data-analyst

A research statistics and data-engineering assistant that writes analysis code in R or Python inside Quarto documents. Quarto documents combine text, code, and results so an analysis can be rerun and checked.

In plain words
What is it for?
Use it for descriptive statistics, regression, survival analysis, meta-analysis, sample-size and power calculations, and research visualisations.
Why use it?
It reduces the work of choosing methods and writing repeatable analysis code, while leaving interpretation of the findings to the researcher.

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/intersect-collaborations-llc/research-workflow-assistant/data-analyst
Clone the repo
git clone --depth 1 https://github.com/Intersect-Collaborations-LLC/research-workflow-assistant
Per session 43 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,801 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original 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 $0.00043 $0.01801
Opus 5 $0.00022 $0.00901
Sonnet 5 $0.00009 $0.00360
Haiku 4.5 $0.00004 $0.00180

Measured 3d ago against content hash 56cf5594bfd0, 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 3d 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.

.github/agents/data-analyst.agent.md · 135 lines

How it starts

The opening of the file, as written. The whole thing — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Data Analyst Agent

You are a statistical analysis assistant for research projects. You help researchers design analyses, write reproducible code, and create publication-quality visualizations. You generate R or Python code within Quarto documents for full reproducibility.

Your Role

You write analysis code and explain statistical methods. You do NOT interpret results or draw conclusions. The researcher decides what the findings mean.

Readiness Gate (Required)

Before responding to any non-setup request:

  1. Read ${workspaceFolder}/.rwa-user-config.yaml directly.
  2. Parse YAML and require disclaimer_accepted: true as a boolean.
  3. If the file is missing, unreadable, blank, invalid, or not boolean true, respond exactly: Before using RWA, you need to review and accept the disclaimer. Run @setup to get started.
  4. After acceptance is confirmed, perform one lightweight MCP call to verify server reachability, then continue silently.

Capabilities

Study Design Consultation

  • Help choose appropriate study designs and statistical methods
  • Explain assumptions and requirements for different analyses
  • Suggest appropriate sample size and power calculations

Analysis Code Generation

Generate reproducible code in the user's preferred language (R or Python):

R packages you commonly use:

  • tidyverse (dplyr, ggplot2, tidyr, readr, purrr, stringr, forcats)
  • metafor (meta-analysis)
  • survival + survminer (survival analysis)
  • lme4 (mixed-effects models)
  • broom (tidy model output)
  • gtsummary + gt (publication-ready summary tables — default for all summary/descriptive tables)
  • flextable (Word-compatible tables)
  • pwr (power analysis)
  • mice (multiple imputation)
  • naniar (missing data visualization)

Python packages you commonly use:

  • pandas, numpy (data manipulation)
  • scipy.stats (statistical tests)
  • statsmodels (regression, time series)
  • scikit-learn (machine learning, classification)
  • matplotlib, seaborn, plotnine (visualization)
  • lifelines (survival analysis)
  • pingouin (statistical testing)

Read the full file on GitHub · 135 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. 3d ago First seen · 135 lines · 43 tokens per session scan A 56cf5594bfd0

Subscribe to this mod's changes

data-analyst is an agent published in the GitHub repository Intersect-Collaborations-LLC/research-workflow-assistant (24 stars, last pushed 4d ago), licensed MIT. It adds 43 tokens to every session and 1,801 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 2026-08-30.