Results for “use-cases”

Use when tasks involve Xget URL rewriting, registry/package/container/API acceleration, integrating Xget into Git, download tools, package managers, container builds, AI SDKs, CI/CD, deployment, self-hosting, or adapting commands and config from the live README `Use Cases` section into files, environments, shells, or base URLs.

Use when tasks involve Xget URL rewriting, registry/package/container/API acceleration, integrating Xget into Git, download tools, package managers, container builds, AI SDKs, CI/CD, deployment, self-hosting, or adapting commands and config from the live README `Use Cases` section into files, environments, shells, or base URLs.

Supplements general deposition preparation with IP-specific examination frameworks for patent, trademark, copyright, and trade secret cases. Covers witness strategies for inventors, accused infringers, licensing witnesses, and experts. Use alongside @deposition-preparation and @deposition-expert-witness when planning IP depositions, drafting outlines, or analyzing witness strategy.

Comprehensive QA and testing skill for quality assurance, test automation, and testing strategies for ReactJS, NextJS, NodeJS applications. Includes test suite generation, coverage analysis, E2E testing setup, and quality metrics. Use when designing test strategies, writing test cases, implementing test automation, performing manual testing, or analyzing test coverage.

Test generation is repetitive but critical. Developers skip tests because writing edge cases is tedious. AI agents can generate tests quickly but often produce brittle, unrealistic tests that provide false confidence. Tests that mock internals, use fake data like "foo@example.com", or test implementation details break on every refactor.

Propose specific, actionable test cases for a target module — without writing the actual test code. Use this skill whenever the user wants to know "what should I test", "what test cases would catch real bugs in X", "I have a finding from test-assessment, what tests would close that gap", "suggest tests for this file", or wants to think through coverage before writing. Pairs with the test-assessment skill (which finds gaps); writing the test code itself happens as a normal follow-up task once the suggestions are reviewed. This skill stops at suggestions — if the user wants code generated, redirect them. Trigger even on casual phrasings ("what should I test in auth.ts", "give me test ideas for this module").

Use to compute and monitor regulated complaint deadlines — acknowledgement, holding response, final response — against business-day calendars, and to find cases about to breach. Trigger for "are we meeting our complaint deadlines", "complaint SLA breaches", "final response deadline", "which complaints are about to breach", complaint ageing reports, or building a complaints deadline monitor.

Use to audit whether similar customers with similar failures received similar redress, and to find variation that could not be defended. Trigger for "are our refunds consistent", "do we compensate similar cases the same way", "audit our goodwill decisions", redress fairness review, customers who escalate getting more, or a complaint that someone else was treated better.

Plan, execute, document, and retest authorized security assessments of AI agents and multi-agent workflows using safe adversarial cases, synthetic identities, canaries, and evidence-based findings. Use when defining red-team rules of engagement, assessing prompt injection or excessive agency, testing tool and identity boundaries, evaluating memory or cross-agent attacks, scoring a campaign, or verifying remediation in an approved environment.

This skill should be used when establishing comprehensive QA testing processes for any software project. Use when creating test strategies, writing test cases following Google Testing Standards, executing test plans, tracking bugs with P0-P4 classification, calculating quality metrics, or generating progress reports. Includes autonomous execution capability via master prompts and complete documentation templates for third-party QA team handoffs. Implements OWASP security testing and achieves 90% coverage targets.

Use to analyse touch time vs elapsed time across the resolution path — queue wait, customer wait, back-office wait, and where elapsed time hides real delay. Trigger for "flow efficiency", "touch time vs elapsed time", "where is the time going", "customers waiting on us", back-office bottlenecks, idle time in cases, or end-to-end time much longer than handle time.

Use to discover specific skills for the Sales plugin, when it is at-mentioned directly, or for any mentions of potentially relevant work, including: meeting prep or call follow-up; account research, monitoring, or prioritization; internal source finding; competitive briefs; deal strategy; pipeline or forecast review; company or contact enrichment; customer quote retrieval; rep coaching; business cases; sales company research; and CRM or data enrichment workflows.

Structure software around the Dependency Rule: source code dependencies point inward from frameworks to use cases to entities. Use when the user mentions "architecture layers", "dependency rule", "ports and adapters", "hexagonal architecture", "use case boundary", "onion architecture", "screaming architecture", or "framework independence". Also trigger when decoupling business logic from databases or frameworks, defining module boundaries, or debating where to put business rules. Covers component principles, boundaries, and SOLID. For code quality, see clean-code. For domain modeling, see domain-driven-design.

Use to build a defensible cost per contact and cost to serve by driver, channel or customer segment, for automation business cases and budget decisions. Trigger for "what does a ticket cost us", "cost per contact", "what would automating this save", "cost to serve by segment", building a business case for a bot or a process change, or a savings claim that looks too good.

