ai-dialogue-detector
Detects AI-generated dialogue patterns specific to screenplays: on-the-nose dialogue
Identifies AI-generated dialogue patterns that kill screenplays — the ways machine-written dialogue fails to sound like real people talking under pressure in cinematic situations.
## Key Points
- Dialogue feels "written" rather than "spoken"
- Every character sounds equally smart and articulate
- Scenes feel like therapy sessions or TED talks
- Conflict resolves through monologues instead of action
- Dialogue is doing all the work because the AI can't write visually
- Coverage readers flag dialogue as the primary weakness
- "As you know..."
- One character explaining something the other would already know
- Dialogue that exists solely to inform the audience
- Characters asking questions they'd know the answer to
- Monologues summarizing backstory, lore, or world rules
- Every character speaks in complete sentences
## Quick Example
```
DETECTIVE CHEN
Same block as the Holloway case.
DETECTIVE RUSSO
Don't start.
```skilldb get screenplay-audit-skills/ai-dialogue-detectorFull skill: 273 linesAI Dialogue Detector (Screenplay)
Identifies AI-generated dialogue patterns that kill screenplays — the ways machine-written dialogue fails to sound like real people talking under pressure in cinematic situations.
When to Use This Skill
- Dialogue feels "written" rather than "spoken"
- Every character sounds equally smart and articulate
- Scenes feel like therapy sessions or TED talks
- Conflict resolves through monologues instead of action
- Dialogue is doing all the work because the AI can't write visually
- Coverage readers flag dialogue as the primary weakness
The AI Screenplay Dialogue Tells
Tell 1 — On-the-Nose Dialogue
Characters say exactly what they think and feel. No gap between intention and expression. This is the #1 AI dialogue problem in screenplays because film dialogue lives in the gap between what characters say and what they mean.
AI writes:
SARAH
I'm angry at you because you
lied to me and I feel betrayed.
MARK
I know I hurt you. I was afraid
of losing you, so I made a
terrible choice. I'm sorry.
A screenwriter writes:
SARAH
How was work?
MARK
Fine.
SARAH
Good. That's good.
(beat)
Your mother called.
MARK
What did you tell her?
SARAH
What do you think I told her?
The anger, betrayal, and lie are all present. Neither character names them. The audience feels more because they have to lean in.
Detection method: For each line of dialogue, ask: is the character saying what they mean, or something adjacent to what they mean? If more than 40% of dialogue is characters directly stating their feelings, motivations, or assessments, the script is on-the-nose.
Tell 2 — Exposition Dumps ("As You Know, Bob")
Characters tell each other information they both already know, purely for the audience's benefit.
AI writes:
DETECTIVE CHEN
As you know, the victim was found
at 3 AM in the warehouse district.
The same warehouse district where
those three murders happened last
year, which we never solved.
A screenwriter writes:
DETECTIVE CHEN
Same block as the Holloway case.
DETECTIVE RUSSO
Don't start.
Two lines. The audience gets that there's history, unresolved cases, and tension between the detectives. The AI version is a news report.
Detection method: Search for:
- "As you know..."
- One character explaining something the other would already know
- Dialogue that exists solely to inform the audience
- Characters asking questions they'd know the answer to
- Monologues summarizing backstory, lore, or world rules
Tell 3 — Universal Eloquence
Every character speaks at the same vocabulary and emotional intelligence level. The CEO and the janitor both construct perfect sentences. Nobody stumbles, interrupts, or says something stupid.
What AI does:
- Every character speaks in complete sentences
- Every character can articulate their emotions precisely
- No one uses filler words (um, uh, like, I mean, well, look)
- No one interrupts or talks over each other
- Every character's dialogue could be swapped with any other character's
What real screenplay dialogue does:
- Characters have different vocabularies, rhythms, and intelligence levels
- Some characters are inarticulate — they can't find the words, and that's the drama
- Interruptions convey power dynamics (who gets to finish their sentence?)
- Characters misunderstand each other because they're not really listening
- One character speaks in run-on sentences while another speaks in fragments
The swap test: Take a line from Character A and attribute it to Character B. Does it still sound right? If yes for more than 50% of lines, all characters have the same voice.
Tell 4 — Conflict Resolution by Monologue
AI resolves dramatic conflict through one character delivering a perfect speech that changes the other person's mind.
AI writes:
JAMES
You know what your problem is?
You're so afraid of being hurt
that you push everyone away. But
that's not strength — it's fear
dressed up as independence. And
someday you're going to realize
that the people you pushed away
were the only ones who ever really
saw you.
Sarah's eyes fill with tears. She nods slowly.
