Results for “flow”

This skill should be used when working with LaminDB, an open-source data framework for biology that makes data queryable, traceable, reproducible, and FAIR. Use when managing biological datasets (scRNA-seq, spatial, flow cytometry, etc.), tracking computational workflows, curating and validating data with biological ontologies, building data lakehouses, or ensuring data lineage and reproducibility in biological research. Covers data management, annotation, ontologies (genes, cell types, diseases, tissues), schema validation, integrations with workflow managers (Nextflow, Snakemake) and MLOps platforms (W&B, MLflow), and deployment strategies.

This skill should be used when working with LaminDB, an open-source data framework for biology that makes data queryable, traceable, reproducible, and FAIR. Use when managing biological datasets (scRNA-seq, spatial, flow cytometry, etc.), tracking computational workflows, curating and validating data with biological ontologies, building data lakehouses, or ensuring data lineage and reproducibility in biological research. Covers data management, annotation, ontologies (genes, cell types, diseases, tissues), schema validation, integrations with workflow managers (Nextflow, Snakemake) and MLOps platforms (W&B, MLflow), and deployment strategies.

Audit websites and landing pages for conversion issues and design evidence-based A/B tests. Use when the user mentions "landing page isnt converting", "conversion rate", "A/B test", "why visitors leave", "objection handling", "bounce rate", "split testing", or "conversion funnel". Also trigger when diagnosing why signups are low, designing experiment hypotheses, or auditing checkout flows for friction points. Covers funnel mapping, persuasion assets, and objection/counter-objection frameworks. For overall marketing strategy, see one-page-marketing. For usability issues, see ux-heuristics.

UI/UX design intelligence and implementation guidance for building polished interfaces. Use when the user asks for UI design, UX flows, information architecture, visual style direction, design systems/tokens, component specs, copy/microcopy, accessibility, or to generate/critique/refine frontend UI (HTML/CSS/JS, React, Next.js, Vue, Svelte, Tailwind). Includes workflows for (1) generating new UI layouts and styling, (2) improving existing UI/UX, (3) producing design-system tokens and component guidelines, and (4) turning UX recommendations into concrete code changes.

This skill should be used when working with LaminDB, an open-source data framework for biology that makes data queryable, traceable, reproducible, and FAIR. Use when managing biological datasets (scRNA-seq, spatial, flow cytometry, etc.), tracking computational workflows, curating and validating data with biological ontologies, building data lakehouses, or ensuring data lineage and reproducibility in biological research. Covers data management, annotation, ontologies (genes, cell types, diseases, tissues), schema validation, integrations with workflow managers (Nextflow, Snakemake) and MLOps platforms (W&B, MLflow), and deployment strategies.

This skill should be used when working with LaminDB, an open-source data framework for biology that makes data queryable, traceable, reproducible, and FAIR. Use when managing biological datasets (scRNA-seq, spatial, flow cytometry, etc.), tracking computational workflows, curating and validating data with biological ontologies, building data lakehouses, or ensuring data lineage and reproducibility in biological research. Covers data management, annotation, ontologies (genes, cell types, diseases, tissues), schema validation, integrations with workflow managers (Nextflow, Snakemake) and MLOps platforms (W&B, MLflow), and deployment strategies.

Walk through the manual-capture.md checklist for a slug, driving Chrome via the Claude in Chrome MCP to capture each visual that needs more than a static URL — multi-step flows, conversation states, settings panels, age gates on third-party sites. Runs equally well locally (your desktop Chrome) or on a VPS with always-on Chrome + the extension installed. Defaults to unattended mode when `BLOG_AGENT_AUTONOMOUS=1` (which forces `UNATTENDED=1`). Use after /generate-visuals has flagged action-shot or failed-screenshot entries.

Expert knowledge for Azure Logic Apps development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when building Logic Apps with SAP/IBM/FTP connectors, B2B/EDI flows, AI/OpenAI calls, XML/JSON transforms, or DevOps CI/CD, and other Azure Logic Apps related development tasks. Not for Azure Functions (use azure-functions), Azure API Management (use azure-api-management), Azure Service Bus (use azure-service-bus), Azure Event Grid (use azure-event-grid).

