contribute-workbench-image

contribute-workbench-image is a skill for Claude Code, Codex from nebius/nebius-physical-ai. It costs 48 tokens per session (913 once invoked), scanned A, original, Apache-2.0.

A contribution process for adding or changing an NPA workbench container image, including licensing checks, trusted builds, validation, and release promotion. A container image is a packaged environment used to run a service.

In plain words
What is it for?
Use it to review, build, validate, and publish workbench images safely.
Why use it?
It separates untrusted contributor code from official builds and checks that the released image matches the tested one.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to review, build, validate, and publish workbench images safely.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/nebius/nebius-physical-ai/contribute-workbench-image
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 nebius/nebius-physical-ai --skill contribute-workbench-image
Clone the repo
git clone --depth 1 https://github.com/nebius/nebius-physical-ai

Made for: Claude Code, 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 contribute-workbench-image

README.md
[![agentmods](https://agentmods.dev/badge/skills/nebius/nebius-physical-ai/contribute-workbench-image/github.svg)](https://agentmods.dev/skills/nebius/nebius-physical-ai/contribute-workbench-image)
Your own site
<a href="https://agentmods.dev/skills/nebius/nebius-physical-ai/contribute-workbench-image"><img src="https://agentmods.dev/badge/skills/nebius/nebius-physical-ai/contribute-workbench-image/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 contribute-workbench-image

Your own site · 80×15
<a href="https://agentmods.dev/skills/nebius/nebius-physical-ai/contribute-workbench-image"><img src="https://agentmods.dev/badge/skills/nebius/nebius-physical-ai/contribute-workbench-image.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 48 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 913 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00048 $0.00913
Opus 5 $0.00024 $0.00456
Sonnet 5 $0.00010 $0.00183
Haiku 4.5 $0.00005 $0.00091

Measured 8d ago against content hash 04e89505c88c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

contribute-workbench-image 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 8d 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.

skills/workflows/contribute-workbench-image/SKILL.md · 96 lines

How it starts

The opening of the file, as written. The whole thing — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Contribute A Workbench Image

Keep source contribution, trusted building, and supported release promotion as separate approval boundaries. Public development pushes are irreversible public disclosures even when their tags are later deleted.

Governing Rules

Before acting, read:

  • skills/atomic/audit-container-docs/SKILL.md
  • skills/atomic/secure-image-build/SKILL.md
  • skills/atomic/solution-licensing/SKILL.md
  • skills/atomic/third-party-eula-preflight/SKILL.md
  • skills/atomic/build-and-push-image/SKILL.md
  • skills/atomic/testing-conventions/SKILL.md
  • docs/workbench/container-packaging.md
  • docs/workbench/container-image-catalog.md
  • docs/workbench/contributing-a-containerized-solution.md

Use npa/.venv/bin/python. Keep live infrastructure identifiers, credentials, and customer data out of commits, workflow inputs, logs, and PR prose.

Contributor Boundary

An external contributor supplies reproducible code and evidence in an unprivileged fork. Never expose official package credentials to fork-controlled code or run untrusted code in privileged pull_request_target/workflow_run jobs. Maintainers rebuild the reviewed commit through the repository workflow.

Add or update the Dockerfile/build script, packaging contract, image resolver and version source, CLI/SDK/workflow surfaces, golden evaluation, tests, docs, and relevant skill together. Use non-root final stages, digest-pinned bases when resolvable, and runtime fetch for gated or non-redistributable material.

Classify source, baked runtime, weights, data, caches, and outputs separately. Only redistribution: public images may enter official GHCR. Restricted images remain build-your-own in an operator registry.

Trusted Public Development Build

After review, build the exact trusted full SHA with the manual publish-public-images.yml workflow on a ref whose code contains that workflow:

gh workflow run publish-public-images.yml \
  --ref <reviewed-branch> \
  -f dry_run=true \
  -f development_sha=<full-git-sha> \
  -f build_development_tools=<tool> \
  -f tool=<tool>

Read the full file on GitHub · 96 lines

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. 8d ago First seen · 96 lines · 48 tokens per session scan A 04e89505c88c

Subscribe to this mod's changes

contribute-workbench-image is a skill published in the GitHub repository nebius/nebius-physical-ai (28 stars, last pushed yesterday), licensed Apache-2.0. It adds 48 tokens to every session and 913 once invoked, about $0.0002 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 2026-09-03.

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