maas-nightly-qe-impact

maas-nightly-qe-impact is a skill for Claude Code from opendatahub-io/ai-helpers. It costs 81 tokens per session (1,691 once invoked), scanned A, original, Apache-2.0.

A review step for Model as a Service autofix changes that may affect downstream nightly quality checks. Model as a Service means providing access to machine-learning models through an application or API.

In plain words
What is it for?
Reading an autofix ticket and verdict, comparing the change with known triggers, and adding a Nightly QE Impact section to a pull request description.
Why use it?
It tells the merge team when a change may need follow-up in related test or continuous-integration repositories. Its findings are informational and do not block merging.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: positional $N argument.

Part of the odh-maas plugin — 1 skill shipped together

Good fit Reading an autofix ticket and verdict, comparing the change with known triggers, and adding a Nightly QE Impact section to a pull request description.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/opendatahub-io/ai-helpers/maas-nightly-qe-impact
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 opendatahub-io/ai-helpers --skill maas-nightly-qe-impact
Clone the repo
git clone --depth 1 https://github.com/opendatahub-io/ai-helpers

Made for: Claude Code.

Or install odh-maas, the plugin that ships this one along with the rest of its 1 skill.

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 maas-nightly-qe-impact

README.md
[![agentmods](https://agentmods.dev/badge/skills/opendatahub-io/ai-helpers/maas-nightly-qe-impact/github.svg)](https://agentmods.dev/skills/opendatahub-io/ai-helpers/maas-nightly-qe-impact)
Your own site
<a href="https://agentmods.dev/skills/opendatahub-io/ai-helpers/maas-nightly-qe-impact"><img src="https://agentmods.dev/badge/skills/opendatahub-io/ai-helpers/maas-nightly-qe-impact/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 maas-nightly-qe-impact

Your own site · 80×15
<a href="https://agentmods.dev/skills/opendatahub-io/ai-helpers/maas-nightly-qe-impact"><img src="https://agentmods.dev/badge/skills/opendatahub-io/ai-helpers/maas-nightly-qe-impact.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 81 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,691 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 $0.00081 $0.01691
Opus 5 $0.00041 $0.00846
Sonnet 5 $0.00016 $0.00338
Haiku 4.5 $0.00008 $0.00169

Measured 12d ago against content hash cc1635579aec, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

maas-nightly-qe-impact 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 12d 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.

plugins/odh-maas/skills/maas-nightly-qe-impact/SKILL.md · 178 lines

How it starts

The opening of the file, as written. The whole thing — 178 lines — stays where its author put it; the contents beside it link to each section on GitHub.

MaaS Nightly QE Impact

Notify the merge team when a MaaS autofix may require follow-up in downstream nightly test or CI repos. This skill is informational only — it does not block merge or trigger re-iteration.

Step 1: Confirm context

  1. Read .autofix-context/ticket.json for the ticket key and summary. If the file is missing or malformed, write an empty findings file and stop.
  2. Read autofix-output/.autofix-verdict.json. If verdict is not committed, write an empty findings file and stop:
mkdir -p .autofix-context/extension-findings
echo '[]' > .autofix-context/extension-findings/maas-nightly-qe-impact.json
  1. Load the static trigger catalog from ${CLAUDE_SKILL_DIR}/references/impact-triggers.md and repo paths from ${CLAUDE_SKILL_DIR}/references/repo-locations.md.

Step 2: Analyze the code change

Collect the diff against the target branch:

TARGET=$(git rev-parse --abbrev-ref origin/HEAD 2>/dev/null | sed 's|^origin/||')
BASE="origin/${TARGET:-main}"
git diff --name-only "${BASE}...HEAD" 2>/dev/null || git diff --name-only HEAD~1
git diff "${BASE}...HEAD" 2>/dev/null | head -2000

Classify changed files against the trigger catalog. Flag a category when the diff touches matching paths or introduces matching concepts (env vars, CRD fields, namespace names, API routes, NetworkPolicy selectors, deployment names).

High-signal patterns (learned from models-as-a-service#1051):

  • Namespace moves (INFRA_NAMESPACE, odh-ai-gateway-infra, redhat-ai-gateway-infra, controller vs infra namespace)
  • Secret relocation (maas-db-config, cross-namespace DB URLs)
  • Renamed reconciler fields (MaaSAPINamespaceInfraNamespace)
  • NetworkPolicy label selectors affecting Gateway ↔ maas-api traffic
  • Deploy/script changes under scripts/deploy.sh, scripts/setup-database.sh, scripts/validate-deployment.sh
  • New or changed API endpoints under /v1/ or /internal/v1/
  • CRD schema changes for MaaS resources (Tenant, MaaSAuthPolicy, etc.)

Read the full file on GitHub · 178 lines

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. 12d ago First seen · 178 lines · 81 tokens per session scan A cc1635579aec

Subscribe to this mod's changes

maas-nightly-qe-impact is a skill published in the GitHub repository opendatahub-io/ai-helpers (37 stars, last pushed 5d ago), licensed Apache-2.0. It adds 81 tokens to every session and 1,691 once invoked, about $0.0004 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 2026-08-30.

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