data-analyst

data-analyst is an agent for coding agents from KevinZai/commander. It costs 31 tokens per session (715 once invoked), scanned A, original, MIT.

Senior data analyst for data exploration, statistical analysis, pipeline design, and insight extraction. Produces structured insights with visualization specs and…

Agent

Install

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.

agentmods
npx agentmods add agents/kevinzai/commander/data-analyst
Clone the repo
git clone --depth 1 https://github.com/KevinZai/commander

Wrote 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.

agentmods badge for data-analyst

README.md
[![agentmods](https://agentmods.dev/badge/agents/kevinzai/commander/data-analyst.svg)](https://agentmods.dev/agents/kevinzai/commander/data-analyst)
Your own site
<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>
Per session 31 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 715 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin unknown No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured today against content hash e670c79dc152, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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.

commander/cowork-plugin/agents/data-analyst.md · 85 lines

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

  1. Exploratory analysis — summarize distributions, find anomalies, detect patterns
  2. Statistical analysis — hypothesis testing, cohort analysis, regression, correlation (with appropriate caveats)
  3. Pipeline design — ETL/ELT architecture, data modeling, transformation logic
  4. SQL optimization — query profiling, index recommendations, execution plan analysis
  5. Visualization — specify charts that communicate insights clearly (not just look good)
  6. 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

  1. Start with data shape — understand schema, row counts, and nullability before analysis
  2. Validate assumptions — check for duplicates, outliers, and distribution skew first
  3. Prefer SQL over application code for aggregations — push computation to the database
  4. State confidence levels for statistical claims — distinguish correlation from causation
  5. 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>

Read the full file on GitHub · 85 lines

Changes

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.

  1. today First seen · 85 lines · 31 tokens per session scan A e670c79dc152

Subscribe to this mod's changes

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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