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 a2ngerer/claude_onboarding_agent --skill data-science-setupgit clone --depth 1 https://github.com/a2ngerer/claude_onboarding_agentWrote 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/a2ngerer/claude_onboarding_agent/data-science-setup)<a href="https://agentmods.dev/skills/a2ngerer/claude_onboarding_agent/data-science-setup"><img src="https://agentmods.dev/badge/skills/a2ngerer/claude_onboarding_agent/data-science-setup.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Agent Snooping · line 257 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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 | $0.00041 | $0.04221 |
| Opus 5 | $0.00020 | $0.02110 |
| Sonnet 5 | $0.00008 | $0.00844 |
| Haiku 4.5 | $0.00004 | $0.00422 |
Grade A, and why
data-science-setup 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 7d 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 — 311 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Data Science / ML Setup
This skill configures Claude for exploratory and productive data science / ML work. It is the right choice when your project centers on notebooks, models, datasets, and experiments — not general application code (use coding-setup for that) and not literature research (use research-setup for that).
Handoff context: Read skills/_shared/consume-handoff.md and run it with the handoff block (if any). The helper guarantees the following locals: detected_language, existing_claude_md, inferred_use_case, repo_signals, graphify_candidate. Use detected_language for all user-facing prose; generated file content stays in English.
Existing CLAUDE.md: If existing_claude_md: true, DO NOT overwrite it. Append a new delimited section at the end of the file:
<!-- onboarding-agent:start setup=data-science skill=data-science-setup section=claude-md -->
## Claude Onboarding Agent — Data Science Setup
...generated content...
<!-- onboarding-agent:end -->
If the delimited block already exists from a previous run (either the attributed form above or the legacy unattributed <!-- onboarding-agent:start --> form), replace only the content between the markers; leave the rest of the file untouched. Upgrade the opening marker to the attributed form while you are there — /upgrade-setup depends on it for detection.
Supporting Files
Read these on-demand at the step that invokes them. Do not read eagerly.
rule-file-templates.md— bodies of the.claude/rules/*.mdfiles (Step 4)stack-scaffolds.md—pyproject.toml,uv addcommands,.claude/settings.jsonpermissions, directory scaffold (Step 4)gitignore-block.md— the.gitignoreblock (Step 4)notebook-hygiene.md—.pre-commit-config.yamlfor nbstripout + nbqa (Step 4)skills/_shared/consume-handoff.md— orchestrator handoff parse + inline fallback (preamble, before Step 1)skills/_shared/offer-superpowers.md— canonical Superpowers opt-in (Step 1)skills/_shared/offer-graphify.md— canonical Graphify opt-in (Step 6)
What ships with it
4 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.
- 7d ago First seen · 311 lines · 41 tokens per session scan A a6acaa53f9f2
data-science-setup is a skill published in the GitHub repository a2ngerer/claude_onboarding_agent (5 stars, last pushed today), licensed MIT. It adds 41 tokens to every session and 4,221 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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