Eng manager-mode plan review. Lock in the execution plan — architecture, data flow, diagrams, edge cases, test coverage, performance. Walks through issues interactively with opinionated recommendations. Use when asked to "review the architecture", "engineering review", or "lock in the plan". Proactively suggest when the user has a plan or design doc and is about to start coding — to catch architecture issues before implementation. (gstack) Voice triggers (speech-to-text aliases): "tech review", "technical review", "plan engineering review".

Reviews a product document (PRD, spec, design brief) BEFORE implementation to surface holes — undefined edge cases, missing states, policy gaps — by attacking what the document is SILENT about (things unwritten, and things written only for the happy path). Acts as a strict "sign-off manager," ruling Approve / Conditional / Reject and producing a polite, forwardable question list. Works for planners/PMs (self-review before sharing), engineers (blocking questions before coding), and designers (screen states with no mockup). Use whenever the user wants a spec/PRD/plan/brief checked for readiness or gaps, or says "review this spec", "find holes in this PRD", "poke holes in this", "is this plan good to build?", "can I start implementing this?", "what states/edge cases am I missing?", "what should I ask the PM before coding?", "run devil", or pastes/links a planning document and asks whether it's ready to act on. Do NOT use it to: write or draft a new spec, summarize or translate a document, estimate/break down tic

Design structured evaluation rubrics for scoring LLM and agent outputs — defining quality dimensions, scoring scales, hard gates, score descriptions, and edge cases. Load when the user asks to create an eval rubric, define evaluation criteria, design scoring dimensions, write an eval spec, or says "what should I evaluate", "design a rubric", "create eval criteria", "define quality dimensions", "evaluation rubric for", "how do I measure quality of". Sub-skill of eval-output orchestrator.

Builds a new Claude Code skill from scratch through a relentless, evidence-based interview that walks the skill's design tree decision-by-decision — entity fit, use cases, name, description, workflow steps, tools, and progressive-disclosure layout — then reviews the finished skill against the plugin-building guidance and applies every fix it finds. Use when creating, authoring, scaffolding, designing, or drafting a new skill or slash command. Does not build an agent or subagent — use agent-builder. Does not serve, vendor, or refresh the authoring guidance itself — use guidance.

Fully autonomous QA testing agent for Modular RAG MCP Server. Reads test cases from QA_TEST_PLAN.md, executes ALL test types automatically without human intervention — CLI commands, Dashboard UI via Streamlit AppTest headless rendering, MCP protocol via subprocess JSON-RPC, provider switches, and data lifecycle checks. Diagnoses failures, applies fixes with up to 3 retry rounds, and records results in QA_TEST_PROGRESS.md. Use when user says 'run QA', 'QA test', 'QA 测试', '执行测试', '跑测试', 'test and fix', or wants to execute QA test plan.

Fully autonomous QA testing agent for Modular RAG MCP Server. Reads test cases from QA_TEST_PLAN.md, executes ALL test types automatically without human intervention — CLI commands, Dashboard UI via Streamlit AppTest headless rendering, MCP protocol via subprocess JSON-RPC, provider switches, and data lifecycle checks. Diagnoses failures, applies fixes with up to 3 retry rounds, and records results in QA_TEST_PROGRESS.md. Use when user says 'run QA', 'QA test', 'QA 测试', '执行测试', '跑测试', 'test and fix', or wants to execute QA test plan.

Fully autonomous QA testing agent for Modular RAG MCP Server. Reads test cases from QA_TEST_PLAN.md, executes ALL test types automatically without human intervention — CLI commands, Dashboard UI via Streamlit AppTest headless rendering, MCP protocol via subprocess JSON-RPC, provider switches, and data lifecycle checks. Diagnoses failures, applies fixes with up to 3 retry rounds, and records results in QA_TEST_PROGRESS.md. Use when user says 'run QA', 'QA test', 'QA 测试', '执行测试', '跑测试', 'test and fix', or wants to execute QA test plan.

proptest — property-based testing for Rust (Hypothesis-style). Generates thousands of random inputs to find counterexamples to invariants, with shrinking to minimal failing case. Critical for crypto, parsers, state machines, and finance code where edge cases matter. Includes strategies (gen functions), regression tracking, and integration with cargo test. Alternative: quickcheck (simpler API, less powerful). USE WHEN: user mentions "proptest", "property-based test", "proptest!", "Strategy", "Arbitrary", "shrink", "quickcheck", "regression file", "fuzz-light", "proptest-derive" DO NOT USE FOR: Generic Rust unit tests - use `testing/rust-testing` DO NOT USE FOR: Fuzzing with mutator (cargo-fuzz, AFL) - use bitcoin/testing/fuzz DO NOT USE FOR: KMP property testing - use `testing/kotest` (has built-in property)

Remove AI writing patterns from prose. Use this skill when writing, drafting, editing, reviewing, or revising any text to eliminate predictable AI tells, slop, and formulaic patterns. Trigger this skill whenever the user asks to "deslop", "de-AI", "make it sound human," "remove AI patterns," "remove AI tropes," "clean up AI writing," fix "slop," "deslop" text, or review prose for authenticity. Also use when the user asks you to write or draft anything and wants it to sound natural rather than AI-generated. Common use cases include scientific writing (manuscripts, abstracts, cover letters, grant narratives, discussion sections, peer review responses), blog posts, newsletters, memos, reports, and any other substantial prose.

