vm-and-bytecode-reverse
Covers reverse engineering custom VMs and bytecode. Applies to CTF challenges or protected software with proprietary bytecode, dispatcher loops, or maze-style challenges.
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Find your next superpower If you are an agent, refer to our llms.txt for full access.Covers reverse engineering custom VMs and bytecode. Applies to CTF challenges or protected software with proprietary bytecode, dispatcher loops, or maze-style challenges.
Generates tool and function calling patterns using @Tool annotations, tool executors, and AiServices registration. Covers parameter validation, execution errors, tool responses, and external API integration in LLM applications.
Retrieves GitHub trending repositories and developers. Supports discovering popular projects, tracking trends, and supplying trending repository data for dashboards.
Provides testing patterns for pure functions, null handling, edge cases, and boundary conditions. Generates AssertJ assertions and parameterized tests for string utilities, math utilities, validators, and collection helpers.
Generate responses to common legal inquiries using configured templates and escalation checks. Covers data subject requests, litigation holds, vendor questions, NDA requests, and subpoenas.
Covers experimental HTML-in-Canvas APIs using HTMLSource for live interactive elements and ElementImageSource for immutable snapshots. Includes feature detection, layout requirements, updates, texture use, fallback detection, errors, and cleanup.
Configures AI model beans, chat memory, and RAG pipelines within Spring Boot and Spring Data. Covers auto-configuration, dependency injection, and integration with the Spring ecosystem.
Follows the official quickstart to scaffold a minimal LangChain agent in Python. Supports quickly building or trying an agent locally.
Generates document ingestion pipelines, embedding stores, vector search, and semantic search using LangChain4j. Supports document question answering, knowledge-base assistants, repository search, and source attribution.
Provides testing patterns for @Scheduled and @Async methods using JUnit 5, CompletableFuture, Awaitility, and Mockito. Covers mocked execution and timing, cron expressions, execution counts, retry behavior, and thread pool simulation.
Investigate competitors' App Store strategies and compare them with an app's positioning. Identify keyword gaps and opportunities informed by competitive research.
Creates a new repository on GitHub and clones it to the local environment.
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