Individual skill
mistral-performance-tuning
Analyze and improve Mistral latency and throughput from measured queue, transport, streaming, retrieval, and token evidence. Use when optimizing a slow integration. Trigger with "speed up Mistral", "reduce Mistral latency", or "tune Mistral throughput".
plugins/saas-packs/mistral-pack/skills/mistral-performance-tuning/SKILL.md
Source commit 0500b275e963c027f6b410e8c49c0446945c574e
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- Observed behavior
- Not checked yet
- Last checked
- Nov 12, 2026
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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
- mistral Declared skill tag
- performance Declared skill tag
- engineering Derived category
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SKILL.mdcore · 3,508 bytesreferences/official-docs.mddoc · 905 bytes
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# Mistral Performance Tuning
## Overview
Optimize the measured bottleneck rather than changing models or caching content by instinct. Separate queue, connection, first-event, generation, tool, and application time.
## Prerequisites
- A representative synthetic benchmark and explicit quality/safety acceptance.
- Content-free latency, token, queue, retry, and error instrumentation.
- Current workspace limits plus fixed model and request parameters.
## Current Contract
Chat, streaming, embeddings, batch, FIM, OCR, and audio differ in latency and batching. Compare only compatible operations and current account access.