudicator: ordered exclusion codes, no silent defaults, resumable batch runs, QC (seed studies, near-miss rechecks, kappa and PABAK), PRISMA 2020 counts, EndNote/Zotero RIS groups, an Excel log, a methods draft and a literature_corpus handoff to academic-paper. Reads RIS, PubMed .nbib, Web of Science and CSV exports; removes duplicates. 8 modes: protocol, quick, pilot, ta-screen, ft-screen, adjudicate, audit, report. Use it to screen records against eligibility criteria, pilot screening, resolve screening conflicts, audit exclusions or report the selection process. Triggers on: screen these papers, title/abstract screening, full-text screening, screening conflicts, inclusion criteria, PRISMA flow, غربالگری مقالات, اسکرینینگ عنوان و چکیده, معیارهای ورود و خروج.
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。