293건 · 관련도순
Build Solana apps with guidance for wallet connections, on-chain programs, testing, and deployment. Also covers balance and transaction lookups, troubleshooting, and migrating older code, with review steps before signing or sending transactions.
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Build JavaScript or TypeScript apps that interact with NEAR. This skill guides token transfers, smart contract calls, account and key management, transaction signing, and message authentication through near-api-js v7 examples.
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Design and debug Solana applications using MagicBlock. The skill covers fast transaction execution, state delegation and settlement, private payments, price feeds, randomness, and temporary permissions, with guidance on routing transactions and validating integrations.
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Integrate Jupiter Lend on Solana to query lending markets, rates, and user positions, then build deposits, withdrawals, borrowing, and repayment transactions. Separate SDKs, or code libraries, cover data access and transactions, including combined collateral and debt operations.
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Build a TRES Finance dashboard ledger URL (Transactions tab) with a precise filter set — date range, wallets, assets, tags, status, amount, and more — so it can be shared with a customer or reused. Use whenever the user asks for a "ledger link", "dashboard link", "filter URL", or "send <customer> a link to <some filtered view>". Scoped to the Transactions tab only (not Accounting, Roll Forward, Pivot Tables, Cost Basis, or Trial Balances).
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Triggered by "tidy up", "clean up transactions", "categorize uncategorized", "organize my transactions"
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Monitor blockchain mempools for pending transactions, gas analysis, and MEV opportunities. Use when analyzing pending transactions, optimizing gas prices, or researching MEV. Trigger with phrases like "check mempool", "scan pending txs", "find MEV", "gas price analysis", or "pending swaps".
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Design data systems by understanding storage engines, replication, partitioning, transactions, and consistency models. Use when the user mentions "database choice", "which database should I use", "SQL or NoSQL", "replication lag", "partitioning strategy", "consistency vs availability", "stream processing", "ACID transactions", "eventual consistency", "my queries are slow at scale", or "data is inconsistent across replicas". Also trigger when choosing a datastore, designing data pipelines, or debugging distributed-system consistency issues. Covers data models, batch/stream processing, and distributed consensus. For system design, see system-design. For resilience, see release-it.
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Implement saga patterns for distributed transactions and cross-aggregate workflows. Use when coordinating multi-step business processes, handling compensating transactions, or managing long-running workflows.
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Read and write YNAB budgets: list budgets, accounts, balances, transactions, and categories; record transactions. Trigger phrases: ynab, budget, my budget, spending.
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Read-only Ramp corporate spend: transactions, cards and card limits, users, departments. No spend actions by design. Trigger phrases: ramp, corporate spend, expense transactions, card spend limits.
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View Mercury bank accounts and transactions. Read-only by design. Trigger phrases: mercury, mercury balance, mercury transactions.
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View Paddle transactions and customers. Read-only by design. Trigger phrases: paddle, paddle transactions, paddle customers.
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Use when you need to write or review programmatic JDBC with Spring — including JdbcClient (Spring Framework 7+) as the default API, JdbcTemplate only where batch/streaming APIs require JdbcOperations, NamedParameterJdbcTemplate for legacy named-param code, parameterized SQL, RowMapper mapping to records, batch operations, transactions, safe handling of generated keys, DataAccessException handling, read-only transactions, streaming large result sets, and @JdbcTest slice testing. This should trigger for requests such as Review Java code for Spring JDBC (JdbcTemplate, JdbcClient, NamedParameterJdbcTemplate); Apply best practices for Spring JDBC data access in Java code; Detect and fix SQL injection risks in JDBC code; Improve transaction boundaries or exception handling for JDBC operations; Review JdbcClient usage in Spring Framework 7. Part of Plinth Toolkit
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Use when you need data access with Micronaut Data — @MappedEntity, CrudRepository/PageableRepository, @Query with parameters, @Transactional services, projections, @Version, and @MicronautTest with TestPropertyProvider and Testcontainers. For raw java.sql access without generated repositories, use @511-frameworks-micronaut-jdbc. This should trigger for requests such as Review or implement Micronaut Data repositories and entities; Add transactions, pagination, or projections in Micronaut persistence layer; Model Micronaut Data entities and repositories; Review Micronaut Data transactions and pageable queries; Improve projections or optimistic locking with Micronaut Data. Part of Plinth Toolkit
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Use when you need MongoDB persistence in Quarkus — including Panache Mongo entities/repositories, document design, indexes, transactions where applicable, and error handling. This should trigger for requests such as Add MongoDB in Quarkus; Review Quarkus Mongo Panache design; Improve Mongo error handling in Quarkus services; Model MongoDB documents for a Quarkus service; Configure Quarkus MongoDB clients codecs or transactions. Part of Plinth Toolkit
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Use when you need programmatic JDBC in Quarkus — Agroal DataSource, parameterized SQL, transactions, batching, and Dev Services. This should trigger for requests such as Review JDBC or SQL data access in a Quarkus project; Improve transactions and parameter binding for Quarkus JDBC; Translate SQLException to domain exceptions or stream large result sets; Fix CDI self-invocation bypassing @Transactional in Quarkus; Review Agroal DataSource usage in Quarkus JDBC. Part of Plinth Toolkit
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Provides comprehensive Drizzle ORM patterns for schema definition, CRUD operations, relations, queries, transactions, and migrations. Proactively use for any Drizzle ORM development including defining database schemas, writing type-safe queries, implementing relations, managing transactions, and setting up migrations with Drizzle Kit. Supports PostgreSQL, MySQL, SQLite, MSSQL, and CockroachDB.