Use when a project's visual foundation — typography scale, color palette, spacing — needs establishing as canonical design tokens; the target has no design system yet (the 0→1 case), the A-Team design phase needs tokens for the lofi and the spec's design-system mapping, or a human runs the token flow standalone ("set up the design system", "pick fonts and colors", "define design tokens"). In the A-Team pipeline it is conducted by ateam-design in pipeline mode — no interview; inputs derive from context.md's

Lazyweb is the design-evidence skill for AI coding agents. Use it when designing, critiquing, or changing product UI — it provides real app screenshots, competitor references, best practices, quick examples, creative cross-category ideas, paywall optimization guidance, and mobile growth + monetization A/B test context. Routes to the right Lazyweb mode (design workflow, quick search, update, flowchart, or A/B test research) using MCP tools and the Lazyweb server at https://www.lazyweb.com/mcp. Use before designing any screen when you need design evidence instead of training-data vibes.

When the user wants to optimize post-signup onboarding, user activation, first-run experience, or time-to-value. Also use when the user mentions "onboarding flow," "activation rate," "user activation," "first-run experience," "empty states," "onboarding checklist," "aha moment," "new user experience," "users aren't activating," "nobody completes setup," "low activation rate," "users sign up but don't use the product," "time to value," or "first session experience." Use this whenever users are signing up but not sticking around. For signup/registration optimization, see signup. For ongoing email sequences, see emails.

When the user wants to optimize post-signup onboarding, user activation, first-run experience, or time-to-value. Also use when the user mentions "onboarding flow," "activation rate," "user activation," "first-run experience," "empty states," "onboarding checklist," "aha moment," "new user experience," "users aren't activating," "nobody completes setup," "low activation rate," "users sign up but don't use the product," "time to value," or "first session experience." Use this whenever users are signing up but not sticking around. For signup/registration optimization, see signup. For ongoing email sequences, see emails.

Analytics tracking, interpretation, funnel analysis, product metrics, and ROI measurement. Use when setting up GA4/GTM tracking, interpreting analytics data, analyzing conversion funnels, calculating ROI, or measuring product engagement. Triggers on "analytics," "GA4," "Google Analytics," "conversion tracking," "event tracking," "UTM parameters," "tag manager," "GTM," "tracking plan," "funnel analysis," "conversion rates," "user flow," "cohort analysis," "retention," "product metrics," "North Star metric," "ROI," "break-even," "payback period," "investment analysis," "validate my funnel," "why isn't my funnel converting," or "executive financial report." For A/B test setup, see ab-test-setup.

Generates NeMo Guardrails Colang (.co) files and YAML config blocks from a plain-language description of a chatbot's purpose, allowed behaviors, and constraints. Use this skill whenever a user wants to build guardrails for a chatbot, define allowed intents for an LLM, create an AI firewall with NeMo Guardrails, generate Colang flow definitions, or configure a semantic allow-list for a bot. Trigger this skill even when the user just describes what their bot should and shouldn't do — generating the Colang and YAML is almost always what they need next.

Production pipeline for interactive and generative visual art using p5.js. Creates browser-based sketches, generative art, data visualizations, interactive experiences, 3D scenes, audio-reactive visuals, and motion graphics — exported as HTML, PNG, GIF, MP4, or SVG. Covers: 2D/3D rendering, noise and particle systems, flow fields, shaders (GLSL), pixel manipulation, kinetic typography, WebGL scenes, audio analysis, mouse/keyboard interaction, and headless high-res export. Use when users request: p5.js sketches, creative coding, generative art, interactive visualizations, canvas animations, browser-based visual art, data viz, shader effects, or any p5.js project.

Production pipeline for interactive and generative visual art using p5.js. Creates browser-based sketches, generative art, data visualizations, interactive experiences, 3D scenes, audio-reactive visuals, and motion graphics — exported as HTML, PNG, GIF, MP4, or SVG. Covers: 2D/3D rendering, noise and particle systems, flow fields, shaders (GLSL), pixel manipulation, kinetic typography, WebGL scenes, audio analysis, mouse/keyboard interaction, and headless high-res export. Use when users request: p5.js sketches, creative coding, generative art, interactive visualizations, canvas animations, browser-based visual art, data viz, shader effects, or any p5.js project.

