Create scalable, containerized bioinformatics pipelines with Nextflow DSL2 supporting Docker, Singularity, and cloud execution. Use when building portable pipelines with container support, running workflows on cloud platforms (AWS, Google Cloud), or leveraging nf-core community pipelines.
Create portable bioinformatics pipelines with Workflow Description Language (WDL) using Cromwell or miniwdl execution engines. Use when running GATK best practices pipelines, working with Terra/AnVIL platforms, or building workflows for cloud execution on Google Cloud or AWS.
Create portable, standards-based bioinformatics pipelines with Common Workflow Language (CWL). Use when building workflows that need maximum portability across execution platforms, sharing pipelines with collaborators using different systems, or contributing to community workflow registries.
Analyze compilation time and test durations from CI logs. Use when the user asks about slow builds, slow tests, or wants to optimize CI time.
Establish performance baselines and detect regressions using flamegraph analysis. Use when optimizing performance-critical code, investigating performance issues, or before creating commits with performance-sensitive changes.
Implements the Ralph Wiggum autonomous iteration technique with deliberate context management. Use when building greenfield projects, iterating on well-defined tasks, or when continuous autonomous development is needed. Manages context like memory - tracks allocations, prevents redlining, and knows when to start fresh.
Bootstrap a new container by validating required tools and installing missing dependencies.
Generate a Graphite chart (12h default) for a Zigbee device metric and post it to the web timeline.
Generate a Graphite chart (12h default) for a Zigbee device metric and post it to the web timeline.
Create a new background worker in daily-api with full type safety, infrastructure config, and tests
Creates a new Figma Code Connect mapping file for a CDS component
Post-implementation cleanup that removes AI-generated bloat while preserving functionality. Runs pass-by-pass with test verification after each pass. Activate after kraken/spark complete a feature, or when a codebase needs hygiene work.
Traffic splitting, health checks, automated rollback, progressive delivery, and canary analysis for safe deployments.
Verification loop for Django projects: migrations, linting, tests with coverage, security scans, and deployment readiness checks before release or PR.
Implement technical plans from thoughts/shared/plans with verification
Implement technical plans from thoughts/shared/plans with verification
Implementation agent that executes a single task and creates handoff on completion
Azure Functions, Cosmos DB modeling, Service Bus patterns, Bicep templates
4-layer memory recall system. Layer 1 (identity) always loaded, Layer 2 (critical facts) per-project, Layer 3 (room recall) on-demand, Layer 4 (deep search) when needed. Progressive context loading for token efficiency.
Agentica server + Claude proxy setup - architecture, startup sequence, debugging
