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概要と使いどころ
Capture the before/after rendered PNGs a UI-affecting PR in this repository needs as visual evidence, including bringing an Android SDK up in a fresh sandbox. Use when a change touches a Compose @Preview, a catalog, the VS Code webview, an overlay, a theme, an icon or a fixture, and the PR body needs real pixels.
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Deterministic handbook-grounded retrieval and thermocouple computations for reflow profile compliance outputs such as ramp, TAL, peak, feasibility, and selection.
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。
Use this skill when implementing PID control loops for adaptive cruise control, vehicle speed regulation, throttle/brake management, or any feedback control system requiring proportional-integral-derivative control.
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。
Provisions and manages Neo4j Aura instances via CLI (aura-cli v1.7+) or REST API. Use when creating, pausing, resuming, resizing, or deleting AuraDB Free/Professional/Business Critical/VDC instances; downloading credentials; scripting CI/CD pipelines; polling async status; or using the Terraform neo4j-labs/neo4jaura provider. Covers auth setup (client credentials OAuth2), credential lifecycle (download once — never recoverable), instance type selection, region codes, and Python provisioning scripts. Does NOT handle Cypher queries — use neo4j-cypher-skill. Does NOT cover Graph Data Science algorithms — use neo4j-gds-skill or neo4j-aura-graph-analytics-skill. Does NOT cover neo4j-admin/cypher-shell — use neo4j-cli-tools-skill.
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。
Run Neo4j Graph Analytics algorithms (PageRank, Louvain, WCC, Dijkstra, KNN, Node2Vec, FastRP, GraphSAGE) directly inside Snowflake without moving data. Use when running graph algorithms against Snowflake tables via the Neo4j Snowflake Native App ("GDS Snowflake", "graph algorithms in Snowflake", "Neo4j Graph Analytics"). Covers the explore → prepare projection views → project-compute-write flow, the strict view/column type rules the graph engine requires, exact SQL CALL syntax, and privilege setup in both modes — app-identity grants and execute-as-user / per-user PAT auth (programmatic access token, set_enable_custom_credentials, register_user_role, caller grants). Does NOT cover Cypher or Neo4j DBMS queries — use neo4j-cypher-skill. Does NOT cover Aura Graph Analytics — use neo4j-aura-graph-analytics-skill. Does NOT cover self-managed GDS — use neo4j-gds-skill.
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。
Programmatic security management in Neo4j — RBAC/ABAC, user lifecycle (CREATE/ALTER/DROP USER), role lifecycle (CREATE/GRANT ROLE/DROP ROLE), privilege grants and denies (GRANT/DENY/REVOKE on graph, database, DBMS), property-level access control, sub-graph access control, SHOW PRIVILEGES inspection, and auth provider config reference (LDAP, OIDC/SSO). Use when an agent needs to manage users, roles, or privileges programmatically via Cypher on the system database. Does NOT handle Cypher query writing — use neo4j-cypher-skill. Does NOT handle cluster ops or backups — use neo4j-cli-tools-skill. Property-level security and ABAC require Enterprise Edition.
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。
Build GraphRAG retrieval pipelines on Neo4j using the neo4j-graphrag Python package (v1.22.0+). Covers retriever selection (VectorRetriever, HybridRetriever, VectorCypherRetriever, HybridCypherRetriever, Text2CypherRetriever, ToolsRetriever), external vector DB retrievers (Weaviate, Pinecone, Qdrant), retrieval_query Cypher fragments, query_params, filters, GraphRAG pipeline wiring (GraphRAG + LLM + prompt), all LLM providers (OpenAI, Anthropic, Gemini/VertexAI, Bedrock, Cohere, Mistral, Ollama), embedder setup, index creation, token usage tracking, Cypher 25 SEARCH clause, and LangChain/LlamaIndex integration. Does NOT handle KG construction — use neo4j-document-import-skill. Does NOT handle plain vector search — use neo4j-vector-index-skill. Does NOT handle GDS analytics — use neo4j-gds-skill. Does NOT handle agent memory — use neo4j-agent-memory-skill.
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。
Use Neo4j GenAI Plugin ai.text.* functions and procedures for in-Cypher embedding generation, text completion, structured output, chat, tokenization, and batch ingestion. Covers ai.text.embed(), ai.text.embedBatch(), ai.text.completion(), ai.text.structuredCompletion(), ai.text.aggregateCompletion(), ai.text.chat(), ai.text.tokenCount(), ai.text.chunkByTokenLimit(), and provider configuration for OpenAI, Azure OpenAI, VertexAI, and Amazon Bedrock. Requires CYPHER 25. Replaces deprecated genai.vector.encode(). Use when writing pure-Cypher GraphRAG, embedding nodes in-graph, generating structured maps from prompts, or calling LLMs inside Cypher queries. Does NOT handle neo4j-graphrag Python library pipelines — use neo4j-graphrag-skill. Does NOT handle vector index creation/search — use neo4j-vector-index-skill.
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。
Orchestrates zero-to-running-app in 8 stages — prerequisites → context → provision → model → load → explore → query → build. Each stage reads its own reference file. Supports HITL and fully autonomous operation. Use when starting a new Neo4j project from scratch, provisioning Aura, generating synthetic data, building a notebook or app, or running the full onboarding pipeline. Time budget ≤15 min autonomous, ≤90 min HITL. Does NOT cover Cypher query authoring — use neo4j-cypher-skill. Does NOT cover driver upgrades or Cypher migration — use neo4j-migration-skill. Does NOT cover CLI/admin tasks on an existing DB — use neo4j-cli-tools-skill.