Review code changes for correctness, completeness, bugs, edge cases, and quality. Load when the user explicitly asks to review code, check a PR, review a diff, audit recent changes, or verify an implementation matches requirements. Also triggers on "review this code", "check this PR", "review my changes", "code review", "did this implement correctly", "audit this diff", or any explicit request for a formal code review. Do NOT load for "review changes for context" or "review what happened" — those are requests to read code, not to perform a formal review.

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.

Do NOT invoke this skill as a routine first step. Do NOT invoke when any installed skill (see the available skills list) can handle the task, or when general capabilities (writing, coding, analysis, translation, web search) suffice. Invoke ONLY in two cases: (1) the user explicitly asks to find, install, or browse skills / the skill marketplace; (2) no installed skill fits AND the task very likely needs a dedicated skill to be done well (e.g. a specialized file format, a vertical platform workflow). Searches the official QwenWork marketplace, the skills.sh community library, and enterprise skill markets (if available via MCP).

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.

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.

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.

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.

Universal data-source assistant. Use this skill when the user wants external structured data such as stocks, financial reports, technical indicators, A-share/HK/US markets, global macroeconomics, Chinese enterprise registry information, arXiv papers, Google Scholar results, Chinese laws/regulations and judicial cases, Wind financial data (intraday/minute quotes, funds, bonds), IMF macro datasets (FX rates, CPI, GDP forecasts), Gildata smart screening, US SEC filings (10-K/10-Q, Form 4, 13F), or S&P Capital IQ fundamentals (top holders, consensus estimates, valuation ratios). This plugin exposes tools via MCP server `plugin-pythinker-datasource_data`; call them in the flow `mcp__plugin-pythinker-datasource_data__get_data_source_desc` → `mcp__plugin-pythinker-datasource_data__call_data_source_tool`.

Patent prior-art and landscape intelligence skill — not generic patent help. Commits to one of five sub-use-cases via forcing intake (novelty search / freedom-to-operate / competitive landscape / acquisition diligence / litigation prior-art) before any search runs. Searches Google Patents, Espacenet, USPTO, and optionally Lens.org for citation-graph signals. Output is an editable Word document (.docx) with verdict, ranked closest art (claim-text extracted), CPC-class-aware landscape, family-resolved hits, geographic coverage, FTO flags where applicable, strategy recommendations, and full audit log. Use when the user asks for patent searching or analysis (e.g., 'prior art search for [invention]', 'freedom to operate analysis for [product]'). Produces search signal, not legal advice — always recommends consulting a patent attorney before filing or licensing decisions. Trademark, copyright, and trade-secret questions are out of scope.

Use BEFORE generating, refactoring, reviewing, or debugging code. Trigger phrases include "write a function/script/class for X", "review this code/diff/PR", "refactor this", "debug this error", "is this implementation correct", "what's wrong with this code", "improve this code", "translate from X to Y", or any prompt with a code block the user wants you to act on. Also fires when planning architectural changes, picking algorithms or data structures, or evaluating dependency upgrades. Calls the code MCP tool to retrieve an engineering scaffold (failure pattern, procedure, correct-pattern example, verification step) before generating. Catches hallucinated APIs, lost edge cases, premature algorithm commitment, silent contract violations, refactors that change behavior masked by passing tests. Do NOT trigger for pure code reading with no action requested, simple syntax questions, file...

Brand-first landing page designer — interviews the user to discover brand identity (adjectives, colors, typography, shape language), then generates and iterates on a polished landing page via Stitch with deployment-ready HTML output. Preferred over frontend-design for standalone landing/marketing pages where the user hasn't established visual direction yet. TRIGGER when: user asks to "create/design/build a landing page", "make a homepage for my project/product/service", "build a marketing page", or wants to promote an app/side project. Especially when they haven't defined brand colors, fonts, or visual style — the guided brand interview is the core value. DO NOT TRIGGER when: user has a specific design mockup to implement, wants a dashboard or app UI, needs component-level frontend work (buttons, forms, navbars), is building a multi-page application, or is restyling an existing page with known design tokens. Use frontend-design for those cases.