「annotations」の検索結果

Wireframe a screen — text/ASCII by default, or hand-drawn HTML when the user says "sketch", "hand-drawn", "lo-fi HTML", "whiteboard", "graph paper", or "visual wireframe". Text mode produces a buildable ASCII spec Form and Prism can act on. HTML mode produces a single self-contained file with graph-paper background, marker headlines, sticky-note annotations, and hatched chart placeholders — looks like a designer's whiteboard, commits to nothing.

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Add caching to Datagrok functions using meta.cache annotations

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Auto-selects and enforces the strongest valid Python typing lane for the detected Python version and dependencies — no user input required. Use when adding or tightening type annotations, eliminating Any usage in internal code, designing boundary validators or parsers, choosing between stdlib typing (TypedDict, Protocol, dataclasses), Pydantic models, or Hypothesis property tests, addressing ty or mypy failures, or applying version-specific features (TypeIs, ReadOnly, PEP 695 generics, PEP 649 deferred evaluation). Enforces boundary isolation — raw payloads validated immediately at ingress and returned as typed internal objects.

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Routes a Superpowers plan file through the /work-backlog-item pipeline and writes SAM task back-references and chunk annotations into the original plan. Use when given a path to a Superpowers plan file via $ARGUMENTS and needing to create a linked backlog item plus SAM task plan.

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Same reverse-thinking method as dh:rt-ica (see dh:rt-ica or dh-glossary for the definition), but localizes any MISSING input to the affected task only, as a non-blocking information-completeness pre-pass before task decomposition and plan generation. Use when grooming backlog items, generating plans, decomposing tasks under uncertainty, or working in brownfield and refactor scenarios. Produces completeness summary (APPROVED-FOR-PLANNING, APPROVED-WITH-GAPS, or BLOCKED-FOR-PLANNING), missing input report with dependency mapping, required unblock actions, and planning annotations for downstream tasks. Use dh:rt-ica instead at the S2 implementation gate where missing inputs must halt execution.

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This skill should be used when the user asks to "fix mypy errors", "add type annotations", "fix type checking", "resolve no-untyped-def", "fix mypy type errors", or when working with type hints while respecting StreamFlow's forbidden type constraints (no Any, dict[str, Any], etc.).

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。

Work with a Grafana instance — search and read dashboards, run datasource queries (Prometheus, Loki, PostgreSQL, etc.), inspect alert rules and silences, post annotations, and manage folders. Use this whenever the user mentions a Grafana dashboard, panel, or alert; pastes a Grafana URL; asks "what does this dashboard show", "query this metric in Grafana", "is this alert firing", "silence this alert", or wants to create/export a dashboard — even if they don't say "API". Always start from this skill when interacting with this service — its bundled scripts and recipes are the fastest path.

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Manages ArgoCD application sync waves and hooks using the ArgoCD API and argocd CLI. Coordinates multi-application deployment ordering with sync-wave annotations, health checks, and progressive rollout gates.

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Use when writing Playwright tests, fixing flaky tests, debugging failures, implementing Page Object Model, configuring CI/CD, optimizing performance, mocking APIs, handling authentication or OAuth, testing accessibility (axe-core), file uploads/downloads, date/time mocking, WebSockets, geolocation, permissions, multi-tab/popup flows, mobile/responsive layouts, touch gestures, GraphQL, error handling, offline mode, multi-user collaboration, third-party services (payments, email verification), console error monitoring, global setup/teardown, test annotations (skip, fixme, slow), test tags (@smoke, @fast, @critical, filtering with --grep), project dependencies, security testing (XSS, CSRF, auth), performance budgets (Web Vitals, Lighthouse), iframes, component testing, canvas/WebGL, service workers/PWA, test coverage, i18n/localization, Electron apps, or browser extension testing. Covers E2E, component, API, visual, accessibility, security, Electron, and extension testing.

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Specifies standards for RestController classes, including API route mappings, HTTP method annotations, dependency injection, and error handling with ApiResponse and GlobalExceptionHandler.

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Guide developers in creating Model Context Protocol (MCP) servers. Use for building MCP tools that enable LLMs to interact with external services. Covers TypeScript (primary) and Python FastMCP (secondary), tool annotations, Zod/Pydantic validation, and evaluation question creation.

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Analyze an arbitrary codebase to auto-detect workflows, data pipelines, and file dependencies using putior's put_auto() engine. Produces an annotation plan that maps detected I/O patterns to source files across 30+ supported languages with 902 auto-detection patterns. Use when onboarding onto an unfamiliar codebase to understand data flow, starting putior integration in a project without existing annotations, auditing a project's data pipeline before documentation, or preparing an annotation plan before running annotate-source-files.

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Create production-ready Grafana dashboards with reusable panels, template variables, annotations, and provisioning for version-controlled dashboard deployment. Use when creating visual representations of Prometheus, Loki, or other data source metrics, building operational dashboards for SRE teams, migrating from manual dashboard creation to version-controlled provisioning, or establishing executive-level SLO compliance reporting.

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Spring Data JPA entity design, repository patterns, query methods, JPQL, Flyway/Liquibase migrations, and N+1 avoidance. Apply on Spring Boot projects with spring-boot-starter-data-jpa. Pairs with spring-boot-plugin:spring-conventions and java-foundation:java-conventions. Use this skill to: - Design JPA entities with proper annotations, ID strategy, and lazy loading. - Write JpaRepository interfaces with derived query methods and JPQL @Query. - Avoid N+1 queries using @EntityGraph or JOIN FETCH. - Manage schema evolution with Flyway or Liquibase. - Project query results with Spring Data Projections and DTOs. Do NOT use this skill for: - Service or controller patterns — see spring-boot-plugin:spring-conventions. - Build tool setup — see java-foundation:build-tooling. - Test slices (@DataJpaTest) — see java-foundation:jvm-testing.

