Crabline is a deterministic local messaging-channel mocking framework for end-to-end testing of chat integrations. It provides a CLI tool and a TypeScript library that simulates 12+ messaging platforms (Discord, Slack, Telegram, WhatsApp, Matrix, etc.) via mock servers and provider adapters. The architecture is built around a provider adapter pattern with lazy loading, a JSONL-based event recorder with cross-process locking, and a fixture-driven test runner that supports probe, send, roundtrip, and agent modes. The system is configuration-driven via YAML manifests validated with Zod schemas, and it publishes readiness artifacts for integration with the OpenClaw QA ecosystem. The codebase demonstrates strong engineering practices: clean separation of concerns, extensive test coverage (including concurrency and edge cases), and reusable infrastructure components such as process-owned file locks, nonce generation, inbound message matchers, and webhook authentication policies. The mock servers faithfully replicate platform-specific APIs (REST, WebSocket, SSE) with configurable resource limits and admin inbound endpoints for injecting test messages. While primarily a testing tool, Crabline's components are designed for reuse: the recorder, lock system, and provider adapter base class can be extracted into other projects. The repository is actively maintained with CI/CD pipelines, dependency management, and a changelog. It is not a data research project; all data artifacts (JSONL logs) are operational evidence for test assertions, not analytical datasets.
OpenClaw RTT is a data repository that stores normalized round-trip time (RTT) performance test results for the OpenClaw multi-channel messaging integration platform. It contains structured JSONL files under `data/channels/` for Telegram, Slack, Discord, and WhatsApp, alongside raw `result.json` files under `runs/`. The data is collected from automated QA canary and release harness runs executed via `pnpm openclaw qa <channel>`, with all tests using a mock OpenAI provider. The repository's primary function is to enable version-to-version performance regression tracking across chat channels, with summaries displayed in the README dashboard. The codebase includes import and summary scripts, validation logic, and CI workflows, but the majority of content is historical test result data. Notable patterns include consistent JSONL schemas, polling configurations, and resource measurement (max RSS, elapsed time). Many channel tests, especially Slack and WhatsApp, show persistent failures, indicating integration issues or broken test infrastructure.