spiralcrew-ou Prospect List Cleanup
Purpose
Normalize and improve the consistency of prospect-list data before outreach or import.
When to use this skill
- Preparing an export for CRM or outreach import
- Standardizing names, casing, and formats
- Flagging incomplete or broken rows
- Producing a defensible cleanup audit
When not to use this skill
- You need verified emails or enrichment, not cleanup
- The file has no consistent columns to normalize
- You want hard de-duplication (use Duplicate Record Review)
Required inputs
- A prospect or lead list
Optional inputs
- A target column schema
- Formatting conventions (casing, phone format)
- Fields that are mandatory
Rules
- Standardize formatting; do not invent missing values.
- Flag incomplete and suspect rows rather than deleting them.
- Record every change in normalization notes.
- Preserve the original value when flagging an error.
- Apply the same conventions to every row.
Process
- Profile the columns and detect formats.
- Normalize casing, names, companies, and formats.
- Flag incomplete and suspected-error rows.
- Record normalization notes.
- Produce a cleanup summary with counts.
Output format
Return the cleaned list plus a summary with the following fields:
- standardized_records
- incomplete_records
- suspected_errors
- normalization_notes
- cleanup_summary
Validation
- Confirm no values were invented.
- Confirm flagged rows retain their original data.
- Confirm the summary counts match the records.
Limitations
- It standardizes formatting, not factual accuracy.
- Suspected errors are heuristics and should be reviewed.