Official agent skill

I4h Workflow E2E

by NVIDIA in NVIDIA/skills

Run the maintained workflow data-to-policy pipeline from recording through checkpoint validation.

OfficialApache-2.0Auto-check passedTesting & QA

Install I4h Workflow E2E

skills CLI
$ npx skills add NVIDIA/skills --skill i4h-workflow-e2e -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install NVIDIA/skills i4h-workflow-e2e --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/NVIDIA/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/i4h-workflow-e2e .claude/skills/i4h-workflow-e2e && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
i4h-workflow-e2e
GitHub stars
3.5k
Used in
1 other repo
Token cost
~1.1k tokens
SKILL.md length
437 words
Files
5
Skills in repo
380
Repo updated
First seen
Licence
Apache-2.0

At a glance

Run the maintained workflow data-to-policy pipeline from recording through checkpoint validation.

  • Works in 4 steps: Resolve the base checkout and policy… → Require a successful driver dry-run. → Execute the maintained driver in the… → …
  • Full end-to-end requests
  • SKILL.md covers Purpose, Instructions, Resolve the checkout and Dry-run first, plus 7 more sections
  • Calls git; reaches github.com

What it does

I4h Workflow E2E is an agent skill from NVIDIA/skills, published by the product's own GitHub organization. Run the maintained workflow data-to-policy pipeline from recording through checkpoint validation. Use for full end-to-end requests; do not use for one individual stage.

Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files (for example `BENCHMARK.md`, `evals/evals.json` and `skill-card.md`).

It sits in Testing & QA, covering End-to-end testing. The repository describes itself as: Agent Skills for NVIDIA products — install into Claude Code, Codex, and other coding agents to run Physical AI, robotics, simulation, CUDA, and RAG workflows end to end. The licence is Apache-2.0.

When your agent uses it

  • Full end-to-end requests
  • Do not use for one individual stage

Example prompts

  • “/i4h-workflow-e2e”

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. Resolve the base checkout and policy workflow.
  2. Require a successful driver dry-run.
  3. Execute the maintained driver in the foreground.
  4. Inspect every stage artifact before reporting completion.

What it can do on your machine

Read from SKILL.md and the folder at commit 67a13c0. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • git

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • github.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

I4h Workflow E2E loads about 1.1k tokens when it runs. Until then it costs about 46 tokens; SKILL.md has 437 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~46
When it runs · the whole SKILL.md, loaded when a task matches
~1.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from NVIDIA/skills at commit 67a13c0, republished under its Apache-2.0 licence (© NVIDIA). 437 words, ~1,132 tokens.

Download SKILL.mdSave it as .claude/skills/i4h-workflow-e2e/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
i4h-workflow-e2e
description
Run the maintained workflow data-to-policy pipeline from recording through checkpoint validation. Use for full end-to-end requests; do not use for one individual stage.
license
Apache-2.0
metadata.author
Isaac for Healthcare Team <isaac-for-healthcare-support@nvidia.com>
metadata.version
0.8.0
metadata.verification-request
2026-09-15
metadata.tags
isaac-for-healthcare, i4h, robotics, data-to-policy

Run the Workflow End-to-End Pipeline

Purpose

Use the maintained driver so stage resolution, artifacts, logs, and checkpoint handoff stay consistent with current workflow/task manifests.

Instructions

  1. Resolve the base checkout and policy workflow.
  2. Require a successful driver dry-run.
  3. Execute the maintained driver in the foreground.
  4. Inspect every stage artifact before reporting completion.

Resolve the checkout

bash
export I4H_WORKFLOWS_REPO_URL="${I4H_WORKFLOWS_REPO_URL:-https://github.com/isaac-for-healthcare/i4h-workflows}"
I4H_REPO_DIR_NAME="${I4H_WORKFLOWS_REPO_URL%/}"
I4H_REPO_DIR_NAME="${I4H_REPO_DIR_NAME##*/}"
I4H_REPO_DIR_NAME="${I4H_REPO_DIR_NAME##*:}"
I4H_REPO_DIR_NAME="${I4H_REPO_DIR_NAME%.git}"
[ -n "$I4H_REPO_DIR_NAME" ] || { echo "Cannot derive a checkout name from I4H_WORKFLOWS_REPO_URL" >&2; exit 2; }
ROOT="${I4H_WORKFLOWS:-$(git rev-parse --show-toplevel 2>/dev/null)}"
if [ ! -d "$ROOT/workflows/i4h_workflows" ]; then
  ROOT="${I4H_WORKFLOWS:-$HOME/$I4H_REPO_DIR_NAME}"
  [ -d "$ROOT/workflows/i4h_workflows" ] || git clone "$I4H_WORKFLOWS_REPO_URL" "$ROOT"
fi
export I4H_WORKFLOWS="$ROOT"
cd "$ROOT"

Treat this resolver as part of the skill contract: a hosted copy may run outside the base repository, so never assume the current checkout contains workflows/i4h_workflows. I4H_WORKFLOWS_REPO_URL selects the clone source. When I4H_WORKFLOWS is unset, derive the fallback directory from that URL; set I4H_WORKFLOWS only to reuse or choose a specific destination. Never replace an existing checkout.

