「cover」の検索結果

Defines testing quality metrics, coverage thresholds, and anti-patterns. Use when establishing test gates or validating a test suite's coverage targets.

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。

Provides error classification, recovery, and graceful-degradation patterns. Use when implementing error handling or debugging resilience failures in any 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。

This skill should be used when the user asks to "revise a chapter", "continuity check", "find inconsistencies", "audit character state", "check timeline consistency", "developmental edit", "structural revision", "reverse outline", "cut a subplot", "revision passes", "what pass next", "pacing check" as a revision pass, "clue check", "cut to a word count", or "length pass", or to prepare existing story material for the next revision pass. NOT for planning book structure (use plot-structure), scene-level craft (use scene-craft), voice consistency (use voice-style), or reconciling a chapter drafted by discovery (use discovery-drafting).

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。

Provide comprehensive techniques for testing REST, SOAP, and GraphQL APIs during bug bounty hunting and penetration testing engagements. Covers vulnerability discovery, authentication bypass, IDOR exploitation, and API-specific attack vectors.

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 an agent workflow needs deterministic recovery evidence for sandbox, MCP/tool, worker, checkpoint, memory, or orchestration failures.

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。

Discover AAS skills for an explicit task and compare their complete instructions without installing them.

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。

SaaS vendor data processing inventory management. Covers shadow IT discovery, API-based data flow detection, processing purpose mapping, contract status tracking, and continuous inventory reconciliation for cloud service providers.

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。

Implements data lineage tracking for privacy compliance including origin tracking, transformation logging, access auditing, deletion verification, and cross-system lineage graphs. Covers source-to-sink mapping, GDPR Art. 30 RoPA integration, automated lineage discovery, and breach impact scoping. Keywords: data lineage, data provenance, data flow mapping, transformation logging, deletion verification.

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。

Builds comprehensive data inventory per GDPR Art. 30 Records of Processing Activities. Covers system-by-system discovery, data flow diagramming, third-party identification, and legal basis per category. Keywords: data inventory, data mapping, Art 30, RoPA, data flow, processing activities.

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。

Coordinates credit monitoring and identity theft protection services for individuals affected by a data breach. Covers vendor selection criteria, enrollment logistics, coverage duration (12-24 months), identity theft insurance options, communication to affected individuals, and enrollment rate tracking. Keywords: credit monitoring, identity protection, breach response, Experian, enrollment, identity theft insurance.

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。

Discovers the core attributes of the current code repository and its projects — languages, frameworks, tooling, and where things live — and writes a concise reference section directly into the project's AGENTS.md or CLAUDE.md for other skills, agents, and hooks to consume. Use when scanning, analyzing, or detecting the project's technology stack, build tools, or repository structure. Does not create or update project documentation — use project-documentation for writing feature or system docs.

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。

Produce a standalone test plan by analyzing code for test coverage gaps and edge cases. Use when you need to create, generate, or draft a test plan for a branch, need to analyze test coverage, or need to identify what tests to write for specific files or directories. Does not produce a plain-language plan for a person to run tests by hand — use manual-test-planning for that. Does not write test code — use tdd to implement behavior test-first. Does not refine existing plans — use iterative-plan-review. Does not review code quality, security, or style — use code-review for full code review. Does not evaluate architectural testability or structural coupling — use architectural-analysis for architectural assessment.

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。

Create professional, consultant-grade PowerPoint presentations from scratch using MckEngine (python-pptx wrapper) with McKinsey-style design. Use when user asks to create slides, pitch decks, business presentations, strategy decks, quarterly reviews, board meeting slides, or any professional PPTX. AI calls eng.cover(), eng.donut(), eng.timeline() etc — 67 high-level methods across 12 categories (structure, data, framework, comparison, narrative, timeline, team, charts, images, advanced viz, dashboards, visual storytelling), consistent typography, zero file-corruption issues, BLOCK_ARC native shapes for circular charts (donut, pie, gauge), production-hardened guard rails for spacing, overflow, legend consistency, title style uniformity, dynamic sizing for variable-count layouts, horizontal item overflow protection, chart rendering, and AI-generated cover images via Tencent Hunyuan 2.0 with professional cutout, cool grey-blue tint, and McKinsey-style Bézier ribbon decoration.

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。

Optimize YouTube videos for search and discovery. Generates SEO-optimized titles, descriptions, tags, hashtags, and chapters. Includes keyword research and competitor analysis. Use when publishing videos, improving discoverability, or optimizing existing content.

