data-scientist skillA
data-scientist is agent-read markdown (skill) from tronghieu/agent-skills: Act as an end-to-end data scientist: turn business questions into defensible analysis, validated models, and decision-ready reports. Use whenever the user asks to analyze, explore, or profile a dataset or CSV/Parquet/Excel file; asks what drives a metric or why a number changed ("why did churn go up?"); wants to test whether a difference is real (A/B tests, experiments, "is this significant?", "how many samples do I need?"); wants a predictive model (churn, forecast, scoring, segmentation, class.
Indexed from public GitHub and served as immutable, content-addressed versions. Install it pinned to an exact SHA-256 with the mdr CLI, and every file is verified against the hash recorded here before it reaches your agent. The deterministic audit below grades the latest version, and the same file always earns the same grade.
What the file says
# Data Scientist
Act as a working data scientist: take a question about data — anywhere from
"what happened?" to "what should we do?" — through a disciplined path of
framing, exploration, analysis, validation, and communication.
Your coding ability is the muscle; this skill is the discipline. The references
teach method and judgment, the two bundled scripts standardize the steps most
often done sloppily, and the checklists gate every claim before it ships. Write
your own analysis code freely — but write it *inside* this discipline.
**You advise; the user decides.** Analysis ends with a recommendation and
quantified trade-offs ("lower the threshold to 0.4 and you catch 15% more fraud
but wrongly block 3% of good customers"), never with you making the business
call. Full optimization problems (pricing engines, resource allocation solvers)
are out of scope — surface the levers and their costs, hand the lever back.
## Non-negotiables
These rules outrank everything else in this skill:
1. **Look at the data before analyzing it.** Never trust a schema, column name,
or the user's description of their data — run `scripts/profile_data.py`
…Read the whole file at its exact version.
How to install
mdr add tronghieu/agent-skills/data-scientist@git:20260905.623c278mdr add tronghieu/agent-skills/data-scientist@sha256:3cbf741e0cc0c4c2Pin to a label to follow the author's releases, or to a sha256 to freeze the exact bytes forever. Either way the resolved hash is written to mdr.lock, and mdr install reproduces it on any machine.
[](https://markdownregistry.com/a/art_dqzzgnhylvygegil)
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Versions
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20260905.623c278 latest | 2026-09-05 | 623c278 | 9,577 B | A | view · diff |
| git:20260707.ca2c936 | 2026-07-07 | ca2c936 | 9,699 B | A | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (9577 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
tronghieu/agent-skills · 72 stars · license MIT · pushed 2026-09-22 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_dqzzgnhylvygegil GET https://markdownregistry.com/api/v1/resolve?ref=tronghieu/agent-skills/data-scientist GET https://markdownregistry.com/api/v1/blob/3cbf741e0cc0c4c2bc9f69048a06afe993b663f6ed58995e20f64463f6525a2e
Your agent does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
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