yocto-project

yocto-project is a skill for Codex from prashantdivate/awesome-yocto-ai-agent-skills. It costs 117 tokens per session (809 once invoked), scanned A, original, MIT.

A guide for making changes in Yocto Project, OpenEmbedded, and Poky codebases. Yocto Project is a toolkit for building custom Linux systems for embedded devices.

In plain words
What is it for?
It helps create or modify layers, package recipes, system images, SDKs, board support, machine and distribution settings, kernels, and development-tool workflows.
Why use it?
It reduces version-specific mistakes by checking the project's release, existing metadata, and official documentation before changes.

Skill for Codex

Written for Codex: agents/openai.yaml present. Also seen: $skill-name invocation.

Good fit It helps create or modify layers, package recipes, system images, SDKs, board support, machine and distribution settings, kernels, and development-tool workflows.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/prashantdivate/awesome-yocto-ai-agent-skills/yocto-project
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add prashantdivate/awesome-yocto-ai-agent-skills --skill yocto-project
Clone the repo
git clone --depth 1 https://github.com/prashantdivate/awesome-yocto-ai-agent-skills

Made for: Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for yocto-project

README.md
[![agentmods](https://agentmods.dev/badge/skills/prashantdivate/awesome-yocto-ai-agent-skills/yocto-project/github.svg)](https://agentmods.dev/skills/prashantdivate/awesome-yocto-ai-agent-skills/yocto-project)
Your own site
<a href="https://agentmods.dev/skills/prashantdivate/awesome-yocto-ai-agent-skills/yocto-project"><img src="https://agentmods.dev/badge/skills/prashantdivate/awesome-yocto-ai-agent-skills/yocto-project/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for yocto-project

Your own site · 80×15
<a href="https://agentmods.dev/skills/prashantdivate/awesome-yocto-ai-agent-skills/yocto-project"><img src="https://agentmods.dev/badge/skills/prashantdivate/awesome-yocto-ai-agent-skills/yocto-project.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 117 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 809 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00117 $0.00809
Opus 5 $0.00059 $0.00404
Sonnet 5 $0.00023 $0.00162
Haiku 4.5 $0.00012 $0.00081

Measured 11d ago against content hash fd58cccbca63, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

yocto-project scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/yocto_doc_router.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

yocto-project/SKILL.md · 49 lines

How it starts

The opening of the file, as written. The whole thing — 49 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Yocto Project

Core Workflow

  1. Identify the target release before giving commands or editing metadata. Inspect branch names, conf/layer.conf, LAYERSERIES_COMPAT, bblayers.conf, README, kas*.yml, poky/meta/conf/distro/include/yocto-uninative.inc, or release tags.
  2. Prefer the workspace's own metadata over generic examples. Search existing layers for the same pattern before inventing a new recipe, image feature, class, override, or machine setting.
  3. Check official docs for version-sensitive behavior. Use yocto_doc_router.py with a topic name for a quick URL map, then open the relevant docs.
  4. Make the smallest layer-local change that fits Yocto conventions. Avoid editing poky/ or upstream layers unless the user explicitly asks for an upstream patch.
  5. Validate with BitBake-native tools whenever available: bitbake-layers, bitbake -e, bitbake -c listtasks, bitbake -c cleansstate, devtool, oe-pkgdata-util, or the existing project build wrapper.

Source Priority

Use official sources first:

  • Local workspace metadata and build configuration.
  • Yocto Project docs: https://docs.yoctoproject.org/
  • BitBake manual: https://docs.yoctoproject.org/bitbake/
  • Yocto source: https://git.yoctoproject.org/
  • OpenEmbedded source: https://git.openembedded.org/
  • OpenEmbedded Layer Index: https://layers.openembedded.org/

If the user asks for "latest", "current", "supported", "LTS", package versions, release notes, migration rules, or security status, verify online before answering.

Task Routing

  • For recipe syntax, tasks, overrides, fetchers, signatures, or .bbappend mechanics, use $bitbake-metadata as the primary skill and return here for Yocto workflow context.
  • For layers, images, SDKs, BSPs, distro/machine policy, build setup, package selection, or migration planning, stay in this skill.
  • For kernel recipe and device-tree work, inspect existing machine and kernel metadata first, then read the kernel development sections from the official docs.

Read the full file on GitHub · 49 lines

Files

What ships with it

4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 11d ago First seen · 49 lines · 117 tokens per session scan A fd58cccbca63

Subscribe to this mod's changes

yocto-project is a skill published in the GitHub repository prashantdivate/awesome-yocto-ai-agent-skills (4 stars, last pushed 2mo ago), licensed MIT. It adds 117 tokens to every session and 809 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Related

Other skills, from other repositories

eide

A build tool for EIDE projects, an embedded-development extension for Visual Studio Code. It finds EIDE project settings and builds firmware using ARM CC or GCC.

zhinkgit/embeddedskills · 151 tokens

workflow

A workflow skill for embedded-device projects that plans and runs building, flashing, debugging, observing, and diagnosis tasks.

zhinkgit/embeddedskills · 88 tokens

robot-perception

Comprehensive best practices for robot perception systems covering cameras, LiDARs, depth sensors, IMUs, and multi-sensor setups. Use this skill when working with RGB image processing, depth maps, point clouds, sensor calibration (intrinsic, extrinsic, hand-eye), object detection, semantic segmentation, 3D…

arpitg1304/robotics-agent-skills · 181 tokens

robotics-software-principles

Foundational software design principles applied specifically to robotics module development. Use this skill when designing robot software modules, structuring codebases, making architecture decisions, reviewing robotics code, or building reusable robotics libraries. Trigger whenever the user mentions SOLID principles…

arpitg1304/robotics-agent-skills · 140 tokens

robotics-design-patterns

Architecture patterns, design principles, and proven recipes for building robust robotics software. Use this skill when designing robot software architectures, choosing between behavioral frameworks, structuring perception-planning-control pipelines, implementing state machines, designing safety systems, or…

arpitg1304/robotics-agent-skills · 120 tokens

robotics-testing

Testing strategies, patterns, and tools for robotics software. Use this skill when writing unit tests, integration tests, simulation tests, or hardware-in-the-loop tests for robot systems. Trigger whenever the user mentions testing ROS nodes, pytest with ROS, launchtesting, simulation testing, CI/CD for robotics, test…

arpitg1304/robotics-agent-skills · 110 tokens