NemoClaw: Skill for Claude Code

.agents/skills/nemoclaw-maintainer-classify-ci-failure/SKILL.md

nemoclaw-maintainer-classify-ci-failure is a skill for Claude Code, Codex from NVIDIA/NemoClaw. It costs 33 tokens per session (719 once invoked), scanned A, original, Apache-2.0.

A read-only tool for classifying one failed NemoClaw GitHub Actions job from bounded, redacted logs and optional saved files. GitHub Actions is GitHub’s system for automatically running builds and tests.

In plain words
What is it for?
Use it to diagnose a failed job, identify likely failure types, and use retained artifact evidence when available.
Why use it?
It turns a failed CI job into a limited diagnostic without exposing unrestricted logs or making changes to GitHub.

Skill for Claude CodeCodex ✓ vendor

Written for Claude Code and Codex: user-invocable in frontmatter, but also agents/openai.yaml present. Also seen: installed under .agents/ (shared by several agents).

This is NVIDIA/NemoClaw's own configuration. It tells Claude Code and Codex how to work on NemoClaw itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything NemoClaw configures →

About the project

NVIDIA/NemoClaw is an open-source reference stack for running supported AI agents inside NVIDIA OpenShell sandboxes with managed inference, network policies, integrations, snapshots, and lifecycle controls. It is used to run agents such as OpenClaw, Hermes, and LangChain Deep Agents with administrative and security controls. Catalogue add-ons guide coding agents through NemoClaw workflows.

NVIDIA/NemoClaw · 22,871 stars · on GitHub · docs.nvidia.com

Reuse

Borrowing it

Nothing to install: this file belongs to NVIDIA/NemoClaw. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/NVIDIA/NemoClaw/main/.agents/skills/nemoclaw-maintainer-classify-ci-failure/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/NVIDIA/NemoClaw

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.

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README.md
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Your own site
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Per session 33 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 719 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
  • Snyk warn 7 Sept 2026
  • 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 $0.00033 $0.00719
Opus 5.5 $0.00013 $0.00288
Sonnet 5.5 $0.00007 $0.00144
Haiku 4.5 $0.00003 $0.00072

Measured 27d ago against content hash f95d08bfe353, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

nemoclaw-maintainer-classify-ci-failure 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 27d 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.

.agents/skills/nemoclaw-maintainer-classify-ci-failure/SKILL.md · 32 lines

What it actually says

Classify a CI Failure

When the failed job is part of E2E, first load Audit E2E Assertions. This classifier can locate the failure signature. Its bounded output does not replace the complete log review and itemized source audit required before an E2E repair push or expensive rerun.

Run the classifier from a NemoClaw checkout:

node --no-warnings \
  .agents/skills/nemoclaw-maintainer-classify-ci-failure/scripts/classify-ci-failure.mts \
  --workdir "$PWD" --job-id <job-id>

The repository is fixed to NVIDIA/NemoClaw. Optional flags include --artifact-name. --max-lines accepts integers from 1 through 500 and defaults to 120. --clip-mode accepts head or tail and defaults to tail.

The script uses authenticated gh reads. It performs no GitHub writes. It bounds and redacts log output. When an artifact is selected, it bounds pagination, compressed and expanded sizes, entries, paths, file reads, and reported failures. It rejects malformed ZIPs, links, special files, duplicate or unsafe paths, ambiguous listings, and size mismatches. Temporary files use process-owned directories under a fixed private root. The classifier attempts to remove them directly through the filesystem after success or failure. If removal fails, the classifier exits nonzero. It reports a bounded, redacted diagnostic with a direct removal command. Each command runs beneath a stable detached group leader that stays alive until every group descendant exits. This is an internal trusted-subprocess boundary: the classifier invokes Bash and GNU coreutils by fixed paths. It finds gh only in /usr/bin, /usr/local/bin, or $HOME/.local/bin after it validates the path, ownership, permissions, and file type. It treats artifacts as data and never executes artifact content or caller-selected programs. On SIGHUP, SIGINT, or SIGTERM, the classifier rejects new commands, terminates and drains every owned group, synchronously removes tracked directories, and exits with the conventional cancellation code. If normal cleanup fails, it reports a bounded, redacted error and a removal command that remains valid if TMPDIR changes.

Run the script from a Linux NemoClaw checkout with Node.js 22.19 or later, /proc, Bash, authenticated gh in a trusted location, and GNU coreutils (dd, stat, tail, and wc).

Any nonzero log acquisition result is a classifier failure. After the cleanup attempt, the script exits nonzero with no success JSON and reports a bounded, redacted diagnostic. On GitHub authentication or authorization failure, stop, follow the repository GitHub access hard stop, and ask the user to correct the configured gh access (including SSO or token scope) before rerunning. Treat unclassified as bounded evidence, not proof that no known cause exists.

Files

What ships with it

2 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. 27d ago Changed · +5 lines f95d08bfe353
  2. 1mo ago Changed · -17 tokens per session 490f0a928521
  3. 1mo ago Changed 074f070c36ad
  4. 1mo ago First seen · 27 lines · 50 tokens per session scan A 12fb2df23694

Subscribe to this mod's changes

nemoclaw-maintainer-classify-ci-failure is a skill published in the GitHub repository NVIDIA/NemoClaw (22,871 stars, last pushed today), licensed Apache-2.0. It adds 33 tokens to every session and 719 once invoked, about $0.0001 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 2026-09-03.

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