Total 50,316 skills, AI & Machine Learning has 8453 skills
Showing 12 of 8453 skills
Build a graph-structured dossier on a seed entity via parallel fan-out + recursive expansion across web, memory, knowledge-graph, codebase, ADR index, and git intel
Publish or fetch learned patterns across projects via IPFS (Pinata) -- the cross-project pattern transfer that hooks_transfer enables
Per-conversation cost view — list every session in cost-tracking with started-at, message count, top model, and total cost
Route tasks through hooks_route, partition by Agent Booster availability, and report Tier 1 bypass utilization with $0 cost
Generate setup scripts/configs for AI agent worktrees and isolated environments across Cursor, Codex, and Conductor. Use when wiring up a project so AI agents start with the same dependencies, env files, and tool configs as the main repo.
Show ContextShield status and waste protection stats
EMIT phase. Pre-emit debug, write files, post-emit verify from disk. Any new unknown triggers immediate snake back to planning — restart chain.
EXECUTE phase. Resolve all mutables via witnessed execution. Any new unknown triggers immediate snake back to planning — restart chain from PLAN.
[BETA] Execute work plans with external delegate support. Same as ce:work but includes experimental Codex delegation mode for token-conserving code implementation.
Author ZenML pipelines: @step/@pipeline decorators, type hints, multi-output steps, dynamic vs static pipelines, artifact data flow, ExternalArtifact, YAML configuration, DockerSettings for remote execution, custom materializers, metadata logging, secrets management, and custom visualizations. Use this skill whenever asked to write a ZenML pipeline, create ZenML steps, make a pipeline work on Kubernetes/Vertex/SageMaker, add Docker settings, write a materializer, create a custom visualization, handle "works locally but fails on cloud" issues, or configure pipeline YAML files. Even if the user doesn't explicitly mention "pipeline authoring", use this skill when they ask to build an ML workflow, data pipeline, or training pipeline with ZenML.
AI voice assistants with custom instructions, knowledge bases, and tool integrations.
AI voice assistants with custom instructions, knowledge bases, and tool integrations.