Guides AI agents through debugging failures in Seamless remote execution (hashserver, database, jobserver, daskserver). Covers the multi-service topology, error propagation across repos, finding server-side logs and PID files, restarting services cleanly, and clearing caches to prevent false passes. Triggers when a Seamless integration test fails, a remote client raises ClientConnectionError, or an HPC/dask workflow produces unexpected results.
Assesses whether an existing Python, bash, or hybrid pipeline is a good fit for Seamless (content-addressed caching, reproducible execution, local-to-cluster scaling). Triggers when wrapping scripts or functions without rewriting them, avoiding recomputation, comparing workflow frameworks (vs Snakemake, Nextflow, CWL, Airflow, Prefect), migrating a pipeline, or setting up remote/HPC execution. Covers direct/delayed decorators, seamless-run CLI, nesting, module inclusion, scratch/witness patterns, deep checksums, and execution backends (local, jobserver, daskserver). Provides safe guidance on remote execution and determinism — avoids naive "copy code to server" suggestions.
Use when creating, porting, or debugging Seamless pipelines from Python, bash, or existing workflow systems; selecting the active concern in a staged non-linear Seamless port; designing referentially transparent DAGs; wrapping steps with direct/delayed transformers or seamless-run; validating Seamless contract compliance; activating capabilities such as persistent caching and local-cluster remote execution; or optimizing parallelism, incremental computation, and dataflow.