SARAH
You're right. I've been so afraid.
A screenwriter writes:
James says something clumsy and wrong. Sarah walks out. James follows. They argue in the parking lot. Neither changes the other's mind. Three scenes later, Sarah does something that shows she heard him — but she'd never admit it.
Detection method: Search for monologues (4+ consecutive lines from one character) that:
- Diagnose another character's psychological problem
- End with the other character agreeing or being visibly moved
- Resolve a conflict that's been building for multiple scenes
- Sound like they were written, rehearsed, and delivered perfectly
Tell 5 — Therapy-Speak
Characters talk like therapists or therapy patients — using clinical emotional language that real people don't use outside a therapist's office.
AI dialogue red flags:
- "I feel like you're not hearing me"
- "I need you to validate my experience"
- "That's your trauma talking"
- "I'm setting a boundary"
- "You're projecting"
- "I need to sit with that"
- "That triggers me"
- "I hear you, and I appreciate your vulnerability"
Some characters (actual therapists, overly online millennials) might talk this way. When EVERY character does, it's AI default.
Tell 6 — The Summarizing Scene
AI writes scenes where characters discuss what happened in previous scenes instead of showing new events.
ALEX
I can't believe what happened
at the restaurant last night.
JORDAN
I know. When she said that thing
about your father, I thought you
were going to lose it.
ALEX
I almost did. But then I thought
about what Dr. Walsh said.
This scene is a podcast recap. The restaurant scene should have been ON SCREEN. If it was, this scene is redundant. If it wasn't, it should have been instead of this one.
Detection method: Count scenes where characters discuss events vs. scenes where events happen. If the ratio exceeds 30% discussion, the script is summarizing instead of dramatizing.
Tell 7 — Question-Answer Tennis
AI defaults to dialogue structured as Q&A — one character asks questions, the other answers. This creates the rhythm of an interview, not a conversation.
EMMA
Where were you last night?
RYAN
I was at Jake's.
EMMA
Until what time?
RYAN
Around midnight.
EMMA
And you didn't think to call?
RYAN
I didn't think you'd care.
Real conversations are messier. People answer questions with questions. They deflect. They answer a different question than the one asked. They change the subject. They attack.
Scoring
Per-Scene Dialogue Score
For each scene with dialogue:
| Metric | Score 1-5 | 1 = | 5 = |
|---|---|---|---|
| Subtext | Characters say what they mean | Meaning lives beneath the words | |
| Voice distinction | All characters sound the same | Each voice is unmistakable | |
| Exposition handling | Info dumps in dialogue | Information woven into conflict | |
| Economy | Overwritten, 10 lines where 3 would do | Every line earns its place | |
| Speakability | Reads like prose | Sounds like real speech rhythms | |
| Conflict | Characters agree or resolve quickly | Dialogue crackles with opposing wants | |
| Behavior gap | Dialogue carries all meaning | Action/behavior contradicts or complicates words |
Manuscript-Level Metrics
- On-the-nose percentage: [N]% of dialogue directly states feelings/motivations
- Exposition dump count: [N] scenes with dialogue-as-information
- Monologue resolution count: [N] conflicts resolved by speech
- Voice distinction score: [swap test results]
- Summarizing scene count: [N] scenes discussing offscreen events
Rewrite Principles
For every flagged line:
- What does the character WANT in this moment? (not feel — want)
- What are they ACTUALLY saying to get it? (probably not the truth)
- What's the other character doing while they talk? (action reveals more than words)
- What would this character NEVER say? (negative space defines voice)
- Can this line be cut entirely? (the best dialogue revision is often deletion)
The Silence Test
For every scene: what if you removed all the dialogue and played it silent? Would the audience still understand what's happening from the visuals and behavior alone? If not, the dialogue is doing too much. Film is a visual medium.
Anti-Patterns
- Making all dialogue oblique. Not every line needs subtext. Sometimes "Pass the salt" means pass the salt. The key scenes need subtext; functional scenes can be direct.
- Removing all exposition. The audience needs information. The craft is delivering it during conflict, not eliminating it. The best exposition happens when a character is forced to reveal information they'd rather hide.
- Adding profanity for "realism." Swearing doesn't make dialogue authentic. Specificity, rhythm, and behavioral truth do.
- Rewriting dialogue without understanding the scene's purpose. Every scene has a function. Dialogue rewrites must serve that function, not just "sound better."
- Applying novel-dialogue standards. Screenplay dialogue is terser, more interrupted, and more dependent on the actor's delivery. Leave room for performance.
Install this skill directly: skilldb add screenplay-audit-skills
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