When the user wants to plan, build, or optimize SMS or MMS marketing — including welcome flows, abandoned cart texts, post-purchase, win-back, promotional sends, or transactional/auth SMS. Also use when the user mentions "SMS marketing," "text message campaigns," "SMS sequence," "SMS automation," "abandoned cart text," "post-purchase SMS," "Klaviyo SMS," "Postscript," "Attentive," "Twilio," "A2P 10DLC," "TCPA," "SMS compliance," "short code," "toll-free SMS," "MMS campaign," "should I do SMS," or "SMS vs email." For email sequences, see emails. For SMS copy framing, see copywriting. For opt-in popups that capture phone numbers, see popups.

Live developer experience audit. Uses the browse tool to actually TEST the developer experience: navigates docs, tries the getting started flow, times TTHW, screenshots error messages, evaluates CLI help text. Produces a DX scorecard with evidence. Compares against /plan-devex-review scores if they exist (the boomerang: plan said 3 minutes, reality says 8). Use when asked to "test the DX", "DX audit", "developer experience test", or "try the onboarding". Proactively suggest after shipping a developer-facing feature. (gstack) Voice triggers (speech-to-text aliases): "dx audit", "test the developer experience", "try the onboarding", "developer experience test".

Use when the user wants to clone or adapt a UI pattern from any website into gotcontext.ai, or asks to "build something like X", "make our nav look like Y", or "clone that component". Prefer aura.build Pro when available; without a Pro subscription, skip Aura and go straight to Phase 2.5 direct rebuild. Aura's clone is now NATIVE — paste a URL or drag a screenshot into aura.build and it generates React/Tailwind directly; the Anima/Chrome-extension flow is only a fallback for login-gated pages Aura can't fetch server-side.

When the user wants to optimize, improve, or increase conversions on any marketing page or form — including homepage, landing pages, pricing pages, feature pages, lead capture forms, or contact forms. Also use when the user says 'CRO,' 'conversion rate optimization,' 'this page isn't converting,' 'improve conversions,' 'why isn't this page working,' 'my landing page sucks,' 'form abandonment,' 'nobody's converting,' 'low conversion rate,' or 'this page needs work.' Use this even if the user just shares a URL and asks for feedback. For signup/registration flows, see signup. For post-signup activation, see onboarding. For popups/modals, see popups.

When the user wants to optimize, improve, or increase conversions on any marketing page or form — including homepage, landing pages, pricing pages, feature pages, lead capture forms, or contact forms. Also use when the user says 'CRO,' 'conversion rate optimization,' 'this page isn't converting,' 'improve conversions,' 'why isn't this page working,' 'my landing page sucks,' 'form abandonment,' 'nobody's converting,' 'low conversion rate,' or 'this page needs work.' Use this even if the user just shares a URL and asks for feedback. For signup/registration flows, see signup. For post-signup activation, see onboarding. For popups/modals, see popups.

Kotest — flexible, idiomatic Kotlin testing framework. Multiple specification styles (StringSpec, FunSpec, BehaviorSpec, DescribeSpec, FeatureSpec, FreeSpec), rich matcher library, property-based testing, data-driven tests, coroutine support, KMP-friendly. Drop-in alternative or complement to JUnit. USE WHEN: user mentions "Kotest", "io.kotest", "shouldBe", "StringSpec", "BehaviorSpec", "DescribeSpec", "kotest property testing", "Arb.list", "forAll", "kotest matchers", "kotlin tests" DO NOT USE FOR: JUnit-specific patterns - use junit skill (or framework-specific test skills) DO NOT USE FOR: Flow testing - use `testing/turbine` DO NOT USE FOR: Compose snapshot tests - use `testing/compose-snapshot` DO NOT USE FOR: Mobile E2E - use `testing/maestro`

Requires python3, and AISA_API_KEY. Uses the supplied AISA_API_KEY to send requests to https://api.aisa.one. Native-first ClawHub plugin for `media-gen`. Ships the packaged AIsa skill with an `openclaw.plugin.json` manifest and a Claude-compatible bundle fallback. Generate images and videos with AIsa. Supports Gemini, Wan, and Seedream image generation plus Wan text-to-video and image-to-video models. One API key; the bundled client routes each model to the correct endpoint automatically. Use when: you need a neutral AIsa media-generation skill that spans multiple model families without changing credentials or request flow.

