data-scientist

A command that starts a Data Scientist workflow defined in `.github/agents/data-scientist.agent.md`. It covers evaluation design, machine-learning outputs, and data-science checks.

In plain words
What is it for?
Use it to plan evaluations, create data-science artifacts, and apply the workflow's validation gates.
Why use it?
It gives the agent a central process for validating analyses and machine-learning work instead of relying on scattered instructions.

Command for Claude Code

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 commands/jnpiyush/agentx/data-scientist
Clone the repo
git clone --depth 1 https://github.com/jnPiyush/AgentX

Made for: Claude Code.

Per session 21 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 72 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 $0.00021 $0.00072
Opus 5 $0.00010 $0.00036
Sonnet 5 $0.00004 $0.00014
Haiku 4.5 $0.00002 $0.00007

Measured 2d ago against content hash 803496a0a6ce, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

data-scientist 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 2d 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.

.claude/commands/data-scientist.md · 7 lines

What it actually says

Read .github/agents/data-scientist.agent.md before taking action.

Treat this command as a thin wrapper over the canonical agent file. Use that file for eval design, ML artifacts, and data-science validation gates.

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. 2d ago First seen · 7 lines · 21 tokens per session scan A 803496a0a6ce

Subscribe to this mod's changes

data-scientist is a command published in the GitHub repository jnPiyush/AgentX (15 stars, last pushed 5d ago), licensed Apache-2.0. It adds 21 tokens to every session and 72 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.