This skill should be used when the user asks to "clean up a transcript", "fix speech artifacts", "edit interview quotes", "polish transcription", "clean up quotes from a recording", or when working with speech-to-text output that needs light editing while preserving the speaker's voice.
Clean speech-to-text artifacts from transcripts and direct quotes without editorializing. The goal is readability, not rewording. Preserve the speaker's vocabulary, sentence structure, and personality. Fix only what a competent transcriptionist would fix.
If you cannot point to a specific speech artifact or transcription error, do not change the sentence. "Sounds better" is not a reason to edit. Every edit must fall into one of the pattern categories below.
Spoken English uses "like" as a verbal pause. Remove it when it serves no grammatical function. Keep it when it means "such as" or "similar to."
| Before | After | Why |
|---|---|---|
| has like a road map | has a road map | filler before article |
| is like no more than three digits | is no more than three digits | filler before adverb |
| was like AI is important |
| where the message was AI is important |
| filler replacing a clause |
| a mega corp like Apple | a mega corp like Apple | means "such as" -- keep |
| a generic topic like generative engine optimization | a generic topic like generative engine optimization | means "such as" -- keep |
Test: Remove "like" and read the sentence. If it still makes grammatical sense and the meaning is unchanged, the "like" was filler.
Speakers routinely break grammar rules that readers notice on the page. Fix subject-verb agreement and comparison constructions.
| Before | After | Rule |
|---|---|---|
| there's so many signals | there are so many signals | subject-verb agreement ("signals" is plural) |
| as powerful than if we had | as powerful as if we had | "as...as" comparison, not "as...than" |
| as much of a signal than if | as much of a signal as if | same pattern |
Test: Read the sentence aloud slowly. If the grammar error is obvious when spoken deliberately rather than quickly, fix it.
Speakers front-load or rearrange words in ways that read awkwardly on paper. Restore standard English word order.
| Before | After |
|---|---|
| put in specifically keywords | specifically put in keywords |
| that's like deep on a bottom of funnel | that's deep on a bottom-of-funnel |
Mid-sentence restructuring during speech leaves behind words that no longer connect to anything. Remove them.
| Before | After | Orphan |
|---|---|---|
| things that while seem exciting | things that seem exciting | "while" left over from an abandoned clause |
Speech-to-text engines sometimes drop words, merge sentences, or mishear connectives. Restore the minimal missing words needed for the sentence to parse.
| Before | After | Fix |
|---|---|---|
| was like AI is important | where the message was AI is important | restored dropped clause |
| who is higher up in the organization chart like a chief marketing officer | who is higher up in the organization chart, like a chief marketing officer | added comma before "like" (parenthetical example) |
Only add words when the sentence is genuinely unparseable without them. If the meaning is clear despite missing words, leave it alone.
When cleaning quotes embedded in documents (blockquotes, inline quotes), apply extra caution. The reader knows this is a quote from a real person. Overcleaning makes quoted speech sound ghostwritten.
For attributed quotes (with a speaker name), preserve more roughness. The attribution signals "this is how they actually talk." For unattributed quotes used as pull-quotes or callouts, slightly more cleanup is acceptable since the reader expects polished text.
When cleaning an entire transcript or document with many quotes: