Clockout Message Format

ReportFlow parses natural-language clockout messages posted by chatters in Discord. There is no rigid template—our AI extraction engine handles hundreds of format variations. However, understanding the core conventions (especially lp/ls/lt markers) will help you maximize accuracy and take full advantage of built-in fraud prevention.

Core structure of a clockout

A typical clockout message includes a greeting or header (e.g., "Clock out"), optional traffic notes, per-model revenue lines, and a total at the bottom. The per-model lines may contain transaction type markers that indicate the last purchase (lp), last subscription (ls), and last tip (lt) of the shift. These markers serve as fraud-prevention boundaries—the next chatter cannot claim the same transactions.

Clock out Traffic: good Hanna $700 - (lp - John - $500, ls - Mike - $200) Alexus $300 - (lt - Sarah - $300) TOTAL $1,000

In this example the chatter earned $1,000 across two models. Hanna brought in $700 with a last purchase from John ($500) and a last subscription from Mike ($200). Alexus contributed $300 from a tip by Sarah. ReportFlow stores these markers and compares them to the next shift's starting transactions to detect duplicate claims.

Understanding lp, ls, and lt markers

  • lp (last purchase) — The final one-time purchase closed during this shift. Usually an unlock of premium content.
  • ls (last subscription) — The last fan who subscribed or renewed during the shift.
  • lt (last tip) — The last tip received before clocking out.

Including these markers is optional, but highly recommended. When present, ReportFlow can warn managers if the next chatter's clockout repeats the same customer + amount combination, which is a strong indicator of double-claiming.

Flexible formatting

Our AI extraction handles a wide variety of human writing styles. All of the following are understood:

Hanna $700 - lp John $500
Hanna - 700 (last purchase John 500)
Hanna: $700, LP = John $500, LS = Mike $200

The parser extracts model names, dollar amounts, transaction types, and customer names regardless of punctuation, capitalization, or ordering. If something is unclear the bot adds a ⚠️ reaction and logs a warning in the dashboard for manual review.

Best practices

  • Include a TOTAL line—the system uses it to verify summed model amounts and flag discrepancies.
  • Always add lp/ls/lt markers even if the amount is small; fraud prevention depends on them.
  • Keep model names consistent across shifts (e.g., "Hanna" vs. "Hannah") for accurate reporting.
  • Avoid emojis inside dollar amounts—write "$500" not "💵500".

Next steps