'phase arc' 검색 결과

Guided journey from a raw app idea to a validated, cleanly architected first version that ships on a sustainable cadence. Orchestrates ten skills phase by phase - lean-startup, design-sprint, clean-architecture, domain-driven-design, clean-code, pragmatic-programmer, system-design, ios-hig-design, 37signals-way, software-design-philosophy - asking the user questions at every decision point and recording results in the project docs/ folder (PRODUCT.md, ARCHITECTURE.md, EXPERIMENTS.md, CREATE-APP-PLAN.md) so the journey resumes across sessions. Use when the user wants to build a new app, validate an idea before writing code, architect an MVP that will not need a rewrite, or says 'help me build my app the right way'. App already exists: use improve-app or grow-app. Business idea not yet validated: run create-business first. Marketing site only: use create-website. Architecture-only question: design-code-architecture. For one framework in isolation, invoke that skill directly.

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Systematic strategic planning framework for philosophy and interdisciplinary academic papers targeting preprint platforms (PhilArchive, arXiv, PhilSci-Archive). Use when users want to: (1) plan a paper on a specific topic, (2) identify research gaps and assess originality, (3) develop optimized paper outlines, (4) prepare for preprint submission, or (5) understand platform requirements and writing standards. Triggered by phrases like 'plan a paper on,' 'help me design a paper about,' 'identify research gaps in,' 'is this idea original,' or when users need structured research planning. The skill guides through three phases: Platform Analysis (identifying target venue and studying sample papers), Theoretical Framework (AI-driven literature search and gap identification), and Outline Optimization (structured design with reviewer-perspective self-assessment). Each phase includes quality evaluation standards and validation checkpoints. Output: optimized detailed outline ready for systematic writing (use with academic-paper-composer skill).

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Use when you want phase research without planning: to investigate before deciding a phase is feasible, or to re-research after a plan already exists. Standalone command; most workflows should use /gsd-plan-phase instead.

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Systematic strategic planning framework for philosophy and interdisciplinary academic papers targeting preprint platforms (PhilArchive, arXiv, PhilSci-Archive). Use when users want to: (1) plan a paper on a specific topic, (2) identify research gaps and assess originality, (3) develop optimized paper outlines, (4) prepare for preprint submission, or (5) understand platform requirements and writing standards. Triggered by phrases like 'plan a paper on,' 'help me design a paper about,' 'identify research gaps in,' 'is this idea original,' or when users need structured research planning. The skill guides through three phases: Platform Analysis (identifying target venue and studying sample papers), Theoretical Framework (AI-driven literature search and gap identification), and Outline Optimization (structured design with reviewer-perspective self-assessment). Each phase includes quality evaluation standards and validation checkpoints.

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Review implemented features against their requirements, add missing tests, and check performance constraints. Produce documentation, a table linking requirements to code and tests, and evidence showing whether the feature is ready for deployment.

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• Review an implementation against its specification
• Add tests for uncovered requirements
• Link requirements to code and passing tests

Investigate complex topics using web sources, stored knowledge, and relevant code. Break questions into smaller parts, compare evidence, and produce a structured report with confidence assessments, unresolved questions, and next steps.

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• Investigating a complex topic through smaller research questions
• Comparing web sources with stored knowledge and code
• Summarizing evidence quality and conflicting findings

Use Phaser 4 Arcade Physics: enable the world, give sprites bodies, set velocity/acceleration/gravity, and resolve collisions with colliders, overlaps, groups, and world bounds. Use when a Phaser game needs movement or collisions — when the user mentions Arcade Physics, this.physics, setVelocity, collider, overlap, gravity, onFloor, or a platformer/top-down controller. For game config, scenes, and the loader use phaser-core.