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Provides distributed transaction patterns using the Saga Pattern for Spring Boot microservices. Use when implementing distributed transactions across services, handling compensating transactions, ensuring eventual consistency, or building choreography or orchestration-based sagas with Kafka, RabbitMQ, or Axon Framework.
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Converts bank, credit card and brokerage statement PDFs, invoices and vendor price lists into clean CSV or Excel, then proves the extraction is complete and correct - opening balance plus transactions equals closing balance, every running balance chains, page totals, row counts and summary totals all tie, signs and decimal separators are consistent. Handles digital PDFs with word-position column bands and detects scanned PDFs that need OCR first. Use it whenever the user wants to convert a bank statement PDF to Excel or CSV, extract transactions from a statement, turn a PDF table into a spreadsheet, import statements into QuickBooks or Xero, or says the converted statement does not balance, rows are missing, or signs look wrong, even if they do not ask for a proof. Never reads amounts off the page image when a text layer exists, and never fixes a failed tie-out by guessing.
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Runs small and midsize business bookkeeping operations - categorizes bank and card transactions to a chart of accounts, reconciles a bank or card statement against the ledger, works a month-end close checklist, and produces a close package for the accountant. Works from QuickBooks Online, Xero, bank CSV/OFX, or Mercury exports, and from the Xero, QuickBooks, or Mercury connectors when present. Use it whenever the user says "reconcile", "bank rec", "categorize transactions", "month end close", "close the books", "books don't match the bank", "reconciliation is off by", "uncategorized expenses", or shares a QuickBooks or Xero export or a bank statement CSV, even if they do not name the task. Never plugs a difference; every unreconciled dollar is explained or listed.
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Match bank transactions to invoices and surface unpaid / unmatched items in a Well workspace. Use when the user asks what's paid vs unpaid, to reconcile the bank, to find missing payments, or to match transactions to invoices.
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Covers the Neo4j Go Driver v6 — driver lifecycle, ExecuteQuery, managed and explicit transactions, session config, error handling, data type mapping, and connection tuning. Use when writing Go code that connects to Neo4j, setting up NewDriver or ExecuteQuery, debugging sessions/transactions/result handling, or working with neo4j-go-driver v5→v6 migration. Triggers on NewDriver, ExecuteQuery, SessionConfig, ManagedTransaction, neo4j-go-driver. Does NOT handle Cypher query authoring — use neo4j-cypher-skill. Does NOT cover driver version migration steps — use neo4j-migration-skill.
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Neo4j Java Driver v6 — driver lifecycle, Maven/Gradle setup, executableQuery, executeRead/Write managed transactions, explicit transactions, async/reactive patterns, error handling, data type mapping, connection pool tuning, causal consistency/bookmarks. Use when writing Java or Kotlin code that connects to Neo4j via GraphDatabase.driver, executableQuery, SessionConfig, executeRead, executeWrite, or TransactionCallback. Does NOT handle Cypher authoring — use neo4j-cypher-skill. Does NOT cover driver version upgrades — use neo4j-migration-skill. Does NOT cover Spring Data Neo4j (@Node, Neo4jRepository) — use neo4j-spring-data-skill.
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