Results for “pip”

Coordinate multi-agent development pipelines using shared JSON task files. Use when dispatching work across dev team agents (code-agent, test-agent, docs-agent, monitor-bot), tracking pipeline progress, or running sequential/parallel workflows. Covers project init, task assignment, status tracking, agent dispatch via sessions_send, and result collection. Supports two modes: linear (sequential pipeline) and dag (dependency graph with parallel execution).

Provides idiomatic PyTorch patterns and best practices for building robust, efficient, and reproducible deep learning applications, covering model architecture, training loops, data pipelines, and checkpointing.

Design and implement a comprehensive DevSecOps pipeline in GitLab CI/CD integrating SAST, DAST, container scanning, dependency scanning, and secret detection.

Designs and implements production-grade ML pipeline infrastructure: configures experiment tracking, creates orchestration DAGs, builds feature store schemas, deploys model registries, and automates retraining and validation workflows.

Qualify, prioritize, and advance sales prospects into the next best action. Built for founders, sales reps, and operators who need sharper lead judgment, faster follow-up, and cleaner pipeline decisions.

Guides the choice between DuckDB and Polars for each stage of an analytical pipeline, covering Arrow transfer, lazy versus eager execution, registration lifetime, schema conversion, and result ownership.

Build and debug Retrieval-Augmented Generation pipelines — chunking, embedding, retrieval, reranking

Run the full cenci plan, test, implementation, review, and pull-request pipeline.

Full release pipeline — tests → coverage → review gate → version bump → CHANGELOG → commit → PR

Manages vector embeddings with Pinecone for semantic search, recommendation, and RAG pipelines.

Write academic papers with a 12-agent pipeline supporting full drafting, revision, citation checks, and LaTeX/DOCX output across multiple disciplines and paper types.

Build an automated IOC enrichment pipeline using OpenCTI's connector ecosystem to enrich indicators with context from VirusTotal, Shodan, AbuseIPDB, GreyNoise, and other sources.

Patterns and architectures for running Claude Code autonomously in loops, from simple sequential pipelines to RFC-driven multi-agent DAG systems.

Plan, configure, and chain Nemotron model customization steps into single-step or multi-step pipelines for curation, translation, fine-tuning, RL alignment, benchmarking, checkpoint conversion, optimization, and evaluation.

Orchestrate autonomous AI development pipelines through your Kanban board, managing multi-worker Claude Code dispatch, deterministic quality gates, adversarial review, per-task cost tracking, and crash-proof pipeline execution.

Simulate and detect software supply chain attacks including typosquatting via Levenshtein distance, dependency confusion testing, package hash verification, and vulnerability scanning with pip-audit.

Audits a project's developer experience by scoring devcontainer, git hooks, linting, build caching, environment setup, and release pipeline, then generates a DX health report with prioritized recommendations.

Designs and implements big data architectures, processes large-scale datasets with distributed systems, and optimizes data pipelines for throughput using Hadoop, Spark, and cloud platforms.

Process data partitioner operations. Auto-activating skill for Data Pipelines. Triggers on: data partitioner, data partitioner Part of the Data Pipelines skill category. Use when working with data partitioner functionality. Trigger with phrases like "data partitioner", "data partitioner", "data".

Validate schema validator operations. Auto-activating skill for Data Pipelines. Triggers on: schema validator, schema validator Part of the Data Pipelines skill category. Use when working with schema validator functionality. Trigger with phrases like "schema validator", "schema validator", "schema".

Retrieval-Augmented Generation pipelines — ingestion, chunking, embedding, vector stores, retrieval, evaluation. Use when building a RAG pipeline, choosing chunking strategies or embedding models, debugging retrieval quality or hallucinations, evaluating an existing RAG system, or scaling/migrating vector stores.

Build automated pipelines with reusable components, data flow between nodes, and state management.

Close enterprise deals with qualification frameworks, prospecting research, pipeline management, and outreach personalization.

Builds NLP pipelines with Haystack for document search, QA, and LLM-powered applications.

Revenue forecast from pipeline data with stage-weighted probability and sensitivity analysis

Cancel any active OMC mode (autopilot, ralph, ultrawork, ultraqa, swarm, ultrapilot, pipeline, team)

Decides whether a personalized gift should be created each day, then generates it as an interactive H5 page, AI image, or AI video through a five-stage creative pipeline.

Load pre-trained models from Hugging Face Hub, run pipeline inference, generate text, and fine-tune models on NLP, vision, audio, and multimodal tasks using the Transformers library.

Monitors and manages Coveo enterprise search platform: sources, indexes, query pipelines, ML models, usage analytics, and security providers, with health checks and license utilization.

This skill should be used when the user asks to "start an LLM project", "design batch pipeline", "evaluate task-model fit", "structure agent project", or mentions pipeline architecture, agent-assisted development, cost estimation, or choosing between LLM and traditional approaches.

Jenkins CLI for controllers. Use when users need to manage jobs, pipelines, config.xml, runs, logs, artifacts, credentials, nodes, or queues in Jenkins. Triggers include "jenkins", "jk", "pipeline", "build", "job create", "job config", "config.xml", "run logs", "jenkins credentials", "jenkins node".

Comprehensive DevOps skill for CI/CD, infrastructure automation, containerization, and cloud platforms (AWS, GCP, Azure). Includes pipeline setup, infrastructure as code, deployment automation, and monitoring. Use when setting up pipelines, deploying applications, managing infrastructure, implementing monitoring, or optimizing deployment processes.

Jenkins CLI for controllers. Use when users need to manage jobs, pipelines, config.xml, runs, logs, artifacts, credentials, nodes, or queues in Jenkins. Triggers include "jenkins", "jk", "pipeline", "build", "job create", "job config", "config.xml", "run logs", "jenkins credentials", "jenkins node".

Jenkins CLI for controllers. Use when users need to manage jobs, pipelines, config.xml, runs, logs, artifacts, credentials, nodes, or queues in Jenkins. Triggers include "jenkins", "jk", "pipeline", "build", "job create", "job config", "config.xml", "run logs", "jenkins credentials", "jenkins node".

OpenTelemetry observability patterns: traces, metrics, logs, context propagation, OTLP export, Collector pipelines, and troubleshooting

Cancel any active OMX mode (autopilot, ralph, ultrawork, ecomode, ultraqa, swarm, ultrapilot, pipeline, team)