---
title: "How to Build on BlueField with DOCA Agent Skills"
description: "A practical how-to for using NVIDIA DOCA Agent Skills to generate BlueField code with verified APIs and hardware checks, reducing correction cycles and failed builds."
---

# How to Build on BlueField with DOCA Agent Skills

**Type:** [How to](https://yomu.fyi/visual-explainers/category/how-to.md)

![A vertical how-to diagram with four numbered checkpoints for building on BlueField with DOCA Agent Skills. Panels show detecting hardware, loading SKILL.md, generating code, and validating on hardware, connected by downward arrows and labeled with short phrases.](https://yomufyi.s3.us-east-1.amazonaws.com/visual-explainers/d4a6b551-c38f-459d-aac2-c5fe038af16b/image-859c39a0-6667-4ba7-9ec0-e97da3862381.webp)

> A practical how-to for using NVIDIA DOCA Agent Skills to generate BlueField code with verified APIs and hardware checks, reducing correction cycles and failed builds.

## Explanation

NVIDIA DOCA Agent Skills provide a machine-readable SKILL.md file with verified API signatures, hardware capability requirements, and build constraints for BlueField components like Flow, GPUNetIO, and PCC. This how-to walks through a checkpoint workflow: detect the target hardware, load the relevant skill, generate code against those constraints, then validate on real BlueField infrastructure instead of trusting a clean agent response. In a 65-prompt evaluation, agents without skills satisfied only 19% of graded checklist items, while agents with skills reached 100%; a side-by-side demo used 73% less handwritten code and 46% fewer hardware commands.

## FAQ

### Why do AI agents need DOCA Agent Skills to build on BlueField?

General-purpose agents often invent APIs or skip hardware checks. DOCA Agent Skills provide a machine-readable SKILL.md with verified API signatures, hardware requirements, and build constraints for components like Flow, GPUNetIO, and PCC. In a 65-prompt evaluation, agents without skills satisfied only 19% of graded checklist items, while those with skills satisfied 100%.

### Does using DOCA Agent Skills reduce manual work and correction cycles?

Yes. In a side-by-side demo, the agent with skills used 73% less handwritten code and 46% fewer hardware commands, and it satisfied 100% of graded checklist items versus 19% without skills. The skills reduce correction cycles by giving agents verified APIs and constraints up front, so they spend less time guessing and more time building stable code.

**Tags:** [AI Agents](https://yomu.fyi/topic/ai-agents.md), [BlueField](https://yomu.fyi/topic/bluefield.md), [Coding Agents](https://yomu.fyi/topic/coding-agents.md), [DOCA](https://yomu.fyi/topic/doca.md), [DPU](https://yomu.fyi/topic/dpu.md), [NVIDIA](https://yomu.fyi/topic/nvidia.md)

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### [Build Applications on NVIDIA BlueField Faster with NVIDIA DOCA Agent Skills](https://yomu.fyi/post/build-applications-on-nvidia-bluefield-faster-with-nvidia-doca-agent-s.md)
- Company: [NVIDIA](https://yomu.fyi/company/nvidia-developer-blog.md)
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General-purpose AI agents lack domain-specific knowledge for NVIDIA DOCA development, often inventing APIs or skipping hardware checks, leading to correction cycles. DOCA AI agent skills provide a structured, machine-readable specification in a SKILL.md file containing verified API signatures, hardware capability requirements, and build constraints for components like Flow, GPUNetIO, and PCC. In a 65-prompt evaluation, agents without skills satisfied only 19% of graded checklist items, while agents with skills satisfied 100% across all prompts. The skills reduce correction cycles; in a side-by-side demo, the with-skills agent used 73% less handwritten code and 46% fewer hardware commands. The skills are available on GitHub and enable developers to build faster, ship more stable code, and deploy with fewer unknowns on BlueField infrastructure.