Perf Hints
Improve C++ (C++11+) performance using Abseil “Performance Hints” (Jeff Dean & Sanjay Ghemawat): estimation + profiling, API/bulk design, algorithmic wins, cache-friendly memory layout, fewer allocations, fast paths, caching, and compiler-friendly hot loops. Use for performance code reviews, refactors, and profiling-driven optimizations. Keywords: performance, latency, throughput, cache, allocation, memory layout, InlinedVector, string_view, Span, flat_hash_map, pprof, perf.
Install
npx skills add omarkilani/perf-hints --skill perf-hintsgit clone --depth 1 https://github.com/omarkilani/perf-hints.git /tmp/perf-hints
mkdir -p ~/.claude/skills
cp -r /tmp/perf-hints/. ~/.claude/skills/perf-hintsPersonal skills live in ~/.claude/skills. Use .claude/skills in a project folder to share a skill with your team.
From the SKILL.md
# C++ Performance Hints (Jeff Dean & Sanjay Ghemawat style) This skill packages key ideas from Abseil’s **Performance Hints** document. Use it to: - review C++ code for performance risks - propose high-impact optimizations with **explicit tradeoffs** - design APIs/data structures that keep future optimizations possible - write an experiment plan (profile + microbenchmark) to validate changes ## Scope and guardrails - **Scope:** single-process / single-binary performance (CPU, memory, allocations, cache behavior). - **Do not:** change externally observable behavior unless the user explicitly agrees. - **Do not:** introduce undefined behavior, data races, or brittle “clever” micro-opts without evidence. - **Default philosophy:** choose the faster alternative **when it doesn’t materially harm readability or complexity**; otherwise, measure first. ## When to apply Use this skill when the task involves any of: - reducing **latency** or improving **throughput** - cutting **memory footprint** or **allocation rate** - improving **cache locality** / reducing cache misses - designing performant **APIs** (bulk ops, view types, threading model) - reviewing performance-sensitive C++ changes - interpreting a **flat profile** and finding next steps ## What to ask for (minimum inputs) If you don’t have enough information, ask for the smallest set that changes your recommendation quality: 1. **Goal:** latency vs throughput vs memory (and the SLO if any)
Details
- Skill name
perf-hints- Repository
- omarkilani/perf-hints
- Repo updated
- 21 December 2025
FAQ
What does the Perf Hints skill do?
Improve C++ (C++11+) performance using Abseil “Performance Hints” (Jeff Dean & Sanjay Ghemawat): estimation + profiling, API/bulk design, algorithmic wins, cache-friendly memory layout, fewer allocations, fast paths, caching, and compiler-friendly hot loops. Use for performance code reviews, refactors, and profiling-driven optimizations. Keywords: performance, latency, throughput, cache, allocation, memory layout, InlinedVector, string_view, Span, flat_hash_map, pprof, perf.
How do I install the Perf Hints skill?
skills CLI (Claude Code, Cursor, Codex and more): npx skills add omarkilani/perf-hints --skill perf-hints. Skills go in ~/.claude/skills (personal) or .claude/skills (project), and Claude loads them automatically when a task matches the description.
Is Perf Hints popular?
It lives in omarkilani/perf-hints, which has 9 GitHub stars and 2 forks.
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