stmo

name	stmo
description	Manage Redash queries and dashboards on Mozilla's STMO (sql.telemetry.mozilla.org) using stmo-cli. Use when the user wants to explore telemetry data on STMO, write, deploy, or execute Redash queries, manage dashboards, or discover data sources. Also trigger on mentions of STMO, Redash, sql.telemetry.mozilla.org, or when the user wants to query Mozilla telemetry data (as opposed to probe/metric discovery, which is mozdata territory).
allowed-tools	["Bash(stmo-cli:*)","Bash(mkdir:*)","Read","Grep","Glob"]

stmo-cli

CLI for managing queries and dashboards on Mozilla's Redash instance (sql.telemetry.mozilla.org).

Prerequisites

Before running any stmo-cli command (except init and update), verify REDASH_API_KEY is set. If missing, every command fails immediately with:

Error: REDASH_API_KEY environment variable not set

To get the key, go to https://sql.telemetry.mozilla.org/users/me (API Key section), copy the key, and export it:

export REDASH_API_KEY=your_key_here

If stmo-cli is not available, install it via ./mach bootstrap.

Working directory

stmo-cli creates queries/ and dashboards/ relative to the current directory. Never run file-creating commands from the Firefox repo tree. Always use the artifacts/stmo/ directory, which is already VCS-ignored:

mkdir -p artifacts/stmo
cd artifacts/stmo

Queries created during exploration are ephemeral: fetch → execute → archive → done.

The temp directory is not a git repo, so stmo-cli deploy (which uses git diff to detect changes) won't work — always use stmo-cli deploy --all instead.

Data exploration workflow

1. Find data sources

   stmo-cli data-sources
   stmo-cli data-sources <id> --schema
   

2. Discover existing queries

   stmo-cli discover
   

3. Fetch and read an existing query

   stmo-cli fetch <id>
   # reads: queries/<id>-*.sql and queries/<id>-*.yaml
   

4. Execute

   stmo-cli execute <id> --format table --limit 50
   stmo-cli execute <id> --format json --limit 50
   stmo-cli execute <id> --param key=value
   stmo-cli execute <id> --param channels='["release","beta"]'  # multi-value enum: always JSON array
   stmo-cli execute <id> --interactive  # prompts for parameter values
   

5. Clean up newly created queries

   If you created a new query (the id: 0 → deploy flow) and it's not worth keeping, archive it — throwaway queries clutter the Redash account:

   stmo-cli archive <id>
   

   If the query is useful or you want to share it with others, leave it in Redash instead. The same applies to dashboards created during exploration — archive with stmo-cli dashboards archive <slug> if throwaway, leave if worth sharing.

   Do not archive queries or dashboards you only fetched to read — that would delete them from Redash.

   To restore an archived query:

   stmo-cli unarchive <id>
   stmo-cli fetch <id>
   

Bootstrap context from existing queries

Before answering a new data question, fetch the user's existing queries to understand what tables, patterns, and SQL style they already use:

stmo-cli fetch --all

Then read the downloaded .sql files to learn which tables are queried, how filters are structured, and what metrics are already tracked. This makes new queries fit naturally into the user's existing work.

Beyond Redash: export and analyze

When Redash isn't sufficient — complex statistics, rich visualizations, or analysis over large result sets — export the raw data and analyze it locally:

stmo-cli execute <id> --format json --limit 10000 2>/dev/null > data.json

From there:

• DuckDB or SQLite for SQL-based analysis over the exported data
• Python + pandas/scipy/numpy for real statistics (mean/median alone is almost always wrong)
• Apache Echarts for rich interactive charts in HTML/JS that handle large datasets well
• Jinja2 for templating if generating reports

A static website updated via cron (behind SSO) is a proven pattern for sharing results within Mozilla — see the App Engine static site with IAP runbook.

SQL style

STMO queries run on BigQuery. Use BigQuery SQL syntax: backtick-quoted identifiers, DATE_ADD(date, INTERVAL N DAY), FORMAT_DATE, APPROX_COUNT_DISTINCT, etc.

mozdata integration

Use the mozdata MCP tools (mozdata:probe-discovery, mozdata:query-writing) to find the right telemetry probes, metrics, and table schemas. Then use stmo-cli to write, deploy, and execute the actual Redash queries.

Query management

Create a new query:

1. Create queries/0-{slug}.sql with the SQL

2. Create queries/0-{slug}.yaml with metadata:

   id: 0
   name: My Query Name
   data_source_id: <id from stmo-cli data-sources>
   options:
     parameters: []
   visualizations: []
   

   Both options (with parameters) and visualizations are required even when empty.

   Do not add a default Table visualization — Redash creates one automatically for every new query.

   Slug rule: stmo-cli derives the expected SQL filename by slugifying the name field — non-alphanumeric chars become -, consecutive dashes collapse, apostrophes are stripped (e.g. "Mozilla's .rpm" → mozilla-s-rpm). The {slug} in both filenames must match this transform.

3. For enum parameters, use YAML multiline format — escaped newlines (\\n) are not valid:

   options:
     parameters:
     - name: normalized_channels
       title: normalized_channels
       type: enum
       value:
       - release
       enumOptions: |-
         nightly
         aurora
         beta
         release
         esr
       multiValuesOptions:
         prefix: ''''
         suffix: ''''
         separator: ','
   

4. Deploy:

   stmo-cli deploy --all
   

5. Sync the server-assigned ID:

   stmo-cli fetch <new-id>  # renames local files to {new-id}-{slug}.*
   

Dashboard management

Dashboards are addressed by slug, not ID.

stmo-cli dashboards discover                    # only shows favorited dashboards
stmo-cli dashboards fetch <slug>
stmo-cli dashboards deploy <slug>
stmo-cli dashboards deploy --all
stmo-cli dashboards archive <slug>
stmo-cli dashboards unarchive <slug>

Create: dashboards/0-{slug}.yaml with id: 0, deploy, file auto-renames with real ID.

Command reference

Run stmo-cli --help — stmo-cli outputs LLM-optimized help when run inside an AI coding environment (CLAUDECODE is set automatically).

File format

queries/{id}-{slug}.sql    # SQL text
queries/{id}-{slug}.yaml   # metadata: name, data_source_id, options, visualizations
dashboards/{id}-{slug}.yaml

New queries/dashboards use id: 0 in the filename until deployed.