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。

n8n workflow automation knowledge base. Provides n8n node information, node functionality details, workflow patterns, and configuration examples. Covers triggers, data transformation, data input/output, AI integration, covering 10 nodes. Keywords: n8n, workflow, automation, node, trigger, webhook, http request, database, ai agent.

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。

Search and discover Claude Code skills and MCP servers from marketplaces, GitHub repositories, and registries. Use when (1) user asks to find skills for a specific task, (2) looking for MCP servers to connect external tools, (3) user mentions "find skill", "search MCP", "discover tools", or "what skills exist for X", (4) before creating a custom skill to check if one already exists.

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。

Recover Vine video metadata (author, user ID, title, thumbnail) from vine.co oembed endpoint even though the Vine API and pages are dead. Use when: (1) you have Vine shortcode URLs (vine.co/v/XXXXX) and need to identify the creator, (2) the Vine page only shows a loading spinner, (3) archive-api.vineapp.com returns 404, (4) need to map Vine shortcodes to user IDs for cross-referencing against the divine.video database. The oembed endpoint is a still-live metadata oracle for the otherwise-dead Vine platform.

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。

Generate comprehensive test case documentation from test code, test framework output, existing test docs, and source code context. Use when documenting test suites, creating test specifications, generating test coverage reports, onboarding developers to testing practices, or preparing QA documentation. Analyzes test functions (pytest, unittest) to extract test names, docstrings, assertions, and organization, then produces structured markdown with both overview-level summaries and detailed test case specifications including purpose, preconditions, steps, expected results, and test data. Triggers when users ask to document tests, generate test specifications, create test reports, summarize test coverage, or explain what tests do.

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。

Establish explicit traceability between formal specifications (preconditions, postconditions, invariants) and verified code components with their correctness proofs. Produce structured Markdown mapping reports showing verification coverage and proof evidence. Use when auditing formal verification, documenting verified systems, establishing traceability for certification, or when the user asks to map specifications to code, generate verification reports, or analyze verification coverage in Coq, Dafny, Isabelle, or other proof assistants.

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。

Removes unnecessary code from a repository while preserving exactly the behavior exercised by a given test suite. Use this skill when you need to debloat, slim down, or remove unused code from a codebase based on test coverage. The skill analyzes which code elements (files, classes, functions, methods, branches, imports) are exercised by tests, identifies unreachable or unused code, and safely removes it while ensuring all tests continue to pass. Triggers when users ask to remove unused code, debloat based on tests, eliminate dead code guided by test coverage, or slim down a repository to only test-required functionality.

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。

Automatically generate regression tests for Java codebases by analyzing changes between old and new code versions. Use when users need to: (1) Generate tests after refactoring or code changes, (2) Ensure previously tested behavior still works in new versions, (3) Cover modified or newly added code paths, (4) Migrate existing tests to work with updated APIs or signatures, (5) Maintain test coverage during code evolution. Supports JUnit and TestNG frameworks with unit tests, parameterized tests, and exception testing patterns.

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。

Optimize test suites using mutation testing to maximize mutation kill rate with minimal tests. Use when you need to reduce test suite size while maintaining quality, identify redundant tests, improve mutation coverage, or validate test effectiveness. The skill analyzes test coverage, execution intervals, and redundancy using mutation operators, selects or generates a minimal subset of tests that maximizes mutation kill rate, and outputs an optimized test suite with detailed reports showing killed and surviving mutants. Supports multiple programming languages and mutation testing frameworks.

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。

This skill applies brand guidelines to content creation. It should be used when the user asks to "write an email", "draft a proposal", "create a pitch deck", "write a LinkedIn post", "draft a presentation", "write a Slack message", "draft sales content", or any content creation request where brand voice should be applied. Also triggers on "on-brand", "brand voice", "enforce voice", "apply brand guidelines", "brand-aligned content", "write in our voice", "use our brand tone", "make this sound like us", "rewrite this in our tone", or "this doesn't sound on-brand". Not for generating guidelines from scratch (use guideline-generation) or discovering brand materials (use discover-brand).

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。

One-time autonomous design context discovery. Scans the codebase to extract design tokens, typography, colors, spacing, brand patterns, and tech stack, then writes a Design Context section to CLAUDE.md. Zero questions asked. Use when: 'setup design', 'design context', 'design tokens', 'brand discovery', 'design system scan', 'initialize design', 'teach design'.

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。