Require the workflow's policy mode. The driver discovers the remote task, embodiment, task text, and trainability from live workflow/task manifests.

Dry-run first

bash
./scripts/e2e/run.sh --env <workflow> --dry-run

Require exit status 0 and inspect every printed command and artifact path. The dry-run is the source of truth for current stages and backend ownership.

Run in the foreground

bash
./scripts/e2e/run.sh --env <workflow>

Use --run-dir only when the caller needs a specific location. Apply --skip-mimic, --skip-annotate, --skip-replay, or --skip-viz only when the user explicitly omits that optional stage or a documented smoke profile requires it.

Keep the driver as this agent's foreground tool call. Do not use a subagent, monitor task, shell backgrounding, nohup, tmux, or a detached process. Poll until exit.

The driver performs full setup, then owns its stage sequence, timestamped run directory, runs/.latest link, and per-stage logs. Do not replace it with a manually assembled subset.

Show full SKILL.md (185 more words)Show less

Verify

On success, inspect the printed summary and artifacts:

  • policy recording
  • expanded/filtered HDF5 as applicable
  • visible replay result when enabled
  • LeRobot metadata, parquet, and videos
  • visualizer URL/content when enabled
  • training logs and exact checkpoint when trainable
  • checkpoint validation recording and final success summary

On failure, stop at the first failed stage, inspect that stage's log, preserve the run directory, and repair the owning stage before rerunning. Do not skip a required failure merely to obtain a green summary. Stop leftovers with ./stop.sh all.

Troubleshooting

Use the first failed stage and its log to choose the owning stage skill. Preserve the run directory and rerun only after that stage verifies its output.

Prerequisites

Require a policy workflow plus host, simulator, backend, VLM, dataset, training, and visualization dependencies for every enabled stage.

Limitations

The pipeline supports only workflows with a policy mode; inference-only Tasks skip fine-tuning and checkpoint validation.

Examples

  • Run end-to-end smoke pipeline for scissor pick-and-place. → dry-run, execute the driver, and report each recording-to-validation stage.

Completion gate

Report workflow/task/embodiment/trainability, dry-run result, run directory, every stage outcome and skip, dataset/visualizer/checkpoint/verification artifacts, final exit status, and cleanup state.

© NVIDIA, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 4 other files in skills/i4h-workflow-e2e of NVIDIA/skills.

  • SKILL.md
  • BENCHMARK.md
  • evals/evals.json
  • skill-card.md
  • skill.oms.sig

Open the folder on GitHubat commit 67a13c0

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in NVIDIA/skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

I4h Workflow E2E next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

I4h Workflow E2E compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
I4h Workflow E2E this skillNVIDIA/skills3.5k1 repos~1.1kAutomated safety check: PassApache-2.0
Web Application Testinganthropics/skills180k51 repos~966Automated safety check: PassApache-2.0
TDD WorkflowhellangleZ/burn-in-cceverywhere-ralph11211 repos~2.4kAutomated safety check: PassNone
Uloop Replay Inputkurotu/VRCQuestTools3733 repos~615Automated safety check: PassMIT
Ui4 Convert Testspayloadcms/payload45k—~3.5kAutomated safety check: PassMIT
E2Estackia/rtp2httpd2.2k—~517Automated safety check: PassGPL-2.0

Similar skills

  • Web Application Testing

    anthropics/skills

    Official

    Tests local web applications with Python Playwright scripts, checking frontend behavior, capturing screenshots and reading browser console logs.

    180k GitHub starsUsed in 51 repos~966 tokens
    Testing & QAAuto-check passed
  • TDD Workflow

    hellangleZ/burn-in-cceverywhere-ralph

    A skill your agent uses when writing new features, fixing bugs, or refactoring code.

    112 GitHub starsUsed in 11 repos~2.4k tokens
    Testing & QAAuto-check passed
  • Uloop Replay Input

    kurotu/VRCQuestTools

    Replay recorded PlayMode keyboard and mouse input. An agent skill from kurotu/VRCQuestTools.

    373 GitHub starsUsed in 3 repos~615 tokens
    Testing & QAAuto-check passed
  • Ui4 Convert Tests

    payloadcms/payload

    A skill your agent uses when UI changes are complete and e2e tests need updating.

