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Found 21 Skills
Build production-ready gRPC services in Go with mTLS, streaming, and observability. Use when designing Protobuf contracts with Buf or implementing secure service-to-service transport.
A Web/JS reverse engineering case knowledge base extracted from 42 articles across the entire 1997.pro site. It applies to case clues such as Akamai/Kasada/PX/reese84/TongDun/a_bogus/Tencent slider/Alibaba slider/JSVMP/227/226/wasm/protobuf/rid/fuid/fs/bx-pp/run_js/storage.estimate/animationend, as well as scenario judgment, method routing and case comparison for risk control fingerprints, environment patching, JSVMP/flat flow/WASM, captchas, and protocol parameter chains; it is used in collaboration with web-js-reverse-master-flow and three MCPs: jshook + js-reverse + chrome-devtools-mcp by default.
kotlinx.serialization - JSON, Protobuf, custom serializers
Master control flow for complex Web/JS website restoration. Applicable to reverse engineering of sign/token/cookie/header/body/websocket fields, heavy obfuscation, junk code, control flow flattening, JSVMP, worker/wasm, browser vs. Node.js difference analysis, environment patching, local reproduction and regression. It also covers case clues such as Akamai/Kasada/PX/reese84/TongDun/a_bogus/Tencent slider/Alibaba slider/JSVMP/227/226/wasm/protobuf/rid/fuid/fs/bx-pp/run_js/storage.estimate/animationend. By default, it adopts three MCP collaborative debugging and analysis: jshook + js-reverse + chrome-devtools-mcp, and switches specialized skills in locate, recover, runtime, env-patch, replay stages.
Review Kafka schema changes (Avro, Protobuf, JSON Schema) for compatibility and evolution best practices using the Lenses MCP server. Detects breaking changes, missing defaults, schema drift and naming issues. Use when user says "review schema changes", "check schema compatibility", "will this schema break consumers" or asks about schema evolution. Do NOT use for creating new schemas from scratch or registering them in the cluster.
Set up end-to-end Change Data Capture (CDC) pipelines on Confluent Cloud using Debezium source connectors, Flink for transformation, and Tableflow for data lake integration. Supports JSON_SR, Avro, and Protobuf formats. Handles schemaless topics (plain JSON without SR) and multi-event topics. This skill handles the complete workflow from database to Iceberg/Delta tables. Use this skill when users want to capture database changes and materialize them into Iceberg or Delta Lake tables via Confluent Cloud Tableflow. Trigger phrases include "CDC to Tableflow", "database to Iceberg", "database to Delta Lake", "stream database changes to data lake", "set up Tableflow pipeline", "schemaless topic to Tableflow", or "multi-event topic to Iceberg". Do NOT trigger for general CDC, Debezium, or database replication requests that do not involve Tableflow or Iceberg/Delta Lake as the destination.
Use when building IoT applications, sensor networks, or edge devices in Rust. Covers telemetry, protocol buffers, protobuf, CoAP, BLE, Bluetooth, serial communication, GPIO, edge computing, OTA update, firmware, data pipeline, MQTT with rumqttc, offline-first store-and-forward, exponential backoff retry, power management, TLS security, and telemetry publishing.
Official Glue IDL guide for agents. Use when writing, explaining, validating, configuring, or generating code from Glue files into TypeScript, Python, Rust, Go, OpenAPI, JSON Schema, or Protobuf.
JSON and binary serialization patterns for .NET applications, including System.Text.Json source generators, Protocol Buffers, MessagePack, and AOT-compatible best practices. Use when configuring JSON serialization, choosing between formats, implementing Protocol Buffers for high-performance scenarios, or working with Native AOT.