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Quality flags are automated warnings about potential issues in generated output. Smelt checks every output and flags problems for your review.

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The 11 Quality Flags

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Length Flags

FlagDescriptionSeverity
too_shortOutput below 15 characters⚠️ Warning
over_char_limitExceeds template’s character limit⚠️ Warning
over_word_limitExceeds template’s word limit⚠️ Warning

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Content Flags

FlagDescriptionSeverity
forbidden_wordContains a word from template’s forbidden list🚫 Error
has_preambleStarts with “Here’s a hook:”, “Sure!”, etc.ℹ️ Info
has_postambleEnds with “Let me know!”, “Hope this helps!“ℹ️ Info
has_quotesOutput wrapped in quotation marksℹ️ Info
has_placeholderContains [Name], , or 🚫 Error
has_ai_speakContains “As an AI…”, “I cannot…”🚫 Error
has_clicheContains “hope this finds you well”, “circle back”⚠️ Warning
genericNot personalized enough based on input⚠️ Warning

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Auto-Fix Feature

Smelt automatically fixes certain issues before you see them!
These are stripped automatically from every AI output:
IssueAuto-Fix
Preambles”Here’s a hook:”, “Sure!”, “Certainly!” → Removed
Postambles”Let me know!”, “Hope this helps!” → Removed
Quote wrappersSurrounding quotation marks → Removed
Flags shown in results are issues that couldn’t be auto-fixed.

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Flag Details

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too_short

What it means: Output is under 15 characters. Common causes:
  • AI misunderstood the prompt
  • Input data was insufficient
  • Template constraints too restrictive
How to fix:
  • Edit inline to expand
  • Re-run with revised prompt
  • Check input data quality

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over_char_limit / over_word_limit

What it means: Output exceeded your template’s length constraints. Common causes:
  • AI didn’t fully respect limits
  • Limits set too low for the task
How to fix:
  • Edit to shorten
  • Adjust template limits
  • Make limit clearer in prompt (“MUST be under 100 characters”)

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forbidden_word

What it means: Output contains a word you banned in the template. Common causes:
  • AI used the word despite instructions
  • Word appears in a different form
How to fix:
  • Edit to remove the word
  • Make prohibition clearer in prompt
  • Consider if the word is truly necessary to ban
Forbidden word detection uses word boundaries—“loan” won’t flag “loans” or “alone”.

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has_preamble

What it means: Output starts with AI-style introductions. Examples:
  • “Here’s a hook for you:”
  • “Sure, here’s what I came up with:”
  • “Certainly!”
Why it’s flagged: These should have been auto-fixed. If you see this flag, the preamble pattern wasn’t recognized. How to fix: Edit to remove the preamble manually.

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has_postamble

What it means: Output ends with AI-style sign-offs. Examples:
  • “Let me know if you need changes!”
  • “Hope this helps!”
  • “Feel free to ask for more!”
Why it’s flagged: These should have been auto-fixed. If you see this flag, the postamble pattern wasn’t recognized. How to fix: Edit to remove the postamble manually.

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has_quotes

What it means: Output is wrapped in quotation marks. Example: 
"Scaling your SaaS team in Austin is no small feat—"
Why it’s flagged: Should have been auto-fixed. Quotes suggest the AI is “presenting” rather than “being” the copy. How to fix: Edit to remove surrounding quotes.

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has_placeholder

What it means: Output contains unfilled placeholders. Examples:
  • [Name]
  • {Company}
  • {{variable}}
  • [INSERT CITY HERE]
Common causes:
  • AI left placeholders instead of using data
  • Variable wasn’t found in CSV
  • AI misunderstood the task
How to fix:
  • Check that CSV has the expected columns
  • Edit to fill in the placeholder
  • Re-run after fixing the prompt
This is a serious flag—placeholders will look terrible if sent to prospects!

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has_ai_speak

What it means: Output contains language revealing it’s AI-generated. Examples:
  • “As an AI language model…”
  • “I cannot provide…”
  • “I don’t have access to…”
Common causes:
  • AI broke character
  • Prompt triggered safety responses
  • Unusual input data
How to fix:
  • Edit to remove AI language
  • Revise prompt to prevent this
  • Check input data for issues

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has_cliche

What it means: Output contains overused phrases. Examples:
  • “I hope this email finds you well”
  • “Circle back”
  • “Touch base”
  • “Low-hanging fruit”
  • “Synergy”
Why it matters: These phrases are so common they reduce impact and feel generic. How to fix:
  • Edit to replace with more original phrasing
  • Add clichés to forbidden words list

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generic

What it means: Output doesn’t seem personalized to the specific lead. Detection: Checks if the output could apply to almost any lead rather than being tailored. Common causes:
  • Not enough data in the CSV
  • Prompt doesn’t reference enough variables
  • Template is too general
How to fix:
  • Use more variables in your prompt
  • Add more specific instructions
  • Ensure CSV has relevant data

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Filtering by Quality

In the Results view, filter to show:
FilterShows
All resultsEverything
Has flagsOnly outputs with quality issues
No flagsOnly clean outputs
Review flagged outputs first, then bulk-approve clean ones.

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Quality Flag Strategy

1

Filter to flagged only

Focus on outputs that need attention
2

Review and edit

Fix issues inline or decide to re-run
3

Bulk approve clean outputs

Select all clean outputs and approve
4

Re-run problematic rows

If many rows have issues, revise template and re-run