1.5천건 · 관련도순
Analyze an existing codebase with parallel agents and produce seven structured documents covering technology, integrations, architecture, conventions, testing, and concerns. Use the results to understand an unfamiliar project or prepare for major changes.
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Produce a structured codebase analysis report with architecture overview, critical files, patterns, and actionable recommendations. Use when asked to "analyze codebase", "explore codebase", "understand this codebase", "map the codebase", "give me an overview of this project", "what does this codebase do", "codebase report", "project analysis", "audit this codebase", or "how is this project structured".
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Explore unfamiliar code with Codebase Memory to map architecture, trace function calls and dependencies, and assess change impact. Findings are checked against source files, with index freshness and coverage considered before drawing conclusions.
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Map an existing codebase into seven documents covering its technology, structure, architecture, conventions, integrations, tests, and concerns. Link findings to file evidence, mark unknowns, and highlight differences between stated plans and the actual implementation.
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Turn any codebase into a beautiful, interactive single-page HTML course that teaches how the code works to non-technical people. Use this skill whenever someone wants to create an interactive course, tutorial, or educational walkthrough from a codebase or project. Also trigger when users mention 'turn this into a course,' 'explain this codebase interactively,' 'teach this code,' 'interactive tutorial from code,' 'codebase walkthrough,' 'learn from this codebase,' or 'make a course from this project.' This skill produces a stunning, self-contained HTML file with scroll-based navigation, animated visualizations, embedded quizzes, and code-with-plain-English side-by-side translations.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Turn any codebase into a beautiful, interactive single-page HTML course that teaches how the code works to non-technical people. Use this skill whenever someone wants to create an interactive course, tutorial, or educational walkthrough from a codebase or project. Also trigger when users mention 'turn this into a course,' 'explain this codebase interactively,' 'teach this code,' 'interactive tutorial from code,' 'codebase walkthrough,' 'learn from this codebase,' or 'make a course from this project.' This skill produces a stunning, self-contained HTML file with scroll-based navigation, animated visualizations, embedded quizzes, and code-with-plain-English side-by-side translations.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Prepare to work on an unfamiliar project by reading every source file in full. Large files are read in chunks, building a shared understanding of the codebase before development begins.
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Document a local codebase with file references, architecture diagrams, and verified project commands. For legacy modernization, assess what still runs and create a phased migration plan with validation methods suited to each component’s current condition.
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Analyze a codebase to draft onboarding documents covering project structure, technologies, local setup, and common tasks. Tailor the depth for junior engineers, senior developers, or contractors, with troubleshooting guidance and contribution checklists.
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How to work in a Codebase Wiki project (the `codebase-wiki` starter pack): an agent-authored, source-grounded wiki of the surrounding codebase. Read when the project has a `wiki/` knowledge base with `architecture/`, `modules/`, `flows/`, `concepts/`, and `guides/` sections plus `wiki/OVERVIEW.md`, or when asked to generate or refresh a wiki of this codebase. Carries the per-folder rules and freshness + log discipline, summarizes the audience/depth knobs and source-reference convention, and bundles the full generate/refresh procedure in `references/`. Complements the platform `open-knowledge` skill; does not replace it.
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[omh] Unfamiliar repository needing a guided tour: create a repo map, reading path, glossary, risk map, and first-task runway for unfamiliar codebases. Use when the user says: codebase-onboarding, codebase onboarding, repo onboarding, repository onboarding, codebase tour, code tour, new repo orientation, understand this repo.
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Interactive codebase orientation for a HUMAN who wants to learn the code. Runs the same tree-sitting + featuring pipeline as exploring-codebases but synthesizes it into guided exercises and an HTML teaching artifact rather than an analysis document. Use for "orient me to this repo", "teach me this codebase", "walk me through this code", "learning orientation", or when someone wants genuine comprehension rather than a task completed. The audience is the test: if nobody is being taught and the goal is to get work done, use exploring-codebases instead.
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First-encounter orientation on a repository nobody here has worked in yet. Runs a fixed five-step workflow — venv setup, tarball fetch, tree-sitting structural scan, featuring synthesis, then reasoning over the two — and yields an account of what the repo contains and how it is arranged, optionally written out as _FEATURES.md. Use for "I just cloned this", "what is this repo", "what does this do", "explore this repo", "give me an orientation", "what are the main features", "review what's new in this repo", or before starting work in a codebase you have not seen. This is the divergent what's-here skill. Route elsewhere for: a named symbol, a file's structure or a line range (tree-sitting); all callers of a Python symbol (searching-codebases); teaching a human the codebase through exercises (orienting-codebases); fetching or cloning a repo without analysing it (accessing-github-repos, cloning-project).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Generate and maintain AI-readable markdown documentation for a codebase in docs/. Use this skill whenever the user asks to document their codebase, generate project docs, create architecture docs, update documentation after code changes, build a knowledge base for AI agents, create onboarding docs, map out a codebase, or explain a project structure. Also trigger when users say things like "document this repo", "create docs for my project", "update the docs", "write architecture documentation", "help AI understand my code", "generate a codebase overview", or "maintain docs". This skill is specifically about creating structured markdown files in a docs/ directory that serve as a knowledge base — NOT about writing inline code comments, README files, or API reference docs from docstrings.
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Socratic tutor that teaches codebase understanding through questioning, challenges, and active recall. Invoke with /learn-codebase when onboarding to a new codebase or deepening understanding of existing code. Maintains a learning journal that tracks mastery and schedules reviews.
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Analyze an arbitrary codebase to identify functions, APIs, and data sources suitable for exposure as MCP tools, producing a tool specification document. Use when planning an MCP server for an existing project, auditing a codebase before wrapping it as an AI-accessible tool surface, comparing what a codebase can do versus what is already exposed via MCP, or generating a tool spec to hand off to scaffold-mcp-server.
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Quickly understand an unfamiliar codebase or project by mapping its architecture, identifying key components and data flows, and surfacing complexity hotspots. Load when the user asks to understand a repo, explain how something works, map the architecture, onboard to a codebase, or explore how components connect. Also triggers on "walk me through this codebase", "how does this project work", "explain the architecture", "what does this repo do", "show me the structure", "onboard me", or any request to build a mental model of a codebase before making changes.
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코드 구조를 살펴 이해와 테스트를 어렵게 하는 부분의 개선안을 도표가 포함된 HTML 보고서로 정리합니다. 후보를 선택하면 제약과 설계 결정을 대화로 구체화합니다.
기존 코드에 담긴 암묵적인 명명, 구성, 오류 처리 관례를 읽어 AI가 참고할 규칙으로 정리합니다. 방침의 충돌을 하나씩 확인하고 코드 변경 후 규칙 갱신도 지원합니다.
Audit a codebase across nine areas, including architecture, tests, security, and documentation. Produces TECH_DEBT_AUDIT.md with source locations, severity ratings, estimated repair effort, and prioritized recommendations to help plan maintenance work.
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Find opportunities to simplify a codebase by hiding complex behavior behind smaller interfaces. Compare candidates in a visual HTML report, then explore the chosen option through questions about constraints, dependencies, and testing.
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Explore an unfamiliar codebase using a graph of code relationships. Inspect its structure, find functions and classes, trace calls and imports, follow execution paths, and locate large functions for closer investigation.
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Review codebases, APIs, and tools for vulnerabilities using source evidence and bounded local checks. Produces supported findings with impact, priority, and focused fixes, and can create structured reports for explicitly requested full audits.
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Combine code from local directories or GitHub into one structured file for AI analysis. Examine project structure, search for related code, and check estimated tokens, the units AI models use to process text.
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