glide-mq
Creates message queues, workers, job workflows, and fan-out broadcasts using glide-mq on Valkey/Redis Streams. Provides API reference, code patterns, and configuration for queues, workers, delayed/priority jobs, schedulers, batch processing, DAG workflows, request-reply, and serverless producers. Triggers on "glide-mq", "glidemq", "job queue valkey", "background tasks valkey", "message queue redis streams".
daggr
Build DAG-based AI pipelines connecting Gradio Spaces, HuggingFace models, and Python functions into visual workflows. Use when asked to create a workflow, build a pipeline, connect AI models, chain Gradio Spaces, create a daggr app, build multi-step AI applications, or orchestrate ML models. Triggers on: "build a workflow", "create a pipeline", "connect models", "daggr", "chain Spaces", "AI pipeline".
airflow
Manages Apache Airflow operations including listing, testing, running, and debugging DAGs, viewing task logs, checking connections and variables, and monitoring system health. Use when working with Airflow DAGs, pipelines, workflows, or tasks, or when the user mentions testing dags, running pipelines, debugging workflows, dag failures, task errors, dag status, pipeline status, list dags, show connections, check variables, or airflow health.
Hamilton Core Development Assistant
Apache Hamilton is a lightweight Python framework for building Directed Acyclic Graphs (DAGs) of data transformations using declarative, function-based definitions.
cai-causal-graph
Define, manipulate, and serialize causal graph structures (DAG, CPDAG, MAG, PAG) using cai-causal-graph. Provides CausalGraph, Node, Edge, Skeleton classes with variable type support (CONTINUOUS, BINARY, MULTICLASS, ORDINAL). Use when user imports from cai_causal_graph, works with causal graphs, needs graph conversion (NetworkX, adjacency matrix, dict), or mentions DAG/CPDAG/PAG/MAG representations. Do NOT trigger for graph neural networks or knowledge graphs unrelated to causality.
ClipCraft
ClipCraft is a video-production mode where the **source of truth is a structured domain model**, not a file. The in-memory model is an event-sourced craft store from `@pneuma-craft`: an Asset registry, a Composition with Tracks and Clips, and a Provenance DAG that tracks how each asset was generated
Lossless Context Commands
You have access to a persistent, DAG-based conversation vault. Every message from every session is preserved in SQLite. Summaries form a directed acyclic graph â nothing is ever deleted.
r-bayes
Patterns for Bayesian inference in R using brms, including multilevel models, DAG validation, and marginal effects. Use when performing Bayesian analysis.
cache-expert
Covers Dagger Engine caching internals including cache key derivation, invalidation, and the immutable DAG model. Use when debugging cache misses, unexpected invalidations, or implementing caching-related engine features.