Results for “expert-parallel”

Provides expert guidance on PyTorch Fully Sharded Data Parallel (FSDP) training, covering parameter sharding, mixed precision, CPU offloading, and FSDP2.

Resolves legacy references to the pr-review-expert capability by routing to the current runtime agent or skill.

Compare, cross-review, and merge competing plans from multiple agents into one executable direction with a clear handoff.

CogVLM: Visual Expert for Pretrained Language Models

Dispatching Parallel Agents

Dispatch multiple independent tasks to parallel agents for faster debugging and problem-solving.

Launches four parallel adversarial review agents covering security, scope, fidelity, and test gaps, then synthesizes findings into a ranked verdict for plans or feature branches.

Test Parallelizer - Auto-activating skill for Test Automation. Triggers on: test parallelizer, test parallelizer Part of the Test Automation skill category. Use when writing or running tests. Trigger with phrases like "test parallelizer", "test parallelizer", "test".

Use when implementing java functionality with production-grade patterns and safeguards.

Scaling Vision with Sparse Mixture of Experts

Use when implementing go functionality with production-grade patterns and safeguards.

Modern Angular (v20+) expert with deep knowledge of Signals, Standalone Components, Zoneless applications, SSR/Hydration, and reactive patterns.

Econometrics skill for Difference-in-Differences (DID) analysis. Activates when the user asks about: "difference in differences", "DID", "DiD", "diff-in-diff", "parallel trends", "treatment group", "control group", "pre-treatment", "post-treatment", "policy evaluation", "natural experiment", "staggered DID", "event study regression", "two-way fixed effects DID", "callaway santanna", "sun and abraham", "双重差分", "倍差法", "平行趋势", "处理组", "对照组", "政策评估", "事件研究", "交错DID", "渐进处理"

Use when implementing perl functionality with production-grade patterns and safeguards.

Write idiomatic Elixir code with OTP patterns, supervision trees, and Phoenix LiveView. Masters concurrency, fault tolerance, and distributed systems.

Delegates independent debugging tasks to parallel agents with isolated context, preserving the main session for coordination.

Orchestrate parallel scientist agents for comprehensive analysis with AUTO mode

Expert guidance for Mojo, the programming language by Modular that combines Python's usability with C-level performance. Helps developers write high-performance AI/ML code, optimize numerical computations with SIMD and parallelism, and gradually port Python code to Mojo for orders-of-magnitude speedups.