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。
Generates, optimizes, and validates Cypher 25 queries for Neo4j 2025.x and 2026.x. Use when writing new Cypher queries, optimizing slow queries, graph pattern matching, vector or fulltext search, subqueries, or batch writes. Covers MATCH, MERGE, CREATE, WITH, RETURN, CALL, UNWIND, FOREACH, LOAD CSV, SEARCH, expressions, functions, indexes, and subqueries. Does NOT handle driver migration or API changes — use neo4j-migration-skill. Does NOT cover DB administration or server ops — use neo4j-cli-tools-skill.
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。
Configure and operate the Neo4j Connector for Kafka (sink + source) and the native Neo4j CDC API. Covers Cypher/Pattern/CUD sink strategies, CDC-based and query-based source, exactly-once semantics, DLQ error handling, Confluent Cloud managed connector, schema registry (Avro/JSON), and native db.cdc.query cursor-loop patterns (Neo4j 5.13+ Enterprise/Aura BC/VDC). Use when streaming Kafka events into Neo4j, streaming Neo4j changes to Kafka, or querying Neo4j change events without Kafka. Does NOT handle Cypher query authoring — use neo4j-cypher-skill. Does NOT handle bulk CSV/file import — use neo4j-import-skill. Does NOT handle GDS algorithms — use neo4j-gds-skill.
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。
Migrates Neo4j driver code and Cypher queries from older versions (4.x, 5.x) to current (2025.x/2026.x, Cypher 25). Covers Python, JavaScript/Node.js, Java, .NET, and Go drivers — package renames, removed APIs, version requirements, diff-ready fixes. Also handles Cypher syntax migration — QPE paths, CALL subqueries, id() → elementId(), PERIODIC COMMIT → CALL IN TRANSACTIONS, and all Cypher 25 removals. Does NOT write new Cypher queries — use neo4j-cypher-skill. Does NOT cover DB administration or server ops — use neo4j-cli-tools-skill. Does NOT provision new Neo4j instances — use neo4j-getting-started-skill.
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。
Create and manage Neo4j vector indexes, run vector similarity search (ANN/kNN), store embeddings on nodes or relationships, use SEARCH clause (Neo4j 2026.01+, preferred) or db.index.vector.queryNodes() procedure (deprecated 2026.04, still works on 2025.x), configure HNSW and quantization options, pick similarity function and embedding provider dimensions, and batch-update embeddings. Use when tasks involve CREATE VECTOR INDEX, vector.dimensions, cosine/euclidean search, embedding ingestion pipelines, semantic or structural nearest-neighbor lookup, or hybrid search (vector + fulltext, multiple vector sources, or graph-derived scores). Does NOT handle GraphRAG retrieval_query graph traversal — use neo4j-graphrag-skill. Does NOT handle fulltext-only/keyword-only search — use neo4j-cypher-skill. Does NOT compute GDS graph embeddings (FastRP, Node2Vec) — use neo4j-gds-skill.
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。
Use when reviewing Java or Kotlin server changes on Spring or Quarkus - security config and method security, JPA/JPQL and JdbcTemplate queries, request binding, deserialization, XML parsers, SpEL, templates, Actuator, JNDI and reflection
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。
Use when you are about to hand off any number, table, chart or analysis someone will act on (a metric query, a dbt mart, a report, an experiment readout) — the pre-delivery checklist for data quality, calculation, reasonableness and presentation, and the pitfalls that produce plausible wrong numbers
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。
Use when dataframe code is slow or runs out of memory, when data outgrows pandas, or when writing pandas 3, Polars or DuckDB code — vectorisation, dtypes, Copy-on-Write, lazy and out-of-core execution, and measuring before and after
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。
Use when data crosses a boundary into your code (file, API, warehouse table, upload, model input or output), when a join or cleaning step can change row counts, or when adding pandera, Great Expectations, Pydantic or dbt checks
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。
Use when a diff or design adds or changes a DB migration, an endpoint or DTO, an event payload, or a shared type with consumers
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。
Use when designing or building any mobile screen or component a user sees (Flutter, SwiftUI or Compose) - platform conventions, hierarchy, type that scales, colour roles and dark mode, safe areas and insets, forms and keyboard, states, feedback, and the generic-mobile anti-patterns.
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。
Use when the task touches a backend API, database or worker - booting it from the task branch, driving real requests and verifying side effects (DB rows, outbound calls, logs) as evidence
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。
Use before handing off any change to an endpoint, job or migration — start the service from the task branch and exercise the change with real requests, real logs and real DB side effects
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。
How to work a task returned with review, QA or UAT findings. Use when a task is in need_revision or PR review comments are in your context.
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 and manage infrastructure as code with Terraform — modules, remote state (S3 + DynamoDB), Stacks (deployments), test framework, preconditions/postconditions, moved/removed blocks, and CI/CD plan/apply separation. Use when user asks to write Terraform config, set up remote state, design modules, manage state, or automate infrastructure. Do NOT use for Kubernetes (use kubernetes), Docker (use docker), or CI/CD pipeline design (use ci-cd).
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。
Encode Emil Kowalski's philosophy on UI polish, component design, animation decisions, and the invisible details that make software feel great. From the creator of Sonner (13M+ weekly npm downloads), Vaul, animations.dev, and Linear's web team. Use when user wants to polish UI, audit animations, review component interactions, add micro-feedback, or elevate motion quality.
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。