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/aristoteleo/pantheonos/general_data_analysisnpx skills add aristoteleo/PantheonOS --skill general_data_analysisgit clone --depth 1 https://github.com/aristoteleo/PantheonOSWrote 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/aristoteleo/pantheonos/general_data_analysis)<a href="https://agentmods.dev/skills/aristoteleo/pantheonos/general_data_analysis"><img src="https://agentmods.dev/badge/skills/aristoteleo/pantheonos/general_data_analysis.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 | $0.00028 | $0.00326 |
| Opus 5 | $0.00014 | $0.00163 |
| Sonnet 5 | $0.00006 | $0.00065 |
| Haiku 4.5 | $0.00003 | $0.00033 |
Grade A, and why
General Data Analysis Skills Index 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
General Data Analysis Skills
Cross-cutting skills for workspace hygiene, environment setup, and computational performance.
Available Skills
Workspace File Organization
Give every analysis task its own descriptively-named folder (notebook, figures, data, reports inside it) — never scatter files at the workspace root or dump figures into internal dirs.
Skill file: file_organization.md
Environment Management
Detect and configure the best available environment manager (Conda/Mamba/venv) for reproducible Python environments.
Skill file: environment_management.md
Parallel Computing & Performance
Multi-core CPU, GPU acceleration, and memory optimization strategies for large-scale data analysis.
Skill file: parallel_computing.md
HPC Data Transfer via SSH
Transfer data to/from HPC clusters with interactive authentication (password + Duo/MFA) using pexpect and SSH ControlMaster.
Skill file: hpc_data_transfer.md
When to use:
- Downloading data from Stanford Sherlock or similar HPC clusters
- Need to handle Duo two-factor authentication programmatically
- Bulk data transfer with rsync over persistent SSH connections
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.
- 6d ago First seen · 50 lines · 28 tokens per session scan A 9eaa3aa9ee08
General Data Analysis Skills Index is a skill published in the GitHub repository aristoteleo/PantheonOS (482 stars, last pushed 3d ago), licensed BSD-2-Clause. It adds 28 tokens to every session and 326 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 2026-08-30.
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