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 skills add Leeroo-AI/superml --skill ml-verifygit clone --depth 1 https://github.com/Leeroo-AI/supermlWrote 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/leeroo-ai/superml/ml-verify)<a href="https://agentmods.dev/skills/leeroo-ai/superml/ml-verify"><img src="https://agentmods.dev/badge/skills/leeroo-ai/superml/ml-verify/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.
<a href="https://agentmods.dev/skills/leeroo-ai/superml/ml-verify"><img src="https://agentmods.dev/badge/skills/leeroo-ai/superml/ml-verify.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00029 | $0.03964 |
| Opus 5.5 | $0.00012 | $0.01586 |
| Sonnet 5.5 | $0.00006 | $0.00793 |
| Haiku 4.5 | $0.00003 | $0.00396 |
Grade A, and why
ml-verify 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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 199 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ML Verification
Catch mistakes before they waste GPU hours. Verify configs, code, and math against documented framework behavior.
Grounding
Detect mode: On your first grounding call, check if Leeroopedia KB tools are available. If they return results, use KB mode. If unavailable or auth fails, use Web mode.
KB mode: Call verify_code_math / query_hyperparameter_priors / review_plan. Cite as [PageID].
Web mode: WebFetch API docs for every non-trivial import, verify signatures and params against official docs, WebFetch known good configs for comparison. Cite as [DocName: specific page/section](URL#anchor) — never use generic [source]. The link text MUST name the document and section (e.g., [HF PEFT: LoRA Conceptual Guide](https://huggingface.co/docs/peft/main/en/conceptual_guides/lora)). Start response with: > Grounding: Web mode — citations from official docs.
Web mode URL registry:
- HF PEFT LoRA guide:
https://huggingface.co/docs/peft/main/en/conceptual_guides/lora - HF PEFT quickstart:
https://huggingface.co/docs/peft/main/en/quicktour - HF Transformers TrainingArguments:
https://huggingface.co/docs/transformers/main/en/main_classes/trainer#transformers.TrainingArguments - HF TRL SFTTrainer:
https://huggingface.co/docs/trl/main/en/sft_trainer - HF TRL SFTConfig:
https://huggingface.co/docs/trl/main/en/sft_trainer#trl.SFTConfig - DeepSpeed:
https://www.deepspeed.ai/docs/config-json - vLLM:
https://docs.vllm.ai - PyTorch:
https://pytorch.org/docs/stable
The Iron Law
NO TRAINING RUN WITHOUT VERIFICATION FIRST
An hour of verification saves days of debugging failed runs. Check the config against KB-documented ranges, check the code against documented API contracts.
Phases
Phase 1: Check Against Documentation
KB mode:
Call the appropriate KB tools:
- For code/math:
verify_code_math(code_snippet, concept_name) - For configs/hyperparameters:
query_hyperparameter_priors(query)with model size, task type, hardware, and framework context - For full training configs:
review_plan(proposal, goal)with the complete config
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.
- 1mo ago First seen · 199 lines · 29 tokens per session scan A a3c0fc385ee2
ml-verify is a skill published in the GitHub repository Leeroo-AI/superml (196 stars, last pushed 7mo ago), licensed Apache-2.0. It adds 29 tokens to every session and 3,964 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 2026-08-30.
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