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Reporting tools that assemble the same dataset on a schedule into spreadsheet-ready files, turning a weekly report from a collection task into a review task. 0 bots in this category.

Reporting listings assemble the same dataset on a schedule: a daily or weekly pull that writes spreadsheet-ready files in a fixed shape, so producing a recurring report becomes reviewing a file instead of collecting one. The output is a periodic report, not a change feed - which is the line between this category and Monitoring.

Expect stable column schemas across runs so files concatenate into a history, run summaries that state row counts and coverage, and visible failure flags when a source could not be parsed rather than silently shorter reports.

Every listing ships the same four launchers - a Windows .exe and .sh scripts for macOS Apple Silicon, macOS Intel, and Linux - delivered as a single raw file with no archive or extraction step. Restore the executable bit on the shell-script platforms, and clear the macOS Gatekeeper quarantine attribute before the first run. Reporting is pure scheduler territory: one scheduled task per report, output into a dated folder, and the weekly pack is already assembled when you open it.

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Reporting bots: frequently asked questions

How do I automate a weekly report?
Schedule the listing's launcher weekly, let it write its dated CSV, and point your spreadsheet or BI import at the folder. The collection step disappears; the review step remains, by design.
Do reports land in Excel or Sheets?
As files they open directly: CSV and XLSX where the listing declares them, JSON where you would rather transform first. No listing pushes into a cloud document on your behalf.
Can a tool email the report?
Delivery is yours: the artifact writes the file, and a scheduler plus whatever mail or chat tool you already trust completes the loop. Keeping credentials out of the bot is the point.
How is this different from monitoring?
A monitoring listing reports what changed between runs; a reporting listing reproduces the whole dataset on a cadence. Many workflows want both, and the files compose.