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Found 1,438 Skills
Use ShadTimePicker and ShadTimePickerFormField for time selection; trailing widget, period variant. Use when adding time pickers or time form fields in a Flutter shadcn_ui app or ShadForm.
Replay a recorded session trajectory against the same URL or a mutated variant; uses browser-selectors embedding similarity to recover from DOM drift
Systematic documentation authoring workflow for AI coding agents. Analyzes repositories to determine what documentation is needed, classifies each document by Diataxis type (tutorial, how-to, reference, explanation), and generates accurate, maintainable documentation that stays synchronized with the codebase. Handles greenfield projects (no docs exist), brownfield updates (refresh, enhance, rewrite existing docs), and doc audits with workflow-specific guidance for each. Use when the user requests documentation for a project: README creation, API reference, architecture docs, developer guides, changelogs, or any technical writing tied to a codebase. Also use when existing docs need auditing, updating, rewriting, or restructuring. Triggers on phrases like "write a README", "document this project", "API reference", "architecture doc", "developer guide", "getting started guide", "tutorial", "how-to", "audit our docs", "what docs are missing", "refresh the docs", "Diataxis", "doc the public API", "write a CHANGELOG", "explain this codebase", "onboarding doc", or "ADR". Triggers when creating or editing `README.md`, `CONTRIBUTING.md`, `CHANGELOG.md`, `docs/`, `mkdocs.yml`, `docusaurus.config.*`, `sphinx`/`conf.py`, ADRs, or any markdown file paired with code. Triggers when public APIs, CLI flags, configuration options, or environment variables change and the user wants the docs kept in sync. Do NOT use for standalone prose, marketing copy, blog posts, design documents, RFCs unrelated to a codebase, or documents where the source of truth is not source code.
Flux GitOps patterns for the homelab Kubernetes platform using ResourceSets. Use when: (1) Adding new Helm releases or applications to the platform, (2) Deploying a new service to Kubernetes, (3) Debugging Flux reconciliation issues or sync problems, (4) Understanding ResourceSet patterns, (5) Configuring Kustomizations and variable substitution, (6) Questions about helm-charts.yaml or platform structure, (7) GitOps workflow questions. Triggers: "add helm release", "deploy to kubernetes", "add new service", "add application", "flux resourceset", "flux reconciliation", "flux not syncing", "flux stuck", "gitops", "helm-charts.yaml", "platform values", "flux debug", "HelmRelease not ready", "kustomization", "helmrelease", "add chart", "deploy helm chart"
Quantify realized risk from historical data using volatility estimators, drawdown analysis, and downside risk metrics. Use when the user asks about historical volatility, maximum drawdown, drawdown duration, historical VaR, downside deviation, semi-variance, or tracking error. Also trigger when users mention 'how risky has this been', 'worst decline', 'Parkinson estimator', 'Yang-Zhang', 'peak-to-trough loss', 'recovery time', 'annualized volatility', or ask how to measure past investment risk.
Evaluate verified findings from merge-ready, Greptile, pull-request, CI, security, billing, and other code reviews, then promote durable review gaps into the version-controlled .greptile configuration. Use when a review uncovers a recurring or high-risk repository invariant that Greptile does not capture, when Greptile repeatedly produces a false positive, or when asked to audit or update OpenSEO's Greptile rules and context.
Create WhatsApp message templates, submit for Meta approval, and send template messages with variables.
Visualize relationships between two variables. Use for correlation analysis and pattern identification.
Help a CS or AI PhD student design hypothesis-driven experiments with baselines, variables, metrics, controls, logging, and stop conditions. Use this skill whenever the user is about to run experiments, compare models, plan an ablation, debug inconclusive results, prepare an experiment section, or wants to avoid changing too many things at once.
Cross-format content adaptation. Turning one substantial piece into many derivative formats (blog series, email sequences, social posts, webinars, podcasts, video shorts) without losing the original's value or producing AI-slop variants. The discipline of adaptation per medium rather than mass-blast distribution. Triggers on content repurposing, content adaptation, cross-format content, content atomization, content multiplication, content distribution across formats, source-piece-to-derivative, video shorts from blog, email from whitepaper, podcast from article, blog series from research. Also triggers when a flagship piece is shipping but the team has not planned how to extend it across formats, when repurposing is happening but the derivatives feel mass-produced, or when AI-assisted repurposing is producing slop variants of strong source pieces.
Add and configure Contentful in an existing Next.js project. Covers installing the JavaScript SDK, configuring environment variables, creating production and preview-aware clients, fetching content in App Router or Pages Router, and wiring Draft Mode preview flows. Use when users ask to integrate Contentful with Next.js, fetch entries, set up preview or draft content, or configure the Contentful client. Also triggers on "Contentful SDK Next.js", "contentful.js", "fetch Contentful entries", "get content from Contentful", "Contentful preview", "preview mode", "Contentful environment variables", "Contentful client setup", "create Contentful client", "Pages Router Contentful", "getStaticProps Contentful", "Server Components Contentful", "revalidate Contentful", "ISR Contentful". Not for personalization or Experiences SDK setup (contentful-personalization). Not for non-Next.js frameworks (contentful-guide can route to platform docs).
Create factory fixture patterns for customizable test setup with variations. Use when building reusable test fixtures with multiple configurations, creating parameterizable mocks, or implementing test data builders. Works with pytest fixtures, mock objects, and test utilities. Enables DRY test setup while maintaining flexibility for edge cases.