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Systematically QA test a web application. Use when asked to "qa", "QA", "test this site", "find bugs", "dogfood", or review quality. Four modes: diff-aware (automatic on feature branches — analyzes git diff, identifies affected pages, tests them), full (systematic exploration), quick (30-second smoke test), regression (compare against baseline). Produces structured report with health score, screenshots, and repro steps.
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4-phase systematic debugging methodology with root cause analysis and evidence-based verification. Use when debugging complex issues.
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Systematic debugging methodology. Reproduce → Isolate → Hypothesize → Verify → Fix → Confirm.
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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.
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Systematic literature review methodology for social science research. Use when conducting systematic reviews, research synthesis, meta-analyses, scoping reviews, or comprehensive literature searches across economics, political science, sociology, education, public health, and development. Produces structured notebook cells with search strategy, evidence table, thematic synthesis, and gap analysis.
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Systematic debugging with root cause investigation. Produces a diagnostic report; mk:fix owns remediation and mk:build-fix owns compile/build failures. Use when asked to "debug this", "fix this bug", "why is this broken", "investigate this error", or "root cause analysis". Proactively suggest when the user reports errors, unexpected behavior, or is troubleshooting why something stopped working. NOT for applying fixes without investigation (see mk:fix); NOT for step-by-step evidence-based reasoning (see mk:sequential-thinking).
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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.
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Use when the user asks for deep or academic research — a literature review, PRISMA systematic review or meta-analysis, fact-check, evidence synthesis, APA 7 research report, or Socratic guidance to sharpen a vague research question. Runs a 13-agent pipeline with full, quick, review, lit-review, fact-check, socratic, and systematic-review modes.
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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.
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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.
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Systematic 6-phase debugging protocol. Structured approach to bugs with quick checks, isolated testing, 20-minute rule, and bug report template.
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8-phase development cycle: Feature requests, current state, functional planning, frontend, backend planning, backend code, tests, use cases. Iterative framework for systematic software development.
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Systematic debugging: production-level reproduce, isolate, instrument, verify. Use when implementing, reviewing or testing systematic debugging for React, Vite, Next.js or Perfect_AI projects.
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Four-phase debugging framework that ensures root cause investigation before attempting fixes. Never jump to solutions.
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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.
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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.
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コードを書く時の実装原則（既存パターンの踏襲・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）。プロダクションコードの差分を作る時に、規模を問わず使用（数行の修正も含む）。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では特に。CSS・HTML・テンプレート等のフロントエンド資産も対象。lint・CI 等の設定ファイルだけの変更では使わない。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。
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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).
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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.
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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".
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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.
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规定会话开始时检查相关技能，并在回复或执行任务前加载的流程。优先使用决定工作方法的技能，再衔接实施技能及各运行环境的使用指南。
通过复现步骤、日志和近期更改，调查缺陷、测试失败及异常行为的原因。按证据推进假设验证、修复和修复后的测试，逐步确认问题根源。
检索学术与技术文献，按预设标准筛选并综合比较。记录检索过程和排除理由，梳理研究分歧与未解问题，区分证据置信度并核查引用，形成可追溯的综述。