「codebase」の検索結果

Fourth step in building instruction context for codebase

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。

Final step in building instruction context for codebase

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。

Third step in building instruction context for codebase

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Perform 12-Factor App compliance analysis on any codebase. Use when evaluating application architecture, auditing SaaS applications, or reviewing cloud-native applications against the original 12-Factor methodology.

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。

Second step in building instruction context for codebase

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Optimize Bazel builds for large-scale monorepos. Use when configuring Bazel, implementing remote execution, or optimizing build performance for enterprise codebases.

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Use this skill for internal TypeScript work in the nuxt-ui-tools repository. Covers the repository's inference-first style, forbidden escape hatches, public API typing rules, schema-driven type design, and how to keep complex types powerful without making the codebase harder to maintain.

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Activate when the user asks about any repository listed in the system prompt under 'OpenViking — Indexed Code Repositories', or when they ask about an external library, framework, or project that may have been indexed. Also activate when the user wants to add, remove, or manage repos. Always search the local codebase first before using this skill.

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。

Use this skill when the user requests to generate, create, or improve documentation for code, APIs, libraries, repositories, or software projects. Supports README generation, API reference documentation, inline code comments, architecture documentation, changelog generation, and developer guides. Trigger on requests like "document this code", "create a README", "generate API docs", "write developer guide", or when analyzing codebases for documentation purposes.

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。

Index a codebase with GitNexus and serve an interactive knowledge graph via web UI + Cloudflare tunnel.

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。

Token-optimized structural code search using tree-sitter AST parsing. Use instead of reading full files when you need to understand code structure, find functions, or explore a codebase efficiently.

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。

Autonomous rule adherence checker. Scans the codebase for rule violations, fixes the highest-impact ones in an isolated worktree, runs full validation, creates a PR. Uses memory to track progress across runs.

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。

Use when the user needs to run GitNexus CLI commands like analyze/index a repo, check status, clean the index, generate a wiki, or list indexed repos. Examples: "Index this repo", "Reanalyze the codebase", "Generate a wiki"

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。

Use when the user asks how code works, wants to understand architecture, trace execution flows, or explore unfamiliar parts of the codebase. Examples: "How does X work?", "What calls this function?", "Show me the auth flow"

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。

Core module implementation for claude-flow v3. Implements DDD domains, clean architecture patterns, dependency injection, and modular TypeScript codebase with comprehensive testing.

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Comprehensive truth scoring, code quality verification, and automatic rollback system with 0.95 accuracy threshold for ensuring high-quality agent outputs and codebase reliability.

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。

Audit codebases and infrastructure for security issues. Use when scanning dependencies for vulnerabilities, detecting hardcoded secrets, checking OWASP top 10 issues, verifying SSL/TLS, auditing file permissions, or reviewing code for injection and auth flaws.

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。

Audit codebases, infrastructure, AND agentic AI systems for security issues. Covers traditional security (dependencies, secrets, OWASP web top 10, SSL/TLS, file permissions) PLUS agentic security (prompt injection scanning, identity spoofing detection, memory poisoning checks, multi-agent communication audit, OWASP Agentic Top 10). Use when scanning for vulnerabilities, detecting hardcoded secrets, reviewing agent workspace configuration, checking prompt injection vectors, or auditing agent permissions and boundaries.

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。

Run a two-pass, multidisciplinary code audit led by a tie-breaker lead, combining security, performance, UX, DX, and edge-case analysis into one prioritized report with concrete fixes. Use when the user asks to audit code, perform a deep review, stress-test a codebase, or produce a risk-ranked remediation plan across backend, frontend, APIs, infra scripts, and product flows.

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。

Triage requirements, specs, or tickets. Detect input (pasted text, markdown path, tracker ticket id/URL, or empty prompt). Explore codebase + docs, score completeness, ask clarifying questions, write a markdown report. Trigger when user says "triage", "review this spec", "is this requirement complete", or provides a ticket/spec to assess.

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。

Generates comprehensive, workable unit tests for any programming language using a multi-agent pipeline. Use when asked to generate tests, write unit tests, improve test coverage, add test coverage, create test files, or test a codebase. Supports C#, TypeScript, JavaScript, Python, Go, Rust, Java, and more. Orchestrates research, planning, and implementation phases to produce tests that compile, pass, and follow project conventions.

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Migration and code evolution instructions generator for GitHub Copilot. Analyzes differences between two project versions (branches, commits, or releases) to create precise instructions allowing Copilot to maintain consistency during technology migrations, major refactoring, or framework version upgrades.

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。

Apply GDPR-compliant engineering practices across your codebase. Use this skill whenever you are designing APIs, writing data models, building authentication flows, implementing logging, handling user data, writing retention/deletion jobs, designing cloud infrastructure, or reviewing pull requests for privacy compliance. Trigger this skill for any task involving personal data, user accounts, cookies, analytics, emails, audit logs, encryption, pseudonymization, anonymization, data exports, breach response, CI/CD pipelines that process real data, or any question framed as "is this GDPR-compliant?". Inspired by CNIL developer guidance and GDPR Articles 5, 25, 32, 33, 35.

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。

Technology-agnostic prompt generator that creates customizable AI prompts for scanning codebases and identifying high-quality code exemplars. Supports multiple programming languages (.NET, Java, JavaScript, TypeScript, React, Angular, Python) with configurable analysis depth, categorization methods, and documentation formats to establish coding standards and maintain consistency across development teams.

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。