Guardian Angel gives AI agents a moral conscience rooted in Thomistic virtue ethics. Rather than relying solely on rule lists, it cultivates stable virtuous dispositions— prudence, justice, fortitude, temperance—that guide every interaction. The foundation is caritas: willing the good of the person you serve. From this flow the cardinal virtues as practical habits of right action and sound judgment. v3.0 introduced virtue-based disposition as the primary evaluation layer, providing deeper coherence than checklists alone. The agent's character becomes the safeguard. v3.1 adds: Plugin enforcement layer with before_tool_call hooks, approval workflows for ambiguous cases, and protections for sensitive infrastructure actions.

Expert CMMC 2.0 (Cybersecurity Maturity Model Certification) advisor for US defense contractors and subcontractors in the Defense Industrial Base (DIB). Use this skill whenever a user asks about CMMC 2.0, CMMC Level 1, Level 2, or Level 3, DoD cybersecurity compliance, NIST SP 800-171, CUI (Controlled Unclassified Information) protection, System Security Plan (SSP), Plan of Action & Milestones (POA&M), C3PAO assessments, DIBCAC audits, self-assessment, SPRS score, or any requirement under DFARS 252.204-7012 or 7021. Also trigger for: "CMMC gap analysis", "CMMC readiness", "FCI protection", "CUI scoping", "CMMC practices", "DoD contract cybersecurity", "defense supply chain security", or "prime contractor flow-down requirements".

Audits codebases for common security vulnerabilities that AI coding assistants introduce in "vibe-coded" applications. Checks for exposed API keys, broken access control (Supabase RLS, Firebase rules), missing auth validation, client-side trust issues, insecure payment flows, and more. Use this skill whenever the user asks about security, wants a code review, mentions "vibe coding", or when you're writing or reviewing code that handles authentication, payments, database access, API keys, secrets, or user data — even if they don't explicitly mention security. Also trigger when the user says things like "is this safe?", "check my code", "audit this", "review for vulnerabilities", or "can someone hack this?".

Complete shadcn/ui component management for adding, searching, fixing, styling, and composing UI in any React project. Use this skill whenever the user mentions shadcn, shadcn/ui, adding UI components, building forms or dashboards with Radix, working with component registries (@shadcn, @magicui, @tailark), or any task involving npx shadcn CLI commands. Also trigger when the user asks to fix styling issues, build a settings page, dashboard, or modal flow in a project that uses shadcn/ui — even if they don't say "shadcn" explicitly. This skill manages the full component lifecycle: search, add, view, diff, smart-merge upstream updates, and enforce critical rules for forms, composition, styling, and icons.

Maestro — declarative E2E mobile UI testing framework by mobile.dev. YAML-based flow files, single tool for Android + iOS (and Compose Multiplatform / Flutter / React Native). Built-in cloud runner, recording mode, JS scripting for complex assertions, screen state diffing, no flakiness from explicit waits. USE WHEN: user mentions "Maestro", "maestro test", "mobile E2E", "cross-platform UI test", "maestro studio", "mobile.dev cloud", ".maestro" folder, "launchApp" YAML DO NOT USE FOR: web E2E - use `testing/playwright` DO NOT USE FOR: unit tests - use `testing/kotest`, `testing/vitest`, etc. DO NOT USE FOR: instrumented Android tests - use Espresso/Compose Test DO NOT USE FOR: snapshot tests - use `testing/compose-snapshot`

Performs deep architectural analysis of a specified module, directory, or feature area by examining structural coupling, data flow, concurrency patterns, risk, and SOLID alignment. Use when the user wants to assess, evaluate, or review the architecture, design quality, dependency structure, coupling, cohesion, or technical debt of an existing part of the codebase. Not for investigating specific bugs, runtime errors, or failures — use investigate. Not for test planning — use automated-test-planning. Not for file-level code review — use code-review. Not for researching open-ended options, prior art, or how something works — use research. Not for designing a new interface or contract — use design-an-api. Not for writing documentation or architectural decision records.

Use Orca orchestration for structured multi-agent coordination: threaded messages, blocking ask/reply flows, task dispatch, worker_done/escalation waits, task DAGs, decision gates, coordinator loops, or decomposing work across agents. Use `orca-cli` instead for full ownership handoffs, including requests phrased as "hand off", "handoff", "handover", "give this to another agent", or "another worktree" when the user did not explicitly ask to supervise, monitor, wait for results, or coordinate a DAG. Use `orca-cli` for ordinary terminal control, lightweight terminal prompts, shell commands, Orca worktree management, reading or waiting on terminals, and automation of the browser embedded inside Orca. Use Computer Use for browser windows, webviews, Orca app UI, or desktop UI outside Orca's embedded browser.

