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 spytensor/openmozi --skill data-analysisgit clone --depth 1 https://github.com/spytensor/openmoziWrote 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/spytensor/openmozi/data-analysis)<a href="https://agentmods.dev/skills/spytensor/openmozi/data-analysis"><img src="https://agentmods.dev/badge/skills/spytensor/openmozi/data-analysis/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/spytensor/openmozi/data-analysis"><img src="https://agentmods.dev/badge/skills/spytensor/openmozi/data-analysis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00048 | $0.00469 |
| Opus 5.5 | $0.00019 | $0.00188 |
| Sonnet 5.5 | $0.00010 | $0.00094 |
| Haiku 4.5 | $0.00005 | $0.00047 |
Grade A, and why
data-analysis 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.
What it actually says
Data Analysis Workflow
How to Execute
- Ingest: Read the data source (CSV, JSON, database, API). Confirm format and size.
- Validate: Check for missing values, outliers, type mismatches. Report data quality issues.
- Explore: Compute basic statistics (count, mean, median, distribution). Identify patterns.
- Analyze: Apply the requested analysis (correlation, aggregation, filtering, comparison).
- Report: Present findings with clear summaries. Generate charts/visualizations if requested.
Rules
- Always inspect the data before analyzing — never assume structure.
- Report data quality issues (nulls, duplicates, outliers) before drawing conclusions.
- Use shell_exec with Python (pandas, matplotlib) for large datasets or complex analysis.
- Show your methodology: what you computed, which columns, what filters.
- Present numbers with appropriate precision (don't show 15 decimal places).
Pitfalls
- Analyzing without first inspecting the data shape and quality
- Drawing conclusions from data with unaddressed quality issues
- Showing raw numbers without context or interpretation
- Not specifying units or time periods for metrics
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 · 46 lines · 48 tokens per session scan A 529cd61b5895
data-analysis is a skill published in the GitHub repository spytensor/openmozi (484 stars, last pushed 2mo ago), licensed MIT. It adds 48 tokens to every session and 469 once invoked, about $0.0002 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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