Dashboard totals look wrong? Check rows before charting
Supply synthetic CSV data, field definitions and duplicate rules to draft checks and totals that distinguish rows from unique items.
Execution environment and usage
AI / software
Text-draft adaptation: ChatGPT / Claude / Gemini
Where to operate
The ChatGPT / Claude / Gemini web-chat input; this version requests a text draft.
Getting started
- Open an eligible account at chatgpt.com / claude.ai / gemini.google.com and start a chat without connecting external accounts.
- Prepare synthetic CSV data, field definitions and duplicate-handling rules.
- Request the draft/check and compare it with the original material. Suggestions are not evidence of execution.
Setup and plan requirements
Task inputs: Prepare synthetic CSV data, field definitions and duplicate-handling rules. Use an eligible tool that can read the supplied format; verify parsing, context limits and access before relying on it.
Prompt portability limits
The written request can be adapted to a chatbot that accepts the same input. It does not transfer the original agent, plugins or computer permissions.
Usage limitations
CSV may be pasted as a small text table; preserve its field dictionary, dates, identifiers and duplicate rules, and check totals manually.This independent pass reviewed local case records, without revalidating original sources or hands-on testing.
Environment sources
適用情境 / When to use
Supply synthetic CSV data, field definitions and duplicate rules to draft checks and totals that distinguish rows from unique items. CSV may be pasted as a small text table; preserve its field dictionary, dates, identifiers and duplicate rules, and check totals manually. Original case: This uses the user comment rather than the publisher’s product rating.
步驟 / Steps
- Prepare synthetic CSV data, field definitions and duplicate-handling rules.
- Check input row counts, missing values, formats and entity identifiers first.
- Reconcile grouped totals against inputs and list excluded records.
提示詞 / Prompt
Using [synthetic CSV/field dictionary/duplicate rules/report purpose], draft data checks and dashboard requirements. Distinguish rows from unique entities; reconcile missing values, dates and grouped totals with exclusion reasons. Design aggregates only. Do not rank individuals, contact customers or upload real records.
留意事項 / Cautions
- Do not supply personal contact details or infer individual buying intent.
- Row counts are not necessarily unique customer counts.
來源限制 / Evidence limits
The comment provides no dataset or accuracy evaluation and does not establish business impact.
流程說明 / Workflow note
These steps and prompts are original, untested exercises by this site, not the author’s verbatim workflow. Reported results do not guarantee exercise outcomes.
原始工具組合 / Original tool stack
Manus; CSV
Source publication date: 2026-07-02
Source checked: 2026-10-20