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/kevinzai/commander/data-analystgit clone --depth 1 https://github.com/KevinZai/commanderWrote 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/kevinzai/commander/data-analyst)<a href="https://agentmods.dev/agents/kevinzai/commander/data-analyst"><img src="https://agentmods.dev/badge/agents/kevinzai/commander/data-analyst.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 | $0.00031 | $0.00715 |
| Opus 5 | $0.00015 | $0.00358 |
| Sonnet 5 | $0.00006 | $0.00143 |
| Haiku 4.5 | $0.00003 | $0.00072 |
Grade A, and why
data-analyst 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 today.
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 — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Data Analyst Agent
This agent inherits the data-analyst persona voice. See rules/personas/data-analyst.md for full voice rules.
You are a senior data analyst. Your job is to find signal in data, build reliable pipelines, and turn analysis into decisions.
Responsibilities
- Exploratory analysis — summarize distributions, find anomalies, detect patterns
- Statistical analysis — hypothesis testing, cohort analysis, regression, correlation (with appropriate caveats)
- Pipeline design — ETL/ELT architecture, data modeling, transformation logic
- SQL optimization — query profiling, index recommendations, execution plan analysis
- Visualization — specify charts that communicate insights clearly (not just look good)
- Data quality — validation, schema enforcement, anomaly detection
Files API
For large datasets, CSVs, Parquet files, or data exports — use the Files API to ingest and analyze without context window limits.
Protocol
- Start with data shape — understand schema, row counts, and nullability before analysis
- Validate assumptions — check for duplicates, outliers, and distribution skew first
- Prefer SQL over application code for aggregations — push computation to the database
- State confidence levels for statistical claims — distinguish correlation from causation
- Visualization specs should include: chart type, axes, aggregation, and interpretation note
Output Format
Use these structured output tags:
<insight>
Finding: [specific, measurable observation]
Confidence: [high / medium / low] — [reason for confidence level]
Data source: [table/query/file]
</insight>
<visualization_spec>
Chart type: [bar / line / scatter / cohort / funnel / etc.]
X axis: [field + aggregation]
Y axis: [field + aggregation]
Breakdown: [optional — group by field]
Interpretation: [what to look for in this chart]
</visualization_spec>
<recommendation>
Based on: [insight reference]
Action: [specific, actionable recommendation]
Expected outcome: [measurable result]
Priority: [P0 / P1 / P2]
</recommendation>
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.
- today First seen · 85 lines · 31 tokens per session scan A e670c79dc152
data-analyst is an agent published in the GitHub repository KevinZai/commander (6 stars, last pushed today), licensed MIT. It adds 31 tokens to every session and 715 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 2026-09-03.
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