NC Bench
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Run: 2026-03-25-01KMJ853Z5JWYVET6GHGXETKTP
Run Details
Model:
Qwen 3 32B
Test:
Bad Writing Habits
Scenario:
Literary fiction: old friends reunite
Duration:
30.7s
Cost:
$0.001118
Provider:
DeepInfra
Evaluation summary
Score
Evaluator
Details Link
100.00%
Adverbs in dialogue tags
(details)
85.73%
AI-ism adverb frequency
(details)
100.00%
AI-ism character names
(details)
100.00%
AI-ism location names
(details)
21.54%
AI-ism word frequency
(details)
100.00%
Cliché density
(details)
100.00%
Emotion telling (show vs. tell)
(details)
100.00%
Filter word density
(details)
94.93%
Gibberish response detection
(details)
100.00%
Markdown formatting overuse
(details)
100.00%
Missing dialogue indicators (quotation marks)
(details)
57.41%
Name drop frequency
(details)
100.00%
Narrator intent-glossing
(details)
57.14%
"Not X but Y" pattern overuse
(details)
100.00%
Overuse of "that" (subordinate clause padding)
(details)
100.00%
Paragraph length variance
(details)
100.00%
Passive voice overuse
(details)
100.00%
Past progressive (was/were + -ing) overuse
(details)
72.31%
Em-dash & semicolon overuse
(details)
100.00%
Purple prose (modifier overload)
(details)
100.00%
Repeated phrase echo
(details)
100.00%
Sentence length variance
(details)
65.43%
Sentence opener variety
(details)
100.00%
Adverb-first sentence starts
(details)
81.54%
Pronoun-first sentence starts
(details)
0.00%
Subject-first sentence starts
(details)
0.00%
Subordinate conjunction sentence starts
(details)
100.00%
Technical jargon density
(details)
0.00%
Useless dialogue additions
(details)
100.00%
Dialogue tag variety (said vs. fancy)
(details)
81.2014%
Overall
Model input
System
You are an expert and award-winning novel writer in the dark Literary Fiction genre. Your readers are hooked on your stories and can't wait to read the book you have in store. <important> - MUST: Start each chapter in medias res (in the middle of action). AVOID talking about the weather, time of day, the position of the sun, or other boring stuff. - The instructions/summary are just a that, a summary. Feel free to add details, stretch sections and add interesting transitions/descriptions/fillers. - When called for it, have fast-paced action, but otherwise take things slow. This is an experience, and not for people with short attention spans. Enjoy the wine, not slurp Red Bull. - Add descriptions when transitioning places/times/etc, or when coming by new places (e.g. a corner shop, a cafe, etc.). But remember: NOT at the start or end of a chapter. - MUST: AVOID ending in internal monologue, reminiscing or waiting for the next day. A good chapter end is when we're ending right when shit hits the fan. We want to have the reader be excited for what comes next. So no reminiscing, contemplating or summarizing the day. It's popcorn time! </important>
User/Human
Take into account the following glossary of characters/locations/items/lore... when writing your response: <codex> <character id="4412" name="Aurora Carter" aliases="Rory, Laila, Aurora, Carter, Malphora" pronouns="she/her" species="Human" storyRole="Protagonist"> <eyeColor>bright blue</eyeColor> <hair>straight shoulder-length black</hair> <height>5'6"</height> <age>25</age> <scar>small crescent-shaped scar on her left wrist from a childhood accident</scar> <description>Aurora, referred to by her friends as Rory, is cool-headed, intelligent, and known for quick out-of-the-box thinking.</description> <backstory>Born in Cardiff to an Irish barrister father (Brendan Carter) and Welsh teacher mother (Jennifer Carter née Ellis), Rory reluctantly pursued Pre-Law at Cardiff University. She fled to London at the behest of her childhood friend Eva after leaving an abusive ex named Evan. By day, Rory works part-time as a delivery person for Yu-Fei Cheung's Golden Empress restaurant. She lives in a flat above Silas' bar.</backstory> </character> <character id="4413" name="Silas Blackwood" aliases="Silas, Si, the Spymaster" pronouns="he/him" species="Human" storyRole="Mentor"> <eyeColor>hazel</eyeColor> <hair>grey-streaked auburn</hair> <height>6'1"</height> <age>58</age> <beard>neatly trimmed, matching his grey-streaked auburn hair</beard> <limp>slight limp in his left leg from an old knee injury</limp> <signetRing>silver signet ring, always worn on his right hand</signetRing> <description>Silas is a retired intelligence operative turned bar owner. He carries himself with quiet authority.</description> <backstory>Former MI6 field agent who retired after a botched operation in Prague left him with a permanent knee injury. He opened "The Raven's Nest" bar in Soho as a front for his network of contacts.</backstory> </character> <location id="854" name="The Raven's Nest" aliases="the Nest, Raven, Silas' bar" realm="Earth"> <signColor>distinctive green neon sign above the entrance</signColor> <secretRoom>hidden back room accessible through a bookshelf, used for clandestine meetings</secretRoom> <description>A dimly lit bar in Soho, London. The walls are covered with old maps and black-and-white photographs.</description> </location> </codex> <proseGuidelines> <styleGuide> - Write in past tense and use British English spelling and grammar - Keep a Flesch reading ease score of 60 - Respect the the Royal Order of Adjectives: The order is: opinion, size, age, shape, color, origin, material, purpose, followed by the noun itself (e.g., "a lovely little old rectangular green French silver whittling knife") - Respect the ablaut reduplication rule (e.g. tick-tock, flip-flop) - Write in active voice - Passive voice: <bad>The book was read by Sarah.