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概要と使いどころ
Create evidence-aware, interactive visual explainers as self-contained offline HTML. Use when a user asks to explain a concept, repository module, engineering tradeoff, or incident with a diagram, walkthrough, ELI5 treatment, data/request trace, failure view, or teach-back. Do not use for a plain short answer, ordinary prose rewrite, generic website implementation, or unsupported claims presented as facts.
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Use this skill when asked to perform any of the following actions in a Java project: - To add jspecify support - To prevent NullPointerExceptions - To better handle Nullability This skill will add jspecify dependency, configure Maven or Gradle build to automatically use jspecify for checking Nullability issues.
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。
CesiumJS materials and post-processing — Material, Fabric JSON, MaterialAppearance, ImageBasedLighting, PostProcessStage, PostProcessStageLibrary, bloom, depth of field, ambient occlusion, FXAA, tonemapping, BlendingState. Use when defining Fabric materials for entities or primitives, configuring PBR image-based lighting, or adding screen-space post-processing effects.
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Use when tutoring a student in MATLAB programming, coaching beginners, explaining MATLAB concepts interactively, or running a conversational AI tutor session.
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 AI tutor session concerns MATLAB programming concepts, MATLAB syntax, MATLAB errors, MATLAB code style, MATLAB projects, or MATLAB toolbox workflows.
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 a learner asks for help with MATLAB homework, labs, projects, graded assignments, take-home exams, quizzes, or any programming task where academic integrity, course policy, or instructor constraints may limit direct solutions. Use to provide policy-aware hints, conceptual coaching, partial feedback, and assignment-safe MATLAB tutoring.
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 creating, asking, grading, or explaining multiple choice questions for MATLAB programming practice, concept checks, quizzes, or tutoring exercises.
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Teach the user a new skill or concept, within this workspace.
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。
Author and maintain MANUAL and hybrid test cases and suites in TestRail, Xray (Jira), Zephyr Scale, and Qase. Covers test-case anatomy (title, preconditions, steps, expected results, test data), suite/section organization, bulk authoring from user stories and acceptance criteria, ambiguous-step linting, CSV/API import-export payloads per tool, requirement traceability and coverage gaps, review hygiene, and when a manual case should graduate to automation. Use when: "write a test case," "manual test case," "TestRail case," "Xray test," "Zephyr Scale case," "Qase case," "import CSV into TestRail," "lint these steps," "traceability report," "should this be automated." Not for: Generating automated TEST CODE — that is ai-test-generation. Sprint-level WHAT-to-test selection — that is test-planning. Related: ai-test-generation, test-planning, exploratory-testing, qa-project-context.
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。
Test native, React Native, hybrid, and Flutter mobile apps with Appium 3.x, Detox, Maestro, and Patrol. Covers device farm setup (BrowserStack, Sauce Labs), gesture simulation, deep link and cold-start testing, push notifications, biometric (Face ID) auth, offline/poor-network simulation, and iOS/Android permission dialog handling. Use when: "mobile test," "Appium," "Detox," "Maestro," "Patrol," "Flutter test," "iOS test," "Android test," "device farm," "deep link," "biometric," "Face ID," "permission dialog," "React Native test." Not for: device/browser matrix strategy in the abstract — use cross-browser-testing; app startup/memory/battery profiling depth — use performance-testing; mobile screenshot diffing — use visual-testing. Related: ci-cd-integration, cross-browser-testing, performance-testing, test-data-management, test-reliability.
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Trim large MetaX model directories for dummy smoke tests or real-checkpoint loading on limited GPUs. Preserve target execution paths while reducing depth; use the real-weight workflow when a loadable checkpoint is requested. Not for accuracy evaluation or model compatibility upgrades.
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Execute implementation within EPICs following test-first development, continuous SoT updates, and code traceability during PRD v0.7 Build Execution. Triggers on requests to start building, implement an epic, begin coding, or when user asks "start building", "implement epic", "coding", "development", "build execution", "implementation", "write code". Consumes EPIC- (context), TEST- (acceptance criteria). Updates existing IDs and creates code. Outputs working code with @implements traceability tags.
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Build Tier 1/2/3 cold outreach sequences differentiated by personalization depth and research signal strength during PRD v0.9 Go-to-Market. Triggers on requests to plan cold outreach, founder-led sales, or when user asks "cold email sequence", "outbound campaign", "founder outreach", "LinkedIn outreach", "Tier 1 personalization", "predictable revenue", "sales cadence", "BDR sequence". Outputs GTM-OUT-* sequence entries and lead-list references.
