Cnb ds eda

A daily-driver collection of skills for agentic coding — a portable, agent-agnostic catalog managed with the vd CLI.

Install

npx -y skills add vanducng/skills --skill cnb-ds-eda

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

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What its author says it does

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Build evidence-backed exploratory analysis and GitHub-renderable notebook reports in `/Users/vanducng/git/work/cnb/cnb-ds-eda`. Use when the user asks for CNB EDA notebooks, Snowflake-backed analysis, Retell or Transfer AI investigations, data-contract-derived report logic, notebook refreshes, or report artifacts under `notebooks/`.

SKILL.md

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CNB DS EDA

Use this skill to produce analysis that a stakeholder can read directly in GitHub and that another analyst can refresh from the warehouse.

Workflow

Start in /Users/vanducng/git/work/cnb/cnb-ds-eda unless the user gives another checkout.
Inspect existing notebook patterns before editing. Prefer notebooks/rnd_disconnection_status/, notebooks/lead_age_performance/, and related topic folders over inventing a new structure.
Translate relative date requests into exact America/New_York report boundaries. State start_date, end_exclusive, and the inclusive last data date in the notebook.
Put runnable SQL in notebooks/<topic>/queries/. Put committed offline snapshot tables in notebooks/<topic>/snapshots/ when GitHub rendering or offline review matters.
Use src/connectors/snowflake.py::query_snowflake() for live refresh paths. Use vd:miudb only when the user explicitly asks for that workflow or when the connector is insufficient.
When the user mentions data contracts, inspect the source YAML under /Users/vanducng/git/work/cnb/cnb-data-contract/contracts/constraints/snowflake/ and mirror the business predicates in the analysis SQL.
Keep notebook code cells compact. Do not embed large TSV/CSV payloads inside code cells; load snapshot files instead.
Execute the notebook in-place before sharing or pushing when the user wants GitHub preview. Commit rendered outputs and PNG-backed Plotly figures.
Validate before handoff: jq empty <notebook>, jupyter nbconvert --execute, jupyter nbconvert --to html, and the repo test/lint commands that apply.

Report Shape

Start the notebook with:

objective and exact snapshot/report window
table of contents
definitions and detection rules
data sources and contract references
a compact data-loading cell

Then present the analysis from broad to specific:

total population and ratios
trend over time
company and agent concentration
lead/app/status/worklist distribution
bounded redacted samples
conclusion, root cause, and fix/monitor recommendation

References

Read references/repo-map.md for repo paths, validation commands, and file placement.
Read references/notebook-report.md before creating or reshaping a notebook report.
Read references/snowflake-contract-analysis.md before writing SQL from Retell, Transfer AI, Tenstreet, or data-contract logic.