    45k GitHub stars~3.5k tokensUpdated today
    Testing & QAAuto-check passed
  • E2E

    stackia/rtp2httpd

    Write, run, review, or debug rtp2httpd E2E tests and their harness in e2e/ and scripts/run-e2e.sh.

    2.2k GitHub stars~517 tokensUpdated 5 days ago
    Testing & QAAuto-check passed
  • Moav E2E

    MotherofallVPNs/MoaV

    Run and debug MoaV's end-to-end tests — real protocol connectivity (client-test.sh) and the moav CLI smoke test — against a LIVE server, via the self-hosted e2e workflow or a local test VPS.

    448 GitHub stars~1.9k tokensUpdated today
    Testing & QAAuto-check: notes

More from NVIDIA/skills

All 380 skills in this repo
  • Official

    A skill your agent uses when the user wants to deploy, run, debug, tear down, or call the REST API of the RTVI-CV 2D detection / tracking microservice.

    3.5k GitHub starsUsed in 1 repo~4.5k tokens
    Auto-check passed
  • Official

    Generates, validates, compares and explains HOLOLINK_def.svh macro files for the HSB IP, using bundled Python scripts and asking before it writes anything.

    3.5k GitHub stars~2.9k tokensUpdated today
    Auto-check passed
  • Official

    Runs and validates an end-to-end Mission Control demo in a locally installed Isaac Sim, with a Nova Carter robot driven through a Python server.

    3.5k GitHub stars~4.8k tokensUpdated today
    Auto-check passed
  • Orchestrates defect image generation for PCBA, metal surface and glass inspection with NVIDIA Cosmos AnomalyGen on OSMO, from cold-start Day 0 to real-photo Day 1 labeling.

    3.5k GitHub stars~5k tokensUpdated today
    Auto-check: notes
  • Orchestrates video data augmentation and auto-labeling workflows on OSMO, from flow selection and preflight checks to submission, monitoring and output download.

    3.5k GitHub stars~4.7k tokensUpdated today
    Auto-check: notes
  • Official

    Runs NVIDIA TAO Data Services KPI analysis on object detection results, comparing predictions to ground truth and writing per-class precision, recall and AP to a CSV.

    3.5k GitHub stars~2.7k tokensUpdated today
    Auto-check: notes

Categories

Questions about I4h Workflow E2E

What does I4h Workflow E2E do?

Run the maintained workflow data-to-policy pipeline from recording through checkpoint validation. I4h Workflow E2E is an agent skill from NVIDIA/skills, published by the product's own GitHub organization. Run the maintained workflow data-to-policy pipeline from recording through checkpoint validation.

When should I use I4h Workflow E2E?

I4h Workflow E2E fits situations like: full end-to-end requests; do not use for one individual stage.

How do I install I4h Workflow E2E in Claude Code?

Run `npx skills add NVIDIA/skills --skill i4h-workflow-e2e -a claude-code`. Or copy the skill folder (skills/i4h-workflow-e2e in NVIDIA/skills) into .claude/skills/i4h-workflow-e2e in your project. Claude Code loads it when a task matches its description.

How do I install I4h Workflow E2E in Codex?

Run `npx skills add NVIDIA/skills --skill i4h-workflow-e2e -a codex`. Or copy the skill folder (skills/i4h-workflow-e2e in NVIDIA/skills) into .agents/skills/i4h-workflow-e2e in your project. Codex loads it when a task matches its description.

Can I use I4h Workflow E2E in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add NVIDIA/skills --skill i4h-workflow-e2e -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/i4h-workflow-e2e, .gemini/skills/i4h-workflow-e2e, .github/skills/i4h-workflow-e2e and .opencode/skills/i4h-workflow-e2e in your project.

What does I4h Workflow E2E need to run?

Going by SKILL.md and its folder, I4h Workflow E2E needs the command-line tools its instructions call (git).

Does I4h Workflow E2E access the network?

SKILL.md names 1 domain. In commands or code: github.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is I4h Workflow E2E safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does I4h Workflow E2E use?

I4h Workflow E2E is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does I4h Workflow E2E use?

About 1.1k tokens (SKILL.md is roughly 4.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to I4h Workflow E2E?

Skills that share tags, products or a category with I4h Workflow E2E: Web Application Testing (anthropics/skills, 180k stars), TDD Workflow (hellangleZ/burn-in-cceverywhere-ralph, 112 stars), Uloop Replay Input (kurotu/VRCQuestTools, 373 stars) and Ui4 Convert Tests (payloadcms/payload, 45k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains I4h Workflow E2E?

NVIDIA (a GitHub organization, an official publisher) maintains it in NVIDIA/skills, which has 3,539 GitHub stars. The repository holds 380 skills in this directory. The repository was last updated on October 7, 2026.

Source: NVIDIA/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.