The Scenario
Your data platform team maintains a shared Google Sheet of 20 Flux queries — written by four different team members over six months, covering different measurements, different time ranges, different aggregation logic. The plan is to promote them all to production dashboards this Friday. Someone raised the question in standup: has anyone actually validated that these queries parse correctly?
The answer, it turns out, is no. Everyone assumed someone else had run them.
You're the one who ends up with the job. InfluxDB Cloud has an AST endpoint that accepts a Flux query string and returns either a parsed AST or a syntax error with line and column numbers. Running 20 queries through it manually — copy each from the sheet, POST to the endpoint, read the response, record the result — is an afternoon of copy-paste work that shouldn't exist.
The bad version:
- Open the sheet, copy query 1 from column B, POST it to the AST endpoint via curl, read the JSON response, manually type "valid" or the error message into column C, repeat for all 20 queries.
- On query 8, get a 400 response that's harder to parse than expected because the error is nested two levels deep in the JSON and you're reading it in a terminal.
- Finish the validation pass, then discover a team member added queries 21-23 while you were working — start over for those.
There's no clever version of this workflow. It's just repetitive.
The Easy Way: One Prompt in SheetXAI
SheetXAI sits inside your Google Sheet. It can read each Flux query string from a column, call the InfluxDB Cloud AST endpoint for each one, and write the parse result back into the adjacent column — all in one instruction.
For each Flux query string in column B of this sheet, call the InfluxDB Cloud AST endpoint to validate the syntax and write 'valid' or the error message into column C.
What You Get
- Column C populated for all 20 rows: "valid" for queries that parse cleanly, or the specific syntax error message (e.g., "expected end of file, found pipe forward operator at line 3, column 14") for those that don't.
- No manual curl commands, no JSON parsing by hand.
- Results are in the sheet, visible to the whole team, not in a terminal session that disappears when you close the tab.
- New rows added later can be re-run with the same prompt — no loop to rebuild.
What If the Data Is Not Quite Ready
Some queries in column B are empty — they're placeholders where the query hasn't been written yet
For each row where column B contains a non-empty string, call the InfluxDB Cloud AST endpoint to validate the Flux query and write the result to column C. Skip blank rows and write 'pending' in column C for those.
The team wants to know not just valid/invalid but also which queries reference deprecated functions
Validate each Flux query in column B via the InfluxDB Cloud AST endpoint and write the parse status to column C. In column D, flag any query that references the 'experimental' package or any function documented as deprecated.
Query strings have inconsistent whitespace and some have trailing semicolons that cause parse failures
Before validating: for each query in column B, trim leading/trailing whitespace and remove any trailing semicolons. Then call the InfluxDB Cloud AST endpoint for the cleaned query and write the result to column C.
Full audit pass: clean, validate, flag owner, and write summary in one shot
For each row in this sheet (columns: query_owner, query_text, status): trim and clean the query_text, validate via InfluxDB Cloud's AST endpoint, write 'valid' or the error to the status column, and in a new column E write the query_owner name next to any rows that failed validation so they know to fix their query.
The cleanup and the validation run together — no separate prep step.
Try It
Get the 7-day free trial of SheetXAI and open your Flux query inventory sheet, then ask SheetXAI to validate every query against the InfluxDB Cloud AST endpoint and write the results back. For related tasks, see bulk-ingesting sensor data from a sheet or the InfluxDB Cloud overview.