BBuf

BBuf/AI-Infra-Auto-Driven-SKILLS

Plugin Claude Code

Agent-ready LLM serving, SGLang model Day-0 support, profiling, capacity, SOTA optimization, incident triage, architecture, and PR-history skills.

BBuf/AI-Infra-Auto-Driven-SKILLS

Plugin Claude Code

Agent-ready playbooks for LLM serving benchmarks, SGLang model Day-0 support, capacity planning, profiling, SGLang/vLLM SOTA loops, code review, incidents, and PR-history dossiers.

BBuf/AI-Infra-Auto-Driven-SKILLS

Skill Claude CodeCodex

Use when an SGLang, vLLM, TensorRT-LLM, or TokenSpeed serving/model optimization task needs prior model-family PR evidence. Query and read the PR-driven history docs under model-pr-optimization-history before choosing source paths, fast paths, kernel/fusion ideas, regression risks, or validation lanes.

BBuf/AI-Infra-Auto-Driven-SKILLS

Skill Claude CodeCodex

Inspect LLM torch profiler traces at forward-pass, layer, and kernel level. Use when you need layer timings, anchor-kernel boundaries, representative kernel flows, or Perfetto time ranges.

BBuf/AI-Infra-Auto-Driven-SKILLS

Skill Claude CodeCodex

Framework-independent LLM serving benchmark skill for comparing SGLang, vLLM, TensorRT-LLM, TokenSpeed, or another serving framework. Use when a user wants to find the best deployment command for one model across multiple serving frameworks under the same workload, GPU budget, and latency SLA.

BBuf/AI-Infra-Auto-Driven-SKILLS

Skill Claude CodeCodex

Parse SGLang/vLLM startup logs to explain GPU memory use and request capacity. Use for KV cache budget, mem-fraction-static comparisons, OOM triage, and max-concurrency estimates.

BBuf/AI-Infra-Auto-Driven-SKILLS

Skill Claude CodeCodex

Unified LLM torch-profiler triage skill for sglang, vllm, TensorRT-LLM, and TokenSpeed. Use it to inspect an existing trace.json(.gz) or profile directory, or to drive live profiling against a running server when supported and return one three-table report with kernel, overlap-opportunity, and fuse-pattern tables.

BBuf/AI-Infra-Auto-Driven-SKILLS

Skill Claude CodeCodex

Return public original model architecture diagrams for user-specified LLM, VLM, MoE, diffusion, OCR, and SGLang/sgl-cookbook model families. Use when the user asks for a model structure chart, architecture diagram, or rendered image link for a specific model such as DeepSeek, GLM, Qwen, Kimi, MiniMax, Step, Hunyuan…

BBuf/AI-Infra-Auto-Driven-SKILLS

Skill Claude CodeCodex

Build an operator-level compute template for an LLM and estimate FLOPs/MFU for a serving shape. Use when you need tensor shapes, per-op FLOPs, kernel-to-op MFU mapping, or parallelism what-if analysis.

BBuf/AI-Infra-Auto-Driven-SKILLS

Skill Claude CodeCodex

Build or audit an evidence-driven SGLang Day-0 support program for a new LLM, VLM, MoE, hybrid-attention, or speculative-decoding model. Use when Codex needs to map a model architecture into SGLang runtime work, design a public support PR DAG, create validation and release gates, sanitize private development evidence…

BBuf/AI-Infra-Auto-Driven-SKILLS

Skill Claude CodeCodex

Perform SGLang code review in the style of human maintainers by consulting the full non-agent PR review episode corpus from project start through 2026-07-27, including inline review threads, top-level PR comments, review submissions, original multilingual text, and multi-round discussions. Use when reviewing SGLang…

BBuf/AI-Infra-Auto-Driven-SKILLS

Skill Claude CodeCodex

Replay-first debug flow for SGLang serving problems. Use when a live or recent server shows health-check failures, latency or throughput regressions, queue growth, timeouts, distributed stalls, crash dumps, wrong outputs after deploys, or PD/EP/HiCache issues, and the job is to turn the problem into a replay plus the…

BBuf/AI-Infra-Auto-Driven-SKILLS

Skill Claude CodeCodex

Run an autonomous Humanize-governed SGLang SOTA performance loop for one LLM model: first perform a fixed fair SGLang benchmark against the requested comparison framework set, then start one RLCR loop that repeatedly decides the gap, profiles the current bottleneck, runs layer/kernel pipeline analysis, patches SGLang…

BBuf/AI-Infra-Auto-Driven-SKILLS

Skill Claude CodeCodex

Run an autonomous Humanize-governed vLLM SOTA performance loop for one LLM model: first perform the fixed fair vLLM/SGLang/TensorRT-LLM deployment search and benchmark, then start one RLCR loop that repeatedly decides the gap, profiles the current bottleneck, runs layer/kernel pipeline analysis, patches vLLM code…