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 agentmods add skills/agenticdevops/aoh/ml-training-job-triagenpx skills add agenticdevops/aoh --skill ml-training-job-triagegit clone --depth 1 https://github.com/agenticdevops/aohWrote 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/agenticdevops/aoh/ml-training-job-triage)<a href="https://agentmods.dev/skills/agenticdevops/aoh/ml-training-job-triage"><img src="https://agentmods.dev/badge/skills/agenticdevops/aoh/ml-training-job-triage.svg" alt="Measured on agentmods" 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 | $0.00034 | $0.00123 |
| Opus 5 | $0.00017 | $0.00062 |
| Sonnet 5 | $0.00007 | $0.00025 |
| Haiku 4.5 | $0.00003 | $0.00012 |
Grade A, and why
ml-training-job-triage 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 6d 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
ML Training Job Triage
Overview
Diagnose ML training job health using logs, metrics, checkpoints, and cost/runtime signals.
Process
- Identify job, run id, dataset, model, and environment.
- Inspect failures, utilization, queue time, and checkpoint state.
- Distinguish code/data failures from infrastructure capacity failures.
- Recommend the safest retry or rollback path.
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.
- 6d ago First seen · 18 lines · 34 tokens per session scan A 658061630f38
ml-training-job-triage is a skill published in the GitHub repository agenticdevops/aoh (5 stars, last pushed 1mo ago), licensed MIT. It adds 34 tokens to every session and 123 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 2026-08-31.
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