Use the Data and analytics pack
Install the Data and analytics pack, run its first task, and follow a typical session step by step.
For analysts and the people who rely on their numbers: review SQL for the bugs that quietly inflate a figure, and spec dashboards around a decision instead of every chart that was easy to make.
Reach for it when: A number matters (a board metric, a finance figure, a team KPI) and people either disagree about it or are about to build a dashboard on it.
1. Install it
npx skilldrop-cli install --pack data-analytics # Claude Code, your user folder
npx skilldrop-cli install --pack data-analytics --project # Claude Code, this repo
npx skilldrop-cli install --pack data-analytics --ide cursor # or kiro, codex, antigravity, copilot
npx skilldrop-cli install --pack data-analytics --local # this repo, hidden from git
In Claude Code you can also add the marketplace once (/plugin marketplace add sananthanarayan/skilldrop) and run /plugin install data-analytics@skilldrop.
It brings core with it, so the shared skills are there too.
2. Run the first task: check a query before its number goes into a report
Before you start:
- A SQL query whose number you need to trust, and the database it runs on
Paste this into your agent:
Review this Postgres query before it goes into the finance dashboard. One row per region; customers.customer_id is unique and an order has many order_items. Finance reports in New York time.
SELECT c.region, SUM(o.amount_usd) AS revenue_usd
FROM orders o
JOIN customers c ON c.customer_id = o.customer_id
JOIN order_items oi ON oi.order_id = o.order_id
WHERE o.created_at BETWEEN '2026-09-01' AND '2026-09-30'
GROUP BY c.region;
How to tell it worked: sql-review opens with a verdict, flags the order_items join as multiplying revenue and the BETWEEN as losing 30 September, gives a corrected query with New York boundaries, and lists verification queries to prove the fix.
If nothing happens: If the review jumps to indexes before correctness, ask for it by name ("use sql-review"). If it guesses the database, tell it which one: integer division and timezone functions differ between engines.
3. A typical session
Bring:
- the metric name and the question it answers
- the SQL or dashboard already computing it, and the tables it reads
- who reads it and what they decide
- the database engine (Postgres, BigQuery, Snowflake, …)
sql-review: Run it on the query that reports the number, with the engine and what one output row should represent. You get: A verdict and line-by-line findings, each with the wrong result and corrected SQL, plus the full corrected query and verification queries. You decide: Trust the number, or fix the SQL and review again. If the findings turn on what the number should mean (timezone, exclusions), settle that with the metric's owner first.dashboard-spec: Give it the audience, the decision and the list of requested charts. You get: A one-page spec: questions in priority order, one chart per question with its metric named and any undefined one flagged as a build blocker, filters, freshness SLA, layout, and a cut list.doc-critique: Run it on the dashboard spec before sharing it with the BI team. You get: A verdict and severity-tagged findings with a fix for each. You decide: Hand the spec to the builder, or revise it.
You end with: Reviewed SQL whose number you can defend, and a dashboard spec a BI developer can build without guessing.
4. Run it as a loop
A loop runs the skills in order and stops at each gate for a verdict. Install and start one:
npx skilldrop-cli install --loop --pack data-analytics
- measure: Take a dashboard request to a spec a BI developer can build on numbers people can defend: the decision it serves and one chart per question, every metric defined, the SQL behind each metric reviewed for the bugs that quietly inflate a figure, and the metric owner's sign-off on each definition before anything is built. Say "run the measure loop on this". Stages: spec → review [G9] → sign-off [G9.1].
Next
- Every skill in the Data and analytics pack: what each one makes, needs and hands off to
- The pack's page, with one-click copy for every command
- Upgrade installed skills when a new version ships