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Define test cases BEFORE implementation, ensuring every API, business rule, and user journey has verifiable acceptance criteria during PRD v0.7 Build Execution. Triggers on requests to define tests, plan test coverage, create test cases, or when user asks "define tests", "test planning", "what to test?", "test cases", "test coverage", "TEST-", "test-first". Consumes EPIC- (scope), API-, DBT-, BR-, UJ-. Outputs TEST- entries with Given-When-Then format. Feeds v0.7 Implementation Loop.
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 a structured implementation plan from an evidence draft. Validate paths, obtain configured independent Codex and Qoder reviews, synthesize available advice against repository evidence, preserve the draft, and produce testable acceptance criteria and validation steps.
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。
Systematically QA test any application — web apps, native macOS apps, Electron apps, CLI tools, interactive REPLs, or anything on screen. Three modes: browser (chromux/CDP, fast, DOM-level), computer (MCP computer-use, screenshot + pixel clicks, any app), and cli (tmux, send-keys + capture-pane for interactive terminals). Auto-selects mode or accepts --browser / --computer / --cli override. Use when asked to "qa", "QA", "test this site", "test this app", "find bugs", "test and fix", "fix what's broken", "dogfood", "exploratory test", "bug hunt", "QA this app", "사이트 테스트", "앱 테스트", "브라우저 QA", "화면 보고 테스트해줘", "네이티브 앱 테스트", "screen test". Three tiers: Quick (critical/high only), Standard (+ medium), Exhaustive (+ cosmetic). Produces before/after health scores, fix evidence, and a ship-readiness summary.
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。
Turn a rough idea, a bug, or a batch of unsolved problems into well-structured GitHub issue(s) and file them with `gh`, auto-classifying type + labels from the content (recommend, then confirm) and following Rove's conventions (beginner-friendly framing, concrete file pointers, an acceptance checklist, zero AI/Anthropic attribution). Handles single, batch, and "file the unsolved problems" modes. Use when the user says "file an issue", "open a GitHub issue", "draft a good first issue", "batch these as issues", "上报 issue", "提个 issue", "报个 bug", "把没解决的发上去", or wants to hand low-priority tasks to outside contributors. Distinct from the daemon-owned internal issue store (`rove api issue-*`); this skill is for outward-facing GitHub issues.
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。
Spawn Comment Sicko, fix accepted findings, and offer encodings for claimed constraints.
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 mathematical animations with Manim Community Edition(manimce), with optional TTS voiceover and synced subtitles. Generates distinctive, production-grade animations that avoid generic "AI slop" aesthetics. Use when user wants to animate concepts, equations, illustrate proofs, visualize algorithms, create math explainers, or produce 3Blue1Brown-style videos.
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。
Analyze application error logs and monitoring platform exports (Sentry, Datadog, Rollbar) to identify error patterns, duplicates, and severity. Use when someone asks to "audit errors", "analyze exceptions", "find noisy alerts", "deduplicate error groups", or "triage production errors". Parses JSON/CSV error exports and produces categorized reports with root cause analysis.
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Cucumber runs behavior-driven (BDD) tests written as plain-language Gherkin feature files and matches each Given/When/Then step to code. Use when the user wants to write feature files, implement step definitions in JavaScript or TypeScript with cucumber-js, share state through a World, add hooks, tags and profiles, or run BDD scenarios in CI. Also use when the user mentions "cucumber," "BDD," "Gherkin," "feature files," "given-when-then," "step definitions," or "behavior-driven." For contract testing, see pact.
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Implement GDPR and ePrivacy-compliant cookie consent: a banner with equal Accept and Reject buttons, per-category choices, stored consent records, consent-gated analytics with Google Consent Mode v2, and Global Privacy Control. Use when adding a cookie banner, managing marketing consent, achieving GDPR compliance for EU users, or integrating consent with analytics platforms.
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。
Dagster is a data pipeline orchestrator built around the concept of software-defined assets. Learn to define assets, ops, jobs, schedules, sensors, and resources for building maintainable data platforms.
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。
Test web application security with Burp Suite. Use when a user asks to intercept HTTP traffic, test for web vulnerabilities, fuzz API endpoints, analyze authentication flows, or perform manual web application pentesting.
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。