- name
- query
- description
- Runs a read-only SQL query against the Customer Experience tables (moz-fx-data-shared-prod.customer_experience_derived) and returns results as a formatted table. Use when the question requires counts, aggregations, rankings, or distributions — not when it requires reading document text.
# Query Skill
Runs a read-only SQL query against BigQuery and prints results as a formatted text table. No embedding required.
This skill is locked to **`moz-fx-data-shared-prod.customer_experience_derived`** — it can read any table or view in that dataset, and anything outside it is rejected. Only a single read-only `SELECT` (optionally `WITH … SELECT`) is accepted. A static allowlist check rejects any out-of-dataset reference before the query runs; the authoritative boundary is the service account's IAM, which grants read access to that dataset only, so BigQuery rejects any out-of-bounds read regardless of the SQL.
## Authentication
This skill connects to BigQuery using a service account — read-only access is enforced on the impersonated token. Just log in:
```bash
gcloud auth application-default login
```
Your authenticated BigQuery credentials are only used to create a new and temporary read-only access token on behalf of the service account defined in `SERVICE_ACCOUNT`, which requires the `roles/iam.serviceAccountTokenCreator` role on that service account. Your login no longer needs `--scopes`.
## Usage
```bash
python ${CLAUDE_PLUGIN_ROOT}/skills/query/scripts/query.py \
--sql "<read-only SELECT over moz-fx-data-shared-prod.customer_experience_derived.<table>>"
```
Reference tables by their fully-qualified name (`moz-fx-data-shared-prod.customer_experience_derived.<table>`).
## When to use
Use this skill instead of `embed` + `vector-search` when the question requires:
- Counts ("how many tickets about X?")
- Rankings ("top N topics by volume")
- Distributions ("ticket count by product")
- Aggregations ("average sentiment by category")
- Any answer that is a number, ranked list, or summary statistic
Use `embed` + `vector-search` when the question requires reading and synthesizing document text.
## Common SQL patterns
**Dataset:** `moz-fx-data-shared-prod.customer_experience_derived`
**Tables:** `kitsune_retrieval_index`, `zendesk_retrieval_index`, `knowledge_base_retrieval_index`
**Date filter columns:**
- Kitsune: `creation_date` DATE — use `creation_date BETWEEN 'YYYY-MM-DD' AND 'YYYY-MM-DD'`
- Zendesk: `creation_date` DATE — use `creation_date BETWEEN 'YYYY-MM-DD' AND 'YYYY-MM-DD'`
- Knowledge Base: query the whole table — **no date filter**. It is a small, curated reference set, so never bound it by `last_approved_revision_date` or any other date column.
Every query against the date-partitioned Kitsune/Zendesk tables must carry a `creation_date` window — the period the caller asked for, or the last 30 days by default. "Most recent / latest N" questions bound the window first and `ORDER BY creation_date DESC LIMIT N` **within** it; never run an unbounded `ORDER BY creation_date DESC` across all history. (The Knowledge Base is exempt — query it in full.)
```sql
-- Most recent N problems reported (Zendesk) — window first, then order within it
SELECT creation_date, ticket_summary_llm, product
FROM `moz-fx-data-shared-prod.customer_experience_derived.zendesk_retrieval_index_v1`
WHERE creation_date BETWEEN '2026-07-09' AND '2026-07-16'
ORDER BY creation_date DESC LIMIT 3
-- Top topics by volume (Kitsune)
SELECT topic, COUNT(*) AS count
FROM `moz-fx-data-shared-prod.customer_experience_derived.kitsune_retrieval_index_v1`
WHERE creation_date BETWEEN '2026-03-24' AND '2026-04-22'
GROUP BY topic ORDER BY count DESC LIMIT 10
-- Top categories by volume (Zendesk)
SELECT ticket_category_llm, COUNT(*) AS count
FROM `moz-fx-data-shared-prod.customer_experience_derived.zendesk_retrieval_index_v1`
WHERE creation_date BETWEEN '2026-03-24' AND '2026-04-22'
GROUP BY ticket_category_llm ORDER BY count DESC LIMIT 10
-- Average sentiment by topic (Kitsune only — do not use Zendesk sentiment)
SELECT topic, COUNT(*) AS count, ROUND(AVG(question_sentiment_score), 2) AS avg_sentiment
FROM `moz-fx-data-shared-prod.customer_experience_derived.kitsune_retrieval_index_v1`
WHERE creation_date BETWEEN '2026-03-24' AND '2026-04-22'
GROUP BY topic ORDER BY avg_sentiment ASC LIMIT 10
-- Volume by product (Zendesk)
SELECT product, COUNT(*) AS count
FROM `moz-fx-data-shared-prod.customer_experience_derived.zendesk_retrieval_index_v1`
WHERE creation_date BETWEEN '2026-03-24' AND '2026-04-22'
GROUP BY product ORDER BY count DESC
```
## Output
A plain-text formatted table:
```
topic count
------------- -----
site-breakage 142
sync 98
passwords 74
```
## Troubleshooting
| Symptom | Fix |
|---------|-----|
| `Authentication rejected (401)` / `GCP authentication required` | Re-run `gcloud auth application-default login`; confirm you have `roles/iam.serviceAccountTokenCreator` on the service account in `SERVICE_ACCOUNT` |
| `Missing dependency` | `pip install google-auth requests` |
| `Refusing to run … outside the allowed dataset` / `Only read-only SELECT` | Query only tables or views in `moz-fx-data-shared-prod.customer_experience_derived` with a single read-only SELECT |
| `No results` | Check date range, table name, and filter values |
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