Evaluates downstream tests for coverage and edge cases.
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概要と使いどころ
Evaluates downstream tests for coverage and edge cases.
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。
Ensure requirement docs define scope, terminology, acceptance criteria, edge cases, and non-functional requirements.
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。
Find missing tests for critical paths, edge cases, and failure handling in changed code.
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。
Ensure tests use clear naming and cover edge cases with proper describe/it structure.
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 wants to design, redesign, shape, critique, audit, polish, clarify, distill, harden, optimize, adapt, animate, colorize, extract, or otherwise improve a frontend interface. Covers websites, landing pages, dashboards, product UI, app shells, components, forms, settings, onboarding, and empty states. Handles UX review, visual hierarchy, information architecture, cognitive load, accessibility, performance, responsive behavior, theming, anti-patterns, typography, fonts, spacing, layout, alignment, color, motion, micro-interactions, UX copy, error states, edge cases, i18n, and reusable design systems or tokens. Also use for bland designs that need to become bolder or more delightful, loud designs that should become quieter, live browser iteration on UI elements, or ambitious visual effects that should feel technically extraordinary. Not for backend-only or non-UI tasks.
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Use when working with Allure Testops — allure TestOps test management and analytics platform monitoring. Covers project dashboards, launch tracking, test case management, defect clustering, environment matrix analysis, and CI/CD integration review. Use when managing test cases in Allure TestOps, reviewing launch results, analyzing flaky tests, or tracking quality trends.
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。
Clean Architecture patterns for Android and Kotlin Multiplatform projects — module structure, dependency rules, UseCases, Repositories, and data layer patterns.
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Stop and check this skill before finishing any reply to a question about how to use Claude or a Claude product — it recommends matching courses, tutorials, and use cases from Claude Academy (academy.claude.com), Anthropic's learning hub. Trigger on: "how do I", "how can I", "getting started with", "what can Claude do", "teach me", "learn to use"; questions about artifacts, projects, skills, plugins, connectors, MCP; requests about rolling Claude out to a team, class, or organization; and any ask for training materials, onboarding content, or learning resources. Use it when the user is learning how to use a feature or product — not when they are mid-task and just want the task done. This skill composes with other skills: after consulting product documentation to answer how a Claude feature works, also check here for a matching course or tutorial — a docs-grounded answer and an Academy recommendation belong together. Only recommend on a strong match; never invent Academy 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。
Create or update a reusable product marketing context document with positioning, audience, ICP, use cases, and messaging. Use at the start of a project to avoid repeating core marketing context across tasks.
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 complete solutions for specific Dataverse SDK use cases with architecture recommendations
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Improve interface resilience through better error handling, i18n support, text overflow handling, and edge case management. Makes interfaces robust and production-ready. Use when the user asks to harden, make production-ready, handle edge cases, add error states, or fix overflow and i18n issues.
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Use when turning something that happened into something that makes the next run better - "write a retro", "record this paper cut", "this bug escaped verification", "make this an eval", "why do we keep hitting this", "did that change actually help", "scorecard", "what did we learn from that run", "lessons keep getting re-learned". Covers the six-step loop (capture, classify, convert, change, measure, retro), the repo artifact each step produces, and how escaped bugs become eval cases. Do NOT use to design or judge a single workflow experiment (see `workflow-experimentation`, which this loop feeds), to decide where to run work (see `dogfooding`), or to debug one failed execution in the moment.
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Get paid from day one. Payments, subscriptions, billing portal, webhooks, metered billing, Stripe Connect. The complete guide to implementing Stripe correctly, including all the edge cases that will bite you at 3am. This isn't just API calls - it's the full payment system: handling failures, managing subscriptions, dealing with dunning, and keeping revenue flowing. Use when: stripe, payments, subscription, billing, checkout.
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Curated collection of high-quality prompts for various use cases. Includes role-based prompts, task-specific templates, and prompt refinement techniques. Use when user needs prompt templates, role-play prompts, or ready-to-use prompt examples for coding, writing, analysis, or creative tasks.
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Pitfalls, examples, and edge cases for FETIH Kanban workers. The lifecycle itself is auto-injected into every worker's system prompt as KANBAN_GUIDANCE (from agent/prompt_builder.py); this skill is what you load when you want deeper detail on specific scenarios.
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。
Legal precedent App-in-Skill (Busabase-backed) desk for internal casebase search, local court-pattern analysis, similar-case packs, citations, and approval-gated research exports. Use when the user invokes $kelly-legal-precedent-desk, mentions 类案检索, 本地裁判尺度, 内部案例库查询, 案例查阅与收藏, precedent research, similar cases, legal research pack, or wants a Busabase-backed desk where lawyers review agent-prepared precedent findings before reuse.
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Build, analyze, repair, and audit finance three-statement models and operating forecasts. Use when the user invokes $kelly-finance, asks for 财务三表, 三表模型, income statement, balance sheet, cash flow statement, forecast model, budget model, financial projections, FP&A model, SaaS/unit economics forecast, fundraising model, board finance pack, investor model, model checks, balance-sheet balancing, cash runway, working capital, capex/depreciation schedules, debt schedules, scenario/sensitivity cases, or Excel/Sheets-ready finance outputs.
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。
Review board (Busabase App-in-Skill) that runs a fixed suite of mock test cases against a baseline vs candidate agent version and surfaces rubric-scored regressions before a release. Use when the user invokes $kelly-agent-eval or /kelly-agent-eval, wants to review agent-version regressions, compare baseline vs candidate quality, triage a release, or record a release approve/block decision. Deterministic mock rubric scores only — not a real LLM-judge call, and it never deploys anything.
日本語の概要は準備中です。原文の説明を表示しています。
Analyze existing code and write comprehensive unit and integration tests for it. Detects the test framework, identifies untested code paths, and generates tests with proper mocking, edge cases, and assertions. Use when the user asks to add tests, improve coverage, or test a specific module.
日本語の概要は準備中です。原文の説明を表示しています。
Set up an LLM-judge evaluation that extracts canonical use cases for a PostHog feature at scale and streams the results to a Slack channel as a live feed. Use when someone wants to understand how users are actually using a specific AI/LLM-powered feature in production — what they're investigating, what questions they're trying to answer, and what patterns surface — without manually reading hundreds of traces. Assumes the feature emits `$ai_generation` and `$ai_evaluation` events with `$session_id` linkage to the trigger user's recording (the standard setup post the session-summary linkage PRs).
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。
Walk every branching path and boundary condition in content, report only unhandled edge cases. Orthogonal to adversarial review - method-driven not attitude-driven. Use when you need exhaustive edge-case analysis of code, specs, or diffs.
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。
Build demos for AI product showcases. TRIGGERS - Use when user needs help with ai-demo-builder related tasks.
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 5G use cases. TRIGGERS - Use when user needs help with 5g-use-case-analysis related tasks.
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。
Deep, excruciating code review. Use anytime to analyze code for correctness, edge cases, security, performance, and design issues. Not tied to baseline—this is pure code analysis.
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。