1.6천건 · 관련도순
Search the live web via Perplexity Search API. Use when you need current documentation, release notes, vendor pages, news, domain-constrained web search, or date/recency filtering. Not for local codebase search or stable docs already in context.
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Plan a refactor as a sequence of tiny safe commits via interview and codebase exploration. Use when restructuring working code, or when the user says 'plan a refactor'.
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Audit code quality focusing on deep modules, naming, model hygiene, and architectural clarity. Use after a burst of development, when codebase structure needs assessment, or to make code more agent-navigable.
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Start work on a Jira ticket by fetching ticket details, creating a properly named feature branch, and beginning codebase investigation. Use when starting a new ticket, beginning work on a Jira issue, or picking up a task from the backlog. Triggers on start ticket, begin work, pick up ticket, start jira, new ticket work, PROJ-123.
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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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Implement, debug and review code with focused checks. Use to fix a bug or failing test, refactor, remove code, perform a code review, or plan engineering work in repository records. Combine with UI for interface concerns and Plan for its native records. Excludes conceptual questions unrelated to a codebase.
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複雑なコードベースを体系的に分析し、アーキテクチャを可視化・ドキュメント化して新規開発者のオンボーディングを支援する汎用スキル。成果物は必ず `docs/` 配下に分割出力する。以下のリクエストで使用する：(1)「このコードベースを分析して」「全体像を教えて」など概要把握、(2)「アーキテクチャドキュメントを作って」「C4図を生成して」など設計ドキュメント生成、(3)「オンボーディング資料を作って」など新規開発者向け資料作成、(4)「技術的負債を洗い出して」など負債評価、(5)「機能一覧を出して」など機能インベントリ生成、(6)「この機能を操作したら何が起きるか追跡して」などユーザー操作フロー追跡、(7)「新機能の実装手順を出して」などフロント／バック横断の実装ガイド生成。特定の言語・フレームワーク・ディレクトリ構成に依存せず、どのリポジトリでも利用できる。
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Research any open-source repository end to end and answer the core question — SHOULD YOU contribute to it? — with a GO / NO-GO / GO-IF verdict backed by evidence: snapshot, momentum, contribution landscape (PR acceptance rates, outside-contributor merge rates, first-timer outcomes), issue health, governance, community sentiment, and a final go/no-go recommendation. Use when the user asks 'should I contribute to X', wants a before-I-contribute due-diligence check on a project, asks whether a project accepts outside PRs, wants contribution-health numbers like PR merge rates or stale-PR counts, or asks for a deep dive on an open-source codebase's health and dynamics before investing time in it.
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Generates a BACKPRESSURE.md file for any project. Analyzes codebase and PRD to produce deterministic self-verification checks that AI coding agents run on their own output.
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Format the codebase. If $ARGUMENTS is provided, format only that target. Codex equivalent of the Claude /format command.
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Use when the user wants to update, refresh, or reinstall the CopilotKit agent SKILLS (the SKILL.md files that teach this agent about CopilotKit). NOT for updating the CopilotKit codebase or project — this is specifically about refreshing the skills/knowledge this agent has loaded. Triggers on "update copilotkit skills", "update skills", "refresh skills", "skills are stale", "skills are outdated", "get latest skills", "my copilotkit knowledge is wrong", "copilotkit APIs changed", "skills seem old", "wrong API names", "reinstall skills", "skills not working right", "update your copilotkit knowledge".
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Scan the current codebase to identify and categorize every public-facing page (landing pages, product/feature pages, solutions, pricing, resources, blogs, case studies, about, legal) and produce a single authoritative inventory document. Use this skill whenever the user asks to "init overgrow", "set up overgrow", "scan the site", "inventory the pages", "categorize pages", "map the site", or whenever any other overgrow skill needs a baseline page map and none exists yet. Output is a structured markdown inventory at `.overgrow/inventory.md` that all other overgrow skills read from.
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Remove signs of AI-generated code from a codebase while preserving behavior. Use when editing or reviewing code to make it read like a human engineer on this team wrote it. Works through a test-guarded detect-modify-verify loop: pin down the functional contract and edge cases first, write or run tests as a safety net, then rewrite AI tells (redundant comments, emoji, verbose names, reflexive try/except, defensive null-guards, over-decomposition, speculative abstraction, dead code, non-idiomatic constructs, hallucinated dependencies) and re-verify after every change. The tests decide whether a defensive block is slop or a real safeguard.
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Generate project-specific AGENTS.md and companion rules by analyzing a codebase. Supports full, minimal, update, and dry-run modes with package-manager detection, monorepos, backups, managed blocks, c
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Find and fix WCAG 2.2 accessibility issues. Two modes — report (sweep a codebase or page, produce a prioritized written report, no edits) and fix (audit→edit→verify loop on a target). Prefers di
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Enable nullable reference types in a C# project and systematically resolve all warnings. USE FOR: adopting NRTs in existing codebases, file-by-file or project-wide migration, fixing CS8602/CS8618/CS86xx warnings, annotating APIs for nullability, cleaning up null-forgiving operators, upgrading dependencies with new nullable annotations. DO NOT USE FOR: projects already fully migrated with zero warnings (unless auditing suppressions), fixing a handful of nullable warnings in code that already has NRTs enabled, suppressing warnings without fixing them, C# 7.3 or earlier projects. INVOKES: Get-NullableReadiness.ps1 scanner script.
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You are a technical debt expert specializing in identifying, quantifying, and prioritizing technical debt in software projects. Analyze the codebase to uncover debt, assess its impact, and create acti
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Refactor legacy codebases, migrate outdated frameworks, and implement gradual modernization. Handles technical debt, dependency updates, and backward compatibility.
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Autonomously deep-scan entire codebase line-by-line, understand architecture and patterns, then systematically transform it to production-grade, corporate-level professional quality with optimizations
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Search logs and codebases for error patterns, stack traces, and anomalies. Correlates errors across systems and identifies root causes.
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Answer repository questions grounded entirely in source code evidence. Use when user asks a question about the codebase, user wants to understand a specific file, function, or component, or user asks "how does X work" or "where is Y defined".
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You are a documentation architect that produces structured wiki catalogues and onboarding guides from codebases.
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Detect inconsistencies in ID formatting, date/time display, monetary amounts, and enum/status labels compared to existing patterns in the codebase.
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Performs architectural code reviews focusing on design patterns, duplication, circular dependencies, and refactoring impact. Is the design consistent with the codebase? Use when reviewing code changes for architectural concerns, code smells, or structural issues.
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