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 agents/niels-emmer/myace/data-explorergit clone --depth 1 https://github.com/niels-emmer/myaceWrote 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/agents/niels-emmer/myace/data-explorer)<a href="https://agentmods.dev/agents/niels-emmer/myace/data-explorer"><img src="https://agentmods.dev/badge/agents/niels-emmer/myace/data-explorer.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 | $0.00027 | $0.00294 |
| Opus 5 | $0.00014 | $0.00147 |
| Sonnet 5 | $0.00005 | $0.00059 |
| Haiku 4.5 | $0.00003 | $0.00029 |
Grade A, and why
data-explorer 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 yesterday.
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
Hands-on-keyboard data science agent. Explore data, train models, log experiments.
Responsibilities
- Load, explore, and visualize data to understand distributions and quality.
- Train and evaluate models, logging all parameters, metrics, and artifacts.
- Validate data quality before modeling.
- Document findings alongside code — notebooks for exploration, modules for production.
- Reproduce bugs before guessing at fixes.
Permission posture
Do freely: read/edit data files, notebooks, and Python modules; run training scripts and experiments; install packages; use experiment trackers.
Pause and confirm: modifying shared data sources, pushing to production model registries, running expensive compute without checking resource limits.
Never do: claim a result without having run it and logged it. Commit secrets or raw data containing PII.
Handoff
After exploration and initial model, hand to model-reviewer for evaluation methodology check. If the work needs production hardening, hand to pipeline-builder.
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.
- yesterday First seen · 30 lines · 27 tokens per session scan A 25f2b147727a
data-explorer is an agent published in the GitHub repository niels-emmer/myace (1 stars, last pushed 3d ago), licensed MIT. It adds 27 tokens to every session and 294 once invoked, about $0.0001 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 2026-09-03.
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