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`.

Specjalistyczna wiedza o WŁASNOŚCIOWYM formacie plików form.xml platformy Soneta (enova365) — bez tego skilla Claude generuje błędne XML z nieistniejącymi elementami. ZAWSZE używaj tego skilla gdy użytkownik: (1) prosi o utworzenie lub modyfikację pliku pageform.xml, viewform.xml, form.xml, lookupform.xml lub gridform.xml dla platformy Soneta (enova365); (2) pyta o elementy DataForm, Page, Group, Grid, Field, Row, Stack, Flow, Command, Include, Appearance, GroupBy w Soneta; (3) pyta o składnię EditValue, DataContext, Visibility, RowCondition, Renderable, CaptionHtml, Footer, Class lub układ UI formularzy Soneta; (4) pokazuje istniejący plik form.xml/pageform.xml/viewform.xml i pyta o jego strukturę lub chce go rozszerzyć; (5) pyta o warunkową widoczność, formatowanie warunkowe (Appearance), bindowanie danych lub wzorce UI w Soneta/enova365.

Expert 3D modeling specialist with deep knowledge of topology, UV mapping, game-ready and film-ready pipelines, DCC tool workflows (Blender, Maya, ZBrush, 3ds Max, Houdini), retopology, LOD systems, and export pipelines. This skill represents years of production experience distilled into actionable guidance. Use when "3d model, 3d modeling, mesh topology, uv unwrap, uv mapping, retopology, retopo, low poly, high poly, subdivision, subdiv, edge flow, edge loops, polygon modeling, box modeling, hard surface, organic modeling, sculpting, zbrush, blender modeling, maya modeling, 3ds max, LOD, level of detail, game ready mesh, film ready, baking normals, high to low, fbx export, gltf export, texel density, 3d, modeling, topology, uv, game-dev, vfx, blender, maya, zbrush, retopology, lod, hard-surface, organic, sculpting" mentioned.

Drive Graphify from its CLI to build, refresh, query, export, and serve a durable code/corpus knowledge graph. Use when the user wants `.graphify/GRAPH_REPORT.md`, `graph.json`, `graph.html`, `graphify update`/`summary`/`query`/`path`/`explain`/`tree`, change-aware review context, git-hook or watch-based refresh, a stdio MCP graph server, or an install into jeo, jeopi, gjc, opencode, Claude, Codex, or Gemini. Also covers the honest structural fallback when native extraction is empty or misleading. Route simple locate/reference work to `codebase-search`, narrative knowledge-base work to `llm-wiki`, and project-memory handoff to `opencontext`. Triggers on: graphify, graphify update, graphify query, knowledge graph CLI, GRAPH_REPORT.md, graph.json, codebase graph, graph refresh, graphify install, graphify serve, review context, affected flows.

Generate user-friendly "Explain Like I'm 5" feature documentation for end users by reading the codebase. Use this skill whenever the user wants to document a feature for non-technical users, write help docs, create an explainer for a feature in their app, produce onboarding content, or asks "make a user doc for X". Trigger on phrasings like "ELI5 the closeout flow", "write user docs for the kanban view", "explain this feature to a customer", "make a help article for X", "document this for end users". Also known as "E-features-LI5". This skill produces plain-language docs written for someone with the app open trying to get something done — not internal developer docs (use the `teach` skill for those) and not feature announcements.

Expert GDPR compliance assistant covering all four core workflows: (1) auditing code and systems for GDPR violations, (2) drafting GDPR-compliant documents such as privacy policies, Data Processing Agreements (DPAs), and consent notices, (3) answering GDPR compliance questions with authoritative article citations, and (4) reviewing data flows and PII handling practices. Use this skill whenever the user mentions GDPR, data protection, privacy compliance, lawful basis, data subject rights, DPA, privacy notices, consent management, data breaches, DPIAs, controller/ processor relationships, cross-border data transfers, or any EU/UK data privacy topic. Also trigger for questions like "is this GDPR compliant?", "how do I handle personal data?", "what does a privacy policy need?", or any request involving PII, personal data, or data retention in a regulatory context.