Design a workflow automation
Maps a manual workflow and designs an automation with tools, triggers, steps, and safeguards.
The prompt
Role: Act as a reporting analyst automating a recurring manual report.
Context: The report - what it contains, who consumes it, cadence, and current manual steps and time: [CURRENT_REPORT]. Data sources and how they are accessed: [SOURCES]. The metric definitions and business rules: [DEFINITIONS]. Known edge cases and manual judgement points: [EDGE_CASES]. Tools available for automation: [TOOLS]. Reliability needs (deadline, accuracy): [RELIABILITY].
Task: Produce: (1) the target workflow - source extract, transformations, the calculation of each metric, and the output(s) and distribution; (2) the validation gates - checks at each stage (freshness, row counts, reconciliation to a control total, business-rule checks) and what happens on failure; (3) how the manual judgement points are handled (automate with a rule, or surface for human review); (4) a fallback / manual-run plan for when automation fails before the deadline; (5) what to monitor and alert on.
Format: Sections: Workflow (stages) | Validation gates (table: stage | check | on failure) | Judgement points | Fallback plan | Monitoring & alerts. ~500 words.
Verification: Ensure every metric in the current report is reproduced with a defined rule; flag any manual step where the rule is genuinely ambiguous and needs sign-off before automating.
Validation: Simulate a source arriving late and a source with a schema change: does the workflow fail safe and alert, or produce a wrong report silently? Strengthen the gate that would miss it.
Highlighted [brackets] are blanks to replace with your own details.
Fill in the blanks and use this promptMore Projects & Operations prompts
What to fill in
- CURRENT_REPORT
- SOURCES
- DEFINITIONS
- EDGE_CASES
- TOOLS
- RELIABILITY
How this prompt is built
This prompt follows the RCTFVV structure (Role, Context, Task, Format, Verification, Validation). RCTFVV extends RCTF with two checking steps. Verification asks the model to review its own draft against your requirements; Validation asks it to flag assumptions and gaps you should confirm.
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