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。

Modern Java idioms for any JVM project (Java 17+): records, sealed types, text blocks, pattern matching, Optional discipline, streams, immutability, null safety, package layout, var usage, and code organisation. Apply when the project is a Java 17+ project. Stack-agnostic — referenced by every Java plugin in the marketplace. Use this skill to: - Write self-documenting, immutable-by-default value types with records. - Model closed type hierarchies with sealed classes and interfaces. - Handle optionality explicitly with Optional instead of returning null. - Write expressive pipelines with Stream API without performance footguns. - Lay out packages consistently (feature-first or layer-first) and keep class responsibilities tight. Do NOT use this skill for: - Framework-specific idioms (Spring annotations, JPA mappings — those live in framework plugin skills). - Build tooling (Maven/Gradle) — see java-foundation:build-tooling. - Testing patterns — see java-foundation:jvm-testing.

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。

Framework-agnostic SQLAlchemy 2.0 core shared by fastapi-plugin and flask-plugin: declarative mapped classes with Mapped/mapped_column, column type selection, relationships with explicit lazy loading and cascades, 2.0-style select() querying, transaction/flush discipline, and Alembic-agnostic migration metadata rules. Framework plugins layer their delta skills (async sessions for FastAPI, Flask-SQLAlchemy integration for Flask) on top of this skill. Use this skill to: - Write SQLAlchemy 2.0 declarative models with Mapped[T] annotations and mapped_column(). - Pick correct column types (String(N), Numeric, DateTime(timezone=True), Uuid, Enum). - Define relationships with explicit lazy loading strategy and cascade settings. - Query with 2.0-style select() statements and manage flush vs commit boundaries. - Keep model metadata visible to Alembic autogenerate. Do NOT use this skill for: - FastAPI async engine/session lifecycle — see fastapi-plugin:sqlalchemy-patterns. - Flask-SQLAlchemy extension setup and Flask-Migrate — see flask-plugin:sqlalchemy-patterns. - Python idioms — see python-foundation:python-conventions.

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ASP.NET Core web framework conventions: Minimal API vs MVC controllers, Program.cs composition, DI lifetimes (Scoped/Singleton/Transient), Options pattern with IOptions<T>, middleware ordering (HTTPS redirect → routing → authentication → authorization), model binding and validation (FluentValidation / DataAnnotations), ProblemDetails error handling, structured logging with ILogger<T>, configuration layering (appsettings.json + environment variables + User Secrets), and health checks. Works alongside csharp-foundation:csharp-conventions and aspnet-core-plugin:efcore-patterns. Use this skill to: - Compose Program.cs correctly — register services, configure middleware in the right order, map endpoints. - Apply the Options pattern to avoid passing raw IConfiguration into services. - Write Minimal API endpoint groups with typed results and authorization. - Handle cross-cutting errors uniformly with ProblemDetails. - Configure structured logging and health checks for production readiness. Do NOT use this skill for: - EF Core entity configuration and migrations — see aspnet-core-plugin:efcore-patterns. - C# language idioms — see csharp-foundation:csharp-conventions. - Testing — see csharp-foundation:dotnet-testing.

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Reorganize label-heavy or netlist-like electronic schematics into human-readable functional diagrams with visible local wiring while preserving proven connectivity. Use for schematic readability correction, overlapping wires or symbols, visually floating connectors or support logic, functional-sheet restructuring, bus presentation, layout annotations, or multi-EDA handoff across KiCad, Altium, EasyEDA, EAGLE/Fusion, gEDA/Lepton, SPICE/netlist, and PDF/image sources.

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。

Design data models with Pydantic schemas, comprehensive validation rules, type annotations, and relationship mappings.

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Use when designing, redrawing, or validating research-paper figures and tables, including Matplotlib plots, LaTeX tables, benchmarks, captions, legends, annotations, color, and typography. Preserves exact evidence and checks rendered PDFs for clipping, overlap, and readability.

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Use this agent when you need to systematically review existing GO annotations for a gene and make curation decisions based on literature evidence and functional analysis. This agent should be called after seeding the SPECIES/GENE/GENE-ai-review.yaml file, which seeds each annotation with `action: PENDING`; these should all be manually reviewed.

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Use this agent when you need to synthesize and distill the core functions of a gene from multiple information sources (textual summaries, reviewed annotations, bioinformatics analysis) and populate the `core_functions` section of a gene review YAML file. This agent should be called after completing the gene research, annotation review, and bioinformatics analysis phases of a gene review project.

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Review computational protein or gene function predictions and fill PredictionReview YAML files using the COR/CNN/LSP/UNC/PLI/NPI/REP biological-validity taxonomy. Use for ProtNLM, DeepECTF, BioReason/GO-GPT, InterPro2GO, PANTHER/IBA, CLEAN, GloEC, MAPred, ProteinInfer, or other predicted EC/GO annotations, including audits of the evidence and reasoning in existing prediction reviews.

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Review the retained annotation candidate queue and curate per-coin editorial history. Use weekly during active event periods, monthly otherwise, or on queue-health warnings; this does not restore the retired live chart overlay.

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。