Results for “pr”

Turn a product idea into a repeatable manual process you can start delivering today. Use to design manual-first products before writing any code.

Scaffold new babysitter process definitions following SDK patterns, proper structure, and best practices. Guides the 3-phase workflow from research to implementation.

Mvp Pressure Launch

Gsd New Project

Imported skill prompt from agentskills

Imported skill protocol from langchain

PR Review Expert

runtime-and-process

unified-query-provider

Pre-landing PR review. (gstack)

WP Builder Pro

Use to analyse billing and pricing complaints, separating genuine pricing objections from billing defects and unclear communication. Trigger for "customers complaining about price", "billing complaint analysis", "why do customers dispute their invoice", "is our pricing a problem", unexpected-charge complaints, or a pricing decision that needs evidence from support.

Generate new feature ideas for an existing product using multi-perspective ideation from PM, Designer, and Engineer viewpoints, then prioritize the best five.

Profiles datasets automatically to assess data quality, structure, and completeness, generating reports with ydata-profiling, pandera, or manual pandas methods.

Checks project progress, summarizes recent work and what's ahead, then routes to the next action by executing an existing plan or creating a new one.

Learn and apply CQL concepts, implementation strategies, best practices, and real-world applications in professional environments. Covers foundational concepts, Python implementation patterns, and production-grade system design.

Profile a target (script, process, GPU, memory, interconnect) using external tools and code instrumentation. Produces structured performance reports with actionable recommendations. Use when user says "profile", "benchmark", "bottleneck", or wants performance analysis.

Enforces a mandatory pre-commit/pre-PR testing gate: detects the test stack, runs the full suite, fixes failures, creates minimal tests when none exist, and verifies coverage before allowing commits.

Guides the agent to act as a product manager, collecting context, proposing three requirement plans (bug fix, new feature, iteration), scoring them by ROI, and recommending one with an MVP slice and timeline.

Use the context-grooming skill to prune and compact the current project context.

Draft product requirements with the problem, users, scope, requirements, metrics, and open decisions.

Guides preparation for supervisory authority (DPA) inspections and investigations including document readiness checklists, interview preparation for key personnel, technical demonstration procedures, on-site logistics, response protocols, and post-inspection follow-up. Covers unannounced inspections, formal audits, and complaint-triggered investigations. Keywords: DPA inspection, supervisory authority, investigation, readiness, interview preparation, response protocol.

Python performance profiling with cProfile, tracemalloc, and line_profiler. Use for identifying bottlenecks and memory issues. USE WHEN: user mentions "Python profiling", "cProfile", "memory profiling", asks about "Python performance", "tracemalloc", "line_profiler", "py-spy", "Python optimization", "Python memory leak" DO NOT USE FOR: Java/Node.js profiling - use respective skills instead

Comprehensive toolkit for protein language models including ESM3 (generative multimodal protein design across sequence, structure, and function) and ESM C (efficient protein embeddings and representations). Use this skill when working with protein sequences, structures, or function prediction; designing novel proteins; generating protein embeddings; performing inverse folding; or conducting protein engineering tasks. Supports both local model usage and cloud-based Forge API for scalable inference.

Comprehensive toolkit for protein language models including ESM3 (generative multimodal protein design across sequence, structure, and function) and ESM C (efficient protein embeddings and representations). Use this skill when working with protein sequences, structures, or function prediction; designing novel proteins; generating protein embeddings; performing inverse folding; or conducting protein engineering tasks. Supports both local model usage and cloud-based Forge API for scalable inference.

Comprehensive toolkit for protein language models including ESM3 (generative multimodal protein design across sequence, structure, and function) and ESM C (efficient protein embeddings and representations). Use this skill when working with protein sequences, structures, or function prediction; designing novel proteins; generating protein embeddings; performing inverse folding; or conducting protein engineering tasks. Supports both local model usage and cloud-based Forge API for scalable inference.

Configure wallet signing providers for OpenSea transactions, supporting Privy, Turnkey, Fireblocks, Bankr, and local private keys.

Identify, categorize, and prioritize accumulated design inconsistencies and structural problems across a product.

Guides reliable project delivery through goal-setting, progress tracking, and structured execution frameworks.

Use this skill to validate the "why" before building, run product diagnostics, and pressure-test product direction before the request becomes an implementation contract.

Create pull requests following Sentry conventions. Use when opening PRs, writing PR descriptions, or preparing changes for review. Follows Sentry's code review guidelines.

Provides production patterns and non-obvious traps for Prisma ORM in TypeScript backends, covering schema design, query optimization, transactions, pagination, and common pitfalls.

Detect process hollowing (T1055.012) by analyzing memory-mapped sections, hollowed process indicators, and parent-child process anomalies in EDR telemetry.

Turn a product URL, script, or brief into a polished launch video with brand assets, storyboard, and frame-by-frame animation.

Trains language models with Direct Preference Optimization using preference pairs, covering DPOTrainer setup, dataset preparation, and beta tuning for stable preference learning without explicit reward models.

Generates a structured 6-minute two-person English product presentation script, split into unique features/target customers and market comparison/competitive advantages, with time allocations and full dialogue.