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Your competitor just launched. You have no idea how they grew so fast. Should you reverse-engineer their website? Track their social media? Map their growth flywheel? This gives you the complete SOP — from Wayback Machine snapshots to X/Twitter propagation analysis to growth flywheel scoring. Built from 150+ AI startup competitive analyses including the Lovable case study (4.3M views, 229K impressions launch day). By @WeiYipei. What's inside: • 4-step research framework (website teardown → social media → traffic sources → ad spend) • 3-version website evolution analysis (V1 / Beta / Launch via Wayback Machine) • X/Twitter propagation chain mapping (4-phase model + single-post teardown template) • Growth flywheel 6-stage scoring system (Activation → Referral → Acquisition → Retention → Revenue → Product) • KOL identification framework (Traffic King / Topic Starter / Mindset Shifter) • Content effectiveness ranking (validated: Visual Demo > User Story > Competitor Comparison) • ICP deep analysis template + Freemium pricing teardown • Complete self-check checklist 🇨🇳 你的竞品刚刚爆了。你完全不知道他们怎么做到的。该拆官网？盯社媒？画增长飞轮？这份 SOP 给你从 Wayback Machine 快照到 X/Twitter 传播链路还原到飞轮六阶段评分的完整方法论。基于 150+ AI 创业公司竞品分析实战，含 Lovable 完整案例。 🇯🇵 競合が突然バズった。どうやって成長したか全く分からない。このSOPは、Waybackスナップショットからツイッター伝播チェーン分析、フライホイール6段階スコアリングまでの完全な競合調査フレームワークを提供します。150以上のAIスタートアップ分析から構築。 🇰🇷 경쟁사가 갑자기 폭발적으로 성장했습니다. 어떻게 그렇게 빨리 성장했는지 모릅니다. 이 SOP는 Wayback 스냅샷부터 X/Twitter 전파 체인 분석, 플라이휠 6단계 스코어링까지 완전한 경쟁사 조사 프레임워크를 제공합니다. 150개 이상의 AI 스타트업 분석에서 구축. Triggers: "competitor research" | "competitive analysis" | "competitor analysis" | "growth flywheel" | "market research" | "竞品调研" | "竞品分析" | "增长飞轮" | "传播链路" | "競合分析" | "경쟁사 분석" | "social media teardown" | "Twitter propagation" | "content strategy analysis"

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Strategic keyword research powered by web search and brand context. Use this skill whenever the user mentions keywords, keyword research, SEO topics, content topics, 'what should I write about', content strategy, blog ideas, search traffic, or content planning. Also trigger when the user wants to plan what content to create, when existing content isn't attracting search traffic, when any skill needs keyword-plan.md but it doesn't exist, or when the user asks about SEO in the context of content creation. Even casual mentions like 'I need blog post ideas' or 'what topics should I cover' warrant this skill. 8-phase process from seed to content brief.

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课题研究员（谭溯源 Tan）。由 research-chief-editor 主理人调度，对课题进行广泛初步调研（Phase 1）或对子主题进行深度研究（Phase 3）。多源聚合（≥5 来源），撰写带引用的研究草稿，覆盖学术/权威机构/行业/媒体多级来源。 触发词：由 research-chief-editor 主理人调度执行，不直接面向用户。当主理人下发 Phase 1 初始调研或 Phase 3 深度调研任务时激活。

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Skippable Phase 0 of the Gaia evidence verification pipeline. Use only on declared need for higher-quality Stage-2 evidence: a promotion candidate, or a skill that gaia-meta-sweep flagged as under-evidenced. Given a skill id, source repo/context, and needed evidence types (benchmark-result, arxiv, peer-review, social-signal), it runs Firecrawl searches, scrapes top hits to markdown, and appends discovered sources into Phase 1 inputs. Missing benchmark evidence is recorded as benchmark-source candidates first, not direct scoring rows. Trigger phrases: "discover evidence", "find new evidence", "Phase 0", "run ev-discovery", "search for benchmarks/papers", "under-evidenced", "promotion candidate needs stronger proof". This is the ONLY ev-* skill that searches the web for NEW evidence; other ev-* skills aggregate or verify known sources. Requires Firecrawl to be usable (`firecrawl --status` authenticated OR FIRECRAWL_API_KEY set); skips gracefully when neither holds.

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Apply source-aware mechanical-engineering judgment to research, analysis, coding, writing, teaching, research identity, and release work. Use for thermal-fluid systems, heat transfer, fluid mechanics, thermodynamics, HVAC, energy systems, turbomachinery, piping, multiphase flow, experiments, correlations, CFD, reduced-order models, AI/ML, uncertainty, engineering datasets, literature reviews, citations, manuscripts, reviewer revisions, Overleaf packages, figures, proposals, research software, reproducibility, public releases, engineering teaching materials, or a research-project logo and visual identity.

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Plan market, competitor, consumer, or financial research with chapter outlines, data requirements, and chart plans. Then turn collected evidence into a structured Markdown report with comparisons, citations, and strategic implications, while clearly identifying missing data.

