Individual skill
openrouter-performance-tuning
Optimize OpenRouter request latency and throughput. Use when building real-time applications, reducing TTFT, or scaling request volume. Triggers: 'openrouter performance', 'openrouter latency', 'openrouter speed', 'optimize openrouter throughput'.
plugins/saas-packs/openrouter-pack/skills/openrouter-performance-tuning/SKILL.md
Source commit 0500b275e963c027f6b410e8c49c0446945c574e
What was checked
- Matches the observed repository HEAD
- Yes
- Scanner rules are current
- No
- Repository scan complete
- No
- Skill scan complete
- No
- Observed behavior
- Not checked yet
- Last checked
- Nov 12, 2026
These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.
Install this skill
Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.
An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.
Repository context
- Repository stars (not skill ratings)
- 2,916
- Repository last updated
- Nov 12, 2026
- License
- MIT
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- ai Repository topic
- automation Repository topic
- claude-code Repository topic
- devops Repository topic
- mcp Repository topic
- ai-agents Repository topic
- anthropic Repository topic
- claude-code-plugins Repository topic
- developer-tools Repository topic
- llm Repository topic
- saas Declared skill tag
- openrouter Declared skill tag
- performance Declared skill tag
- latency Declared skill tag
- optimization Declared skill tag
- engineering Derived category
Files and excerpt
File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.
Browse files
SKILL.mdcore · 9,721 bytesSKILL.mdcore · 9,721 bytesSKILL.mdcore · 9,721 bytesSKILL.mdcore · 9,721 bytesSKILL.mdcore · 9,721 bytesreferences/batch-processing.mddoc · 902 bytesreferences/best-practices-summary.mddoc · 810 bytesreferences/caching-strategies.mddoc · 2,354 bytesreferences/configuration-tuning.mddoc · 1,013 bytesreferences/errors.mddoc · 478 bytesreferences/examples.mddoc · 3,789 bytesreferences/latency-optimization.mddoc · 1,245 bytesreferences/model-selection-for-speed.mddoc · 1,063 bytesreferences/monitoring-&-profiling.mddoc · 1,893 bytesreferences/request-optimization.mddoc · 1,511 bytes
Read excerpt
# OpenRouter Performance Tuning
## Overview
OpenRouter adds minimal overhead (~50-100ms) to direct provider calls. Most latency comes from the upstream model. Key levers: model selection (smaller = faster), streaming (lower TTFT), parallel requests, prompt size reduction, and provider routing to faster infrastructure. This skill covers benchmarking, streaming optimization, concurrent processing, and connection tuning.
## Prerequisites
- An OpenRouter API key (`sk-or-v1-...`) exported as `OPENROUTER_API_KEY` — see the `openrouter-install-auth` skill for setup
- Python 3.8+ with the OpenAI SDK (`openai` package) — the examples use both the sync `OpenAI` client and `AsyncOpenAI` for parallel processing
- Credits on the key if you benchmark paid models like `anthropic/claude-3.5-sonnet`; a `:free` model is enough to validate the benchmark harness itself
- `HTTP-Referer` / `X-Title` header values for your app (set in every client constructor here)
## Instructions
