Results for “pr”

Enforces ML infrastructure, experiment tracking, reproducibility, model packaging, CI/CD, monitoring, and infrastructure-as-code standards at principal-engineer level.

Create a SAM.gov search monitor from a pursuit or expiring row — persists to Pipeline and writes sam_monitor.md in the pursuit folder. Primary admin rote task for capture managers watching recompetes.

Three-layer verification pipeline for AI output. Extracts verifiable claims, finds supporting or contradicting sources via web search, runs adversarial review for hallucination patterns, and produces a structured verification report with source links for human review.

You are an Inngest expert who builds reliable background processing without managing infrastructure. You understand that serverless doesn't mean you can't have durable, long-running workflows - it means you don't manage the workers.

Build scalable data pipelines, modern data warehouses, and real-time streaming architectures. Implements Apache Spark, dbt, Airflow, and cloud-native data platforms. Use PROACTIVELY for data pipeline design, analytics infrastructure, or modern data stack implementation.

Run Python code in the cloud with serverless containers, GPUs, and autoscaling. Use when deploying ML models, running batch processing jobs, scheduling compute-intensive tasks, or serving APIs that require GPU acceleration or dynamic scaling.

Set up and orchestrate multi-container Docker applications using docker-compose, including service configuration, networking, volumes, and environment management. Use when the user requests docker compose setup or provides relevant inputs for this workflow.

Full daily sales pipeline execution. Run at 9 AM via cron. Scans for signals, enriches company leads, auto-applies to gigs, runs multi-channel outreach, processes follow-ups. All delivery automated via Chrome DevTools MCP.

Probe the forms on a page for validation gaps — missing required-field enforcement, no client-side validation, accepts malformed input, and absent error messaging. Reports per-field findings. Playwright MCP only, no signup.

Run the standard single-cell RNA-seq analysis pipeline with Scanpy on AnnData — QC filtering, normalization, dimensionality reduction (PCA, UMAP, t-SNE), Leiden/Louvain clustering, marker/differential expression, PAGA trajectories, and plotting. Use when analyzing scRNA-seq data through clustering, cell-type annotation, DE, or pseudotime workflows; for building or reading the .h5ad data structure itself (layers, obs/var, concatenation, backed mode) prefer alterlab-anndata instead, and for RNA velocity from spliced/unspliced counts prefer alterlab-scvelo instead. Part of the AlterLab Academic Skills suite.

Validate enterprise workloads against Google Cloud best practices using public client libraries and the REST API to manage evaluations, rules, scanned resources, and validation results.

Execute Azure deployments for already-prepared applications using azd up, azd deploy, terraform apply, and az deployment commands with built-in error recovery and verification.

Walks users from a bare AKS cluster to a running AI model deployment, covering cluster verification, controller install, GPU assessment, provider setup, and first deployment.

Collects launch inputs and runs preflight checks before executing TAO workflows such as AutoML, training, evaluation, inference, export, TensorRT engine generation, or DEFT jobs on supported platforms.

Generates and writes unit tests for any programming language using a multi-agent pipeline that researches, plans, and implements tests with build and verification steps.

Diagnose and fix slow MSBuild incremental builds by identifying why targets re-execute unnecessarily, covering common causes like missing Inputs/Outputs, volatile properties, and FileWrites registration.

Detect and fix code-quality and correctness issues in AEM as a Cloud Service projects locally, without external services or network calls.

Registers prompt-based AI agents in Azure AI Foundry via REST API from a local JSON manifest, making them immediately available for invocation.

Reviews and hardens GitHub Actions workflows against injection, privilege escalation, supply-chain, and token-scoping risks that pattern matchers miss.

Adds GraalVM native image support to Java applications by analyzing the project structure, configuring the build tool, and iteratively resolving build errors.

Automatically discover, classify, and protect sensitive data in S3 buckets using machine learning and pattern matching for PII, financial data, and credentials detection.

Implement infrastructure as code with Terraform across AWS, Azure, or GCP, including module development, state management, provider configuration, multi-environment workflows, and infrastructure testing.

Design tool descriptions, schemas, and response formats that agents can reliably route on, including MCP server design, tool-set consolidation, and naming conventions.

Makes n8n workflow failures loud, structured, and recoverable by wiring per-node error outputs, retry logic, error-trigger workflows, and proper HTTP response shapes.

Selects the correct SageMaker serving container image URI for HuggingFace model deployments, prioritizing HuggingFace-curated Deep Learning Containers over generic alternatives.

Orchestrate CTF, exploit, reverse engineering, DFIR, and other challenge types by treating presented targets as sandbox-internal, tracing minimal paths, and routing to specialized downstream skills.

Provides multi-language code navigation via persistent LSP daemons, supporting definitions, references, hover, symbols, and diagnostics for Python, TypeScript, Rust, Go, and more.

Build, test, inspect, install, and deploy MCP servers with FastMCP in Python, including wrapping APIs, databases, or files as tools and exposing resources or prompts.

Automates repetitive infrastructure and deployment tasks with Terraform, OpenTofu, Ansible, GitHub Actions, and n8n, enforcing safe practices like plan review and confirmation before applying changes.

Upserts a validated MDX book corpus into Supabase via Drizzle, hydrating books, chapters, sections, and chunks tables while preserving stable bookmark anchors and only re-embedding changed content.

Manages Neon serverless Postgres databases via the neonctl CLI and Neon API, covering projects, branches, databases, roles, endpoints, and compute scaling with a discovery-first workflow.

Quick reference for Salesforce Agent Script CLI commands, covering retrieve, validate, publish, deploy, and test workflows, plus authoring bundle structure and CI/CD integration.

You are an Inngest expert who builds reliable background processing without managing infrastructure. You understand that serverless doesn't mean you can't have durable, long-running workflows - it means you don't manage the workers.

Run Python code in the cloud with serverless containers, GPUs, and autoscaling. Use when deploying ML models, running batch processing jobs, scheduling compute-intensive tasks, or serving APIs that require GPU acceleration or dynamic scaling.

Guided webinar creation pipeline from vague idea to production-ready deliverables. Use when creating a webinar from scratch. Triggers: 'create a webinar', 'build a webinar', 'webinar creation', 'new webinar', 'help me make a webinar'.

Use this skill for glTF/GLB assets, compression, optimization, transforms, texture sizing, browser delivery. Trigger when the task involves 3d web work related to Gltf Asset Pipeline, production implementation, audits, debugging, strategy, or validation.