Skill Claude CodeCodex
Code instrumentation for timing workloads. Two scenarios: (1) Training loop — inject manual timing to report per-iteration latency, throughput (samples/sec), and data load time. (2) Standalone kernel/op — write CUDA event timing code with warmup, per-iteration statistics, and anti-pattern avoidance. Also covers NVTX…
Skill Claude CodeCodex
A benchmarking workflow for comparing a system that separates incoming requests into hot and cold pools with a shared cache-aware system when serving large language models. It can optionally reproduce the test on Kubernetes using kind, a local Kubernetes cluster.
Skill Claude CodeCodex
Use this skill any time a .pptx file is involved in any way — as input, output, or both. This includes: creating slide decks, pitch decks, or presentations; reading, parsing, or extracting text from any .pptx file (even if the extracted content will be used elsewhere, like in an email or summary); editing, modifying…
Skill Claude CodeCodex
Build throwaway prototypes to validate a design before production code. Terminal state-machine for routing/cache/overload logic, or UI variants on one route. Use when prototyping, sanity-checking a state model, exploring routing policies, or saying "prototype this" / "let me play with it".
Skill Claude CodeCodex
Two-axis branch review — Standards (CONTRIBUTING.md, CONTEXT, ADRs) and Spec (issue/PRD/plan). Runs parallel sub-agents on git diff. Use before PR, when reviewing a branch, or after implementing routing/benchmark/harness changes.
Skill Claude CodeCodex
Research-before-coding workflow. Search the repo, framework APIs, libraries, and existing patterns before writing custom code. Use when adding a feature to a mature framework (vLLM, SGLang, TRT-LLM, benchmark harness), before creating a utility/helper, or when the user asks to "add X functionality".
Skill Claude CodeCodex
Scaffold docs/agents/ in a target repo — issue tracker (GitHub/GitLab/local), triage labels, domain doc layout. Run once per repo before to-issues, review, or other skills that read docs/agents/issue-tracker.md.
Skill Claude CodeCodex
Simplify and refine recently changed code for clarity, reuse, and efficiency while preserving behavior. Use before opening a PR, after implementing a feature in a mature framework, or when asked to clean up a branch diff.
Skill Claude CodeCodex
Test-driven development with red-green-refactor loop. Use when user wants to build features or fix bugs using TDD, mentions "red-green-refactor", wants integration tests, asks for test-first development, or writes tests for benchmark harnesses, profiling scripts, or inference automation.
Skill Claude CodeCodex
Break a plan, spec, or PRD into independently-grabbable GitHub issues using tracer-bullet vertical slices. Use when converting a plan into issues, splitting a benchmark study / routing feature / multi-PR infra work into tickets, or preparing AFK-agent-ready tasks.
Skill Claude CodeCodex
Before claiming work is complete, fixed, or passing — run verification commands and cite evidence. Use before commit/PR, after implementing features or benchmark fixes, when saying tests pass or bug is fixed.
Skill Claude CodeCodex
Write bite-sized implementation plans from an approved spec. Use after brainstorming or grill-with-docs, before touching code on multi-step features in mature codebases (vLLM, SGLang, inference harness, serving stack patches).
Skill Claude CodeCodex
Review pull requests and code changes for high-performance Python, PyTorch, CUDA, and distributed systems using a correctness-first P0-P4 rubric. Use when the user asks for a strict production-grade review, especially for inference, GPU, concurrency, or performance-sensitive code.
Skill Claude CodeCodex
Write GPU kernels using NVIDIA CuTe DSL (CUTLASS 4.x Python API) — NOT for Triton, CUDA C++, or conceptual-only questions. Covers element-wise kernels, GEMM patterns, reductions, memory hierarchy (global/shared/register/TMA), MMA tensor core ops, software pipelining, and framework integration. Use when implementing…
Skill Claude CodeCodex
Build operator-level compute templates from model config; estimate FLOPs, MFU, tensor shapes, and TP/EP what-if for serving shapes. Use before benchmarking to sanity-check compute bounds or when writing REPORT.md theoretical sections.
At most 3 mods per repository are shown here, and a mod shipped inside a plugin is left to that plugin's page — the rest are on their repository pages: