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 0x-Professor/Agent-Skills-Hub --skill ml-experiment-trackergit clone --depth 1 https://github.com/0x-Professor/Agent-Skills-HubWrote 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/0x-professor/agent-skills-hub/ml-experiment-tracker)<a href="https://agentmods.dev/skills/0x-professor/agent-skills-hub/ml-experiment-tracker"><img src="https://agentmods.dev/badge/skills/0x-professor/agent-skills-hub/ml-experiment-tracker/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/0x-professor/agent-skills-hub/ml-experiment-tracker"><img src="https://agentmods.dev/badge/skills/0x-professor/agent-skills-hub/ml-experiment-tracker.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 | $0.00033 | $0.00169 |
| Opus 5 | $0.00016 | $0.00084 |
| Sonnet 5 | $0.00007 | $0.00034 |
| Haiku 4.5 | $0.00003 | $0.00017 |
Grade A, and why
ml-experiment-tracker 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.
What it actually says
ML Experiment Tracker
Overview
Generate structured experiment plans that can be logged consistently in experiment tracking systems.
Workflow
- Define dataset, target task, model family, and parameter search space.
- Define metrics and acceptance thresholds before training.
- Produce run plan with version and artifact expectations.
- Export the run plan for execution in tracking tools.
Use Bundled Resources
- Run
scripts/build_experiment_plan.pyto generate consistent run plans. - Read
references/tracking-guide.mdfor reproducibility checklist.
Guardrails
- Keep inputs explicit and machine-readable.
- Always include metrics and baseline criteria.
What ships with it
3 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.
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.
- 12d ago First seen · 28 lines · 33 tokens per session scan A 6bea1e6b6478
ml-experiment-tracker is a skill published in the GitHub repository 0x-Professor/Agent-Skills-Hub (10 stars, last pushed 6mo ago), licensed Apache-2.0. It adds 33 tokens to every session and 169 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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