「annotations」の検索結果

Query Metabolomics Workbench REST API (4,200+ NIH studies) for metabolite ID, study discovery, RefMet standardization, m/z precursor searches, and gene/protein annotations. Quirks: compound input_item rejects `name` (use pubchem_cid/kegg_id/inchi_key/etc.); free-text → compound is a two-step refmet/match→refmet/name flow; moverz endpoint returns TSV text, not JSON. Use hmdb-database for local XML; pubchem-compound-search for general compound lookup.

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Provides patterns for unit testing Spring Cache annotations (@Cacheable, @CachePut, @CacheEvict). Generates test code that mocks cache managers, verifies cache hit/miss behavior, tests cache key generation with SpEL expressions, validates eviction strategies, and checks conditional caching scenarios. Triggers: caching tests, test Spring cache, mock cache, Spring Boot caching, cache hit/miss verification, @Cacheable testing.

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Provides patterns to generate comprehensive REST API documentation using SpringDoc OpenAPI 3.0 and Swagger UI in Spring Boot 3.x applications. Use when setting up API documentation, configuring Swagger UI, adding OpenAPI annotations, implementing security documentation, or enhancing REST endpoints with examples and schemas.

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Provides patterns to build declarative AI Services with LangChain4j for LLM integration, chatbot development, AI agent implementation, and conversational AI in Java. Generates type-safe AI services using interface-based patterns, annotations, memory management, and tools integration. Use when creating AI-powered Java applications with minimal boilerplate, implementing conversational AI with memory, or building AI agents with function calling.

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Provides patterns for implementing Spring Boot caching: configures Redis/Caffeine/EhCache providers with TTL and eviction policies, applies @Cacheable/@CacheEvict/@CachePut annotations, validates cache hit/miss behavior, and exposes metrics via Actuator. Use when adding caching to Spring Boot services, configuring cache expiration, evicting stale data, or diagnosing cache misses.

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Analyze construction drawings to extract dimensions, annotations, symbols, and metadata. Support quantity takeoff and design review automation.

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Adds developer-authored annotations to the gauntlet knowledge base. Use when capturing tribal knowledge or rationale not visible in code.

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Main app Jetpack Compose UI patterns (WooTheme, Fragment hosting, composeView/legacyComposeView helpers, preview annotations, WC components). Use when writing, editing, exploring, debugging, or reviewing Compose UI in the store management app. NOT for POS (WooPos*) code — use the `pos` skill instead.

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Generate hand-drawn 16:9 article illustrations with the Grav character IP, sparse annotations, and absurd but clear visual metaphors.

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Use when exposing Spring Boot 4 application capabilities through Model Context Protocol tools, resources, or prompts. Covers Spring AI 2.0 MCP annotations, transport selection, schemas, errors, security, and the standalone MCP Java SDK 2.x.

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Automatically migrate Spring MVC applications to Spring Boot. Use when you need to modernize a Spring MVC project to Spring Boot while preserving functionality. The skill analyzes the codebase, updates build configuration (Maven/Gradle), migrates annotations, converts XML configuration to Java/properties, updates controllers and tests, and creates the Spring Boot main application class. Creates git commits for each migration phase and generates a comprehensive summary. Supports both Maven and Gradle projects.

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Generates meaningful comments and documentation for code to improve maintenance and readability. Use when adding documentation to Python or Java code, including function/method docstrings, class documentation, inline explanations for complex logic, and code annotations (TODO, FIXME). Analyzes existing comment style in the codebase to match conventions. Produces clear, concise comments that explain the "why" not just the "what", following best practices for each language.

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Create text-based wireframes at low, mid, and high fidelity with component inventories, interaction annotations, and responsive breakpoint specifications. Use when the user requests wireframing or provides relevant inputs for this workflow.

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Production guidance for converting sourced data and approved claims into truthful, accessible, deterministic animated visualizations with D3. Use for data-driven charts, maps, networks, hierarchies, transitions, annotations, responsive video variants, frame-by-frame browser rendering, and visualization QA; not for generic dashboards, unsourced decorative charts, or ordinary motion graphics without a data contract.

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Extract, filter, annotate, and export differential expression results from DESeq2 or edgeR. Use for identifying significant genes, applying multiple testing corrections, adding gene annotations, and preparing results for downstream analysis. Use when filtering and exporting DE analysis results.

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Query UniProt protein database. Use when user asks about protein sequences, functions, annotations, domains, or protein identifiers. Triggers on "uniprot", "protein function", "protein sequence", "gene product", "protein info".

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Workflow for retrieving public omics datasets, sequences, annotations, and literature-linked biological resources.

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Access UniProt for protein sequence and annotation retrieval. Use this skill when: (1) Looking up protein sequences by accession, (2) Finding functional annotations, (3) Getting domain boundaries, (4) Finding homologs and variants, (5) Cross-referencing to PDB structures. For structure retrieval, use pdb. For sequence design, use proteinmpnn.

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Extracts executable task definitions from Markdown files and runs them as shell pipelines. Parses fenced code blocks with task metadata annotations and manages dependencies between tasks.

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Portrait Mode for SVGs — foveated vectorization with 4-zone selective detail. Combines vision annotations, MediaPipe segmentation/landmarks, and optional saliency. Like phone portrait mode, but vectorized. Use when vectorizing a portrait or photo where subject detail should outrank background detail.

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Suede AI MCP release QA, scoped to this pack's own server (mcp/suede-skills-mcp.mjs) and its catalog, install, and docs surface. Runs the full JSON-RPC lifecycle against a live server (initialize, notifications/initialized, ping, tools/list, tools/call, resources/list, resources/read, prompts/list, prompts/get), plus protocol negotiation, closed input and output schemas, tool annotations, structuredContent with text fallbacks, malformed-input probes, clean stdio, catalog-to-folder agreement, and install-path language. Use when the MCP server, mcp/catalog.json, a tool, resource, or prompt definition, or the MCP install docs change, or before publishing an MCP release. A check that did not run against the live server is a FAIL, not a skip. NOT FOR: a generic third-party MCP server, which this skill's hardcoded surface does not describe; fixing or testing the public install path itself (use suede-launch-packaging).

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Use when building Spring Boot applications with Neo4j using Spring Data Neo4j (SDN 7.x/8.x) — @Node entity mapping, @Relationship, @RelationshipProperties, Neo4jRepository, ReactiveNeo4jRepository, @Query annotations, application.yml configuration, projections, Neo4jClient, Neo4jTemplate, transactions, auditing, or Spring AI Neo4jVectorStore vector search. Does NOT handle raw Java driver code without Spring — use neo4j-driver-java-skill. Does NOT handle Cypher query authoring — use neo4j-cypher-skill. Does NOT handle driver version upgrades — use neo4j-migration-skill.

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Register and implement PydanticAI tools with proper context handling, type annotations, and docstrings. Use when adding tool capabilities to agents, implementing function calling, or creating agent actions.

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RIPDPI Compose performance: stability annotations, compiler metrics, LazyColumn key/contentType, per-screen recomposition notes. Use when diagnosing recomposition, stability, or list performance here.

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。