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.
npx skills add prashantdivate/awesome-yocto-ai-agent-skills --skill yocto-image-analysisgit clone --depth 1 https://github.com/prashantdivate/awesome-yocto-ai-agent-skillsWrote 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.
[](https://agentmods.dev/skills/prashantdivate/awesome-yocto-ai-agent-skills/yocto-image-analysis)<a href="https://agentmods.dev/skills/prashantdivate/awesome-yocto-ai-agent-skills/yocto-image-analysis"><img src="https://agentmods.dev/badge/skills/prashantdivate/awesome-yocto-ai-agent-skills/yocto-image-analysis/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.
<a href="https://agentmods.dev/skills/prashantdivate/awesome-yocto-ai-agent-skills/yocto-image-analysis"><img src="https://agentmods.dev/badge/skills/prashantdivate/awesome-yocto-ai-agent-skills/yocto-image-analysis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00080 | $0.00401 |
| Opus 5.5 | $0.00032 | $0.00160 |
| Sonnet 5.5 | $0.00016 | $0.00080 |
| Haiku 4.5 | $0.00008 | $0.00040 |
Grade A, and why
yocto-image-analysis 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 2mo ago.
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.
What it actually says
Yocto Image Analysis
Workflow
- Identify image recipe,
MACHINE,DISTRO, package format, and actual deploy directory. - Collect image manifests, package data, dependency graphs, and buildhistory when available.
- Trace inclusion from image recipe, packagegroups, features, runtime dependencies, recommends, and distro/machine policy.
- Estimate "what-if" changes by checking dependency chains before editing metadata.
- Route recipe changes to
$yocto-recipe-maintenanceand build failures to$yocto-build-debug.
Commands
oe-pkgdata-util list-pkgs
oe-pkgdata-util find-path <path>
oe-pkgdata-util lookup-recipe <pkg>
oe-pkgdata-util list-pkg-files <pkg>
bitbake -g <image>
bitbake -e <image>
Use find_image_package_refs.py with a build/repo path and package name for a quick text scan across manifests, package data, and dependency graph files.
References
- image-analysis-playbook.md: why/what-if/image-size workflows.
Guardrails
- Do not assume a package is directly listed in
IMAGE_INSTALL; it may arrive through packagegroups, recommends, shlib deps, or image features. - Do not remove packages from an image without checking runtime dependencies and service impact.
- Do not optimize size blindly; preserve required update, debug, recovery, and compliance artifacts.
What ships with it
3 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.
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.
- 2mo ago First seen · 38 lines · 80 tokens per session scan A 6be09e4c5c3c
yocto-image-analysis is a skill published in the GitHub repository prashantdivate/awesome-yocto-ai-agent-skills (4 stars, last pushed 4mo ago), licensed MIT. It adds 80 tokens to every session and 401 once invoked, about $0.0003 per session on Opus 5.5. 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.
yocto-image-analysis compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| yocto-image-analysisprashantdivate/awesome-yocto-ai-agent-skills | Skill | 4 | 4mo ago | MIT | A | 80 | Codex |
| eidezhinkgit/embeddedskills | Skill | 785 | 18d ago | MIT | A | 151 | Claude Code |
| workflowzhinkgit/embeddedskills | Skill | 785 | 18d ago | MIT | A | 88 | Claude Code |
| lov-migrate-camera-medialovstudio/skills | Skill | 72 | 3d ago | MIT | A | 86 | Claude Code |
| robot-perceptionarpitg1304/robotics-agent-skills | Skill | 393 | 2mo ago | Apache-2.0 | A | 181 | Claude Code, Codex |
| robotics-software-principlesarpitg1304/robotics-agent-skills | Skill | 393 | 2mo ago | Apache-2.0 | A | 140 | Claude Code, Codex |
| robotics-design-patternsarpitg1304/robotics-agent-skills | Skill | 393 | 2mo ago | Apache-2.0 | A | 120 | Claude Code, Codex |