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• Planning research chapters and data collection requirements
• Turning market and competitor findings into a report
• Organizing consumer insights and brand strategy analysis

Design a Google Cloud system for data analysis or machine learning with AI agents. Turn requirements into product choices, an architecture diagram, infrastructure configuration, deployment instructions, and validation steps, with user reviews between phases.

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• Design a data analysis system with multiple AI agents
• Choose Google Cloud products for analytical requirements
• Prepare an architecture diagram and deployment guide

Audit a development milestone before archiving it by checking requirements, connections between phases, and complete user flows. It reads existing verification reports and gathers technical debt and deferred gaps to assess whether the original completion criteria were met.

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• Checking completion criteria before archiving a milestone
• Reviewing coverage of milestone requirements
• Checking connections and user flows across phases

Research an unfamiliar topic or turn a collection of sources into structured notes, a reference article, or a publish-ready draft. The workflow connects sections to evidence, makes conflicting claims visible, and guides revision before publication.

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• Research an unfamiliar field using primary sources
• Compile supplied materials into a coherent article
• Build reference notes without drafting an article

Research Guardian - Ethics Advisory & Bias Detection across all research stages Enhanced VS 3-Phase process: Surface-level screening, deep contextual analysis, constructive recommendations Use when: reviewing research ethics, checking for bias, assessing trustworthiness, QRP screening Triggers: ethics review, IRB, bias detection, QRP, trustworthiness, research integrity, p-hacking, HARKing

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Multi-AI research using available external providers (Double Diamond Discover phase) - Questions about best practices, patterns, or ecosystem research PRIORITY TRIGGERS (always invoke): "octo research", "octo discover", "co-research", "co-discover" DO NOT use for: simple file searches (use Read/Grep), questions Claude can answer directly, debugging issues (use skill-debug), or "what are my options" for decision support.

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Model a Phase-Locked Loop (PLL) IC from its datasheet or system specs using Mixed-Signal Blockset. Without this skill, agents universally select the wrong solver and produce non-functional PLL models — 100% of unguided attempts fail. Covers Integer-N, Fractional-N, Dual Modulus architectures, loop filter design, lock time optimization, VCO phase noise configuration, and msbPllArchitectures/msbPllFoundation block assembly. Use when: PLL modeling, frequency synthesizer design, phase noise simulation, lock time analysis, charge pump design, loop filter tuning, datasheet-to-model, Mixed-Signal Blockset PLL, msbPllArchitectures.

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Use before planning a frontend phase, or when a UI contract must be locked before implementation. Orchestrates gsd-ui-researcher and gsd-ui-checker to validate, research, and verify UI-SPEC.md for the phase.

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Use after a phase has been discussed, or when the user asks for a PLAN.md for a roadmap phase. Researches, spawns gsd-planner, verifies with gsd-plan-checker, and iterates; supports --gaps, --prd, --skip-research.

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Creates high-converting 'X vs Y' and 'X alternatives' SEO pages that capture comparison search traffic. Researches competitors, writes honest comparison content, and adds schema markup (FAQPage, ItemList). Use when someone needs alternatives pages, comparison content, or says 'alternatives page', 'vs page', 'comparison', 'competitor alternatives', 'X vs Y page', or wants to capture competitor brand search traffic with SEO content. Also trigger when someone wants to rank for competitor brand names, capture competitor search traffic, create a compare page, or build a competitive content hub. Even if they just say 'how do we compete with X' or 'we need to show up when people search for [competitor]', this skill applies. Owns the individual alternatives / vs / comparison page. For a batch roadmap of many pages with a phase tracker, see /seo-machine. For programmatic SEO and templated content at scale, see /seo-content.

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Phase 1 of the Forge pipeline. Gather real context from the codebase, answer everything the code can answer through exploration, then grill the user one question at a time (with a recommended answer) for only what code cannot answer, and write a research document. Use when starting /forge-research or the research step of /forgemaster, or when the user wants a research-first investigation before planning a feature.

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기능 추가와 버그 수정 등 개발 작업을 변경 규모에 따라 조사·계획·테스트·검토 단계로 배분합니다. 관련 스킬이 공유하는 절차에 계획 승인과 커밋 전 확인을 포함합니다.

• 기능 추가와 버그 수정 절차를 통일합니다
• 변경 규모에 맞는 단계를 선택합니다
• 설계 문서에서 MVP 개발을 진행합니다