「develop」の検索結果

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 closing out a feature, tidying developing/ documentation, or asked to check docs health — runs the lifecycle linter and applies the README deletion rules.

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Use Gentle AI harness discipline for Pi work: clarify first, track ODD work, use applicable test-first development by default, delegate when useful, and protect review workload.

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Trigger: RDD, receipt-driven development, review authority, receipt/lineage, correction/recovery, delivery gate/kill switch, bounded review defects. Guide work.

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Runway developer API: text-to-video, image-to-video, task polling, video upscale, lip-sync. Trigger phrases: runway, runway video, gen-4 video, runway upscale, runway lip sync.

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Remove video backgrounds with VEED's direct developer API: standard, fast and green-screen endpoints. Trigger phrases: veed, remove video background, background removal, transparent video.

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Use when executing a written implementation plan across sessions or with review checkpoints. Small or single-slice plans stay inline. For same-session independent tasks, use subagent-driven-development instead.

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Use when the user explicitly requests strict or test-first TDD, or when the current conversation already contains an explicit `TDD Route: strict` decision from another Aegis workflow.

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Use when verified work needs integration or cleanup of an existing task-created branch/worktree, or the user explicitly requests merge, PR, or branch lifecycle handling.

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Use when executing a written implementation plan with independent tasks in the current session where delegation beats inline coordination cost; otherwise inline. Ad-hoc 2+ tasks without a plan use dispatching-parallel-agents.

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Use when facing 2+ independent tasks without a written plan, with no conflicting shared mutable state or sequential dependencies, where parallel delegation beats inline cost; otherwise inline. Planned tasks use subagent-driven-development.

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Regression testing strategies for AI-assisted development. Sandbox-mode API testing without database dependencies, automated bug-check workflows, and patterns to catch AI blind spots where the same model writes and reviews code.

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Capture architectural decisions made during Claude Code sessions as structured ADRs. Auto-detects decision moments, records context, alternatives considered, and rationale. Maintains an ADR log so future developers understand why the codebase is shaped the way it is.

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Register a deferred decision in the debt registry. Trigger by judgment, not a marker scan, whenever a future reader would ask "why this way?": an unmade decision, stub, loosened type, bypassed check, swallowed error, a default picked "for now", or a TODO/FIXME/HACK/XXX marker. Trigger immediately whenever you defer work, or when the user invokes $add. Over-register freely; the developer drops with "drop A", "drop A,C", or "drop all".

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Eval-Driven Development (EDD) for AI workflows. pass@k metrics, capability evals, regression evals. Triggers: eval, edd, pass@k, capability, regression, benchmark.

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Autonomous development with experimental self-correction. Iterates through quality gates until antifragile or blocked.

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Use when you write a Julia package

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Universal coding standards, best practices, and patterns for TypeScript, JavaScript, React, and Node.js development.

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Transforms knowledge sources into an Obsidian StudyVault. Two modes: (1) Document Mode — PDF/text/web sources → study notes with practice questions. (2) Codebase Mode — source code project → onboarding vault for new developers. Mode is auto-detected based on project markers in CWD.

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Mobile specialist for Flutter, React Native, and cross-platform mobile development. Use for mobile app, Flutter, Dart, iOS, Android, Riverpod, and widget work.

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INVOKE THIS SKILL when using the langgraph CLI to scaffold, develop, build, or deploy LangGraph applications. Covers langgraph new, dev, build, up, deploy, and langgraph.json configuration.

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Master skill — set up the full agent harness for any repo so an agent can work it reliably: legible (map-not-manual docs + custom lints), executable (one-command dev stack), verifiable (e2e gate + a verify-before-ship loop), plus commit hygiene and entropy control. Use when onboarding a new/unfamiliar codebase to agent-driven development — "set up the harness", "make this repo agent-ready", "harness this codebase".

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Use when a model — a full theory paper's argument or the structural/conceptual scaffolding behind an empirical AER: Insights short-format manuscript — needs to be made minimal, so it carries the single insight in a few pages. Keeps only what the insight requires; it does not develop a general framework.

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Use when deciding whether a microeconomics project fits the American Economic Journal: Microeconomics (AEJ: Micro) rather than JET, GEB, Theoretical Economics, Econometrica, or AEJ: Applied. Tests scope and broad-interest fit; it does not develop the model (see aejmic-theory-model).

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。