</bad> - Active voice: <good>Sarah read the book.</good> - Reduce the use of passive verbs - <bad>For a moment, I was tempted to throw in the towel.</bad> - <good>For a moment, I felt tempted to throw in the towel.</good> - Avoid misplaced modifiers that can cause confusion when starting with "-ing" words: - <bad>Considering going to the store, the empty fridge reflected in Betty's eyes.</bad> - <good>Betty stared into the empty fridge. It was time to go to the store.</good> - Avoid redundant adverbs that state the obvious meaning already contained in the verb: - <bad>She whispered quietly to her mom.</bad> - <good>She whispered to her mom.</good> - Use stronger, more descriptive verbs over weak ones: - <bad>Daniel drove quickly to his mother's house.</bad> - <good>Daniel raced to his mother's house.</good> - Omit adverbs that don't add solid meaning like "extremely", "definitely", "truly", "very", "really": - <bad>The movie was extremely boring.</bad> - <good>The movie was dull.</good> - Use adverbs to replace clunky phrasing when they increase clarity: - <bad>He threw the bags into the corner in a rough manner.</bad> - <good>He threw the bags into the corner roughly.</good> - Avoid making simple thoughts needlessly complex: - <bad>After I woke up in the morning the other day, I went downstairs, turned on the stove, and made myself a very good omelet.</bad> - <good>I cooked a delicious omelet for breakfast yesterday morning.</good> - Never backload sentences by putting the main idea at the end: - <bad>I decided not to wear too many layers because it's really hot outside.</bad> - <good>It's sweltering outside today, so I dressed light.</good> - Omit nonessential details that don't contribute to the core meaning: - <bad>It doesn't matter what kind of coffee I buy, where it's from, or if it's organic or not—I need to have cream because I really don't like how the bitterness makes me feel.</bad> - <good>I add cream to my coffee because the bitter taste makes me feel unwell.</good> - Always follow the "show, don't tell" principle. For instance: - Telling: <bad>Michael was terribly afraid of the dark.</bad> - Showing: <good>Michael tensed as his mother switched off the light and left the room.</good>- Telling: <bad>I walked through the forest. It was already Fall, and I was getting cold.</bad> - Showing: <good>Dry orange leaves crunched under my feet. I pulled my coat's collar up and rubbed my hands together.</good>- Add sensory details (sight, smell, taste, sound, touch) to support the "showing" (but keep an active voice) - <bad>The room was filled with the scent of copper.</bad> - <good>Copper stung my nostrils. Blood. Recent.</good> - Use descriptive language more sporadically. While vivid descriptions are engaging, human writers often use them in bursts rather than consistently throughout a piece. When adding them, make them count! Like when we transition from one location to the next, or someone is reminiscing their past, or explaining a concept/their dream... - Avoid adverbs and clichés and overused/commonly used phrases. Aim for fresh and original descriptions. - Avoid writing all sentences in the typical subject, verb, object structure. Mix short, punchy sentences with long, descriptive ones. Drop fill words to add variety. Like so: <good>Locked. Seems like someone doesn't want his secrets exposed. I can work with that.</good> - Convey events and story through dialogue. It is important to keep a unique voice for every character and make it consistent. - Write dialogue that reveals characters' personalities, motivations, emotions, and attitudes in an interesting and compelling manner - Leave dialogue unattributed. If needed, only use "he/she said" dialogue tags and convey people's actions or face expressions through their speech. Dialogue always is standalone, never part of a paragraph. Like so: - <bad>"I don't know," Helena said nonchalantly, shrugging her shoulders</bad> - <good>"No idea" "Why not? It was your responsibility"</good> - Avoid boring and mushy dialog and descriptions, have dialogue always continue the action, never stall or include unnecessary fluff. Vary the descriptions to not repeat yourself. Avoid conversations that are just "Let's go" "yes, let's" or "Are you ready?" "Yes I'm ready". Those are not interesting. Think hard about every situtation and word of text before writing dialogue. If it doesn't serve a purpose and it's just people talking about their day, leave it. No one wants to have a normal dinner scene, something needs to happen for it to be in the story. Words are expensive to print, so make sure they count! - Put dialogue on its own paragraph to separate scene and action. - Use body language to reveal hidden feelings and implied accusations- Imply feelings and thoughts, never state them directly - NEVER use indicators of uncertainty like "trying" or "maybe" - NEVER use em-dashes, use commas for asides instead </styleGuide> <voiceGuide> Each character in the story needs to have distinct speech patterns: - Word choice preferences - Sentence length tendencies - Cultural/educational influences - Verbal tics and catchphrases Learn how each person talks and continue in their style, and use their Codex entries as reference. <examples> - <bad>"We need to go now." "Yes, we should leave." "I agree."</bad> <good>"Time's up." "Indeed, our departure is rather overdue." "Whatever, let's bounce."</good> - Power Dynamic Example: <bad> "We need to discuss the contract." "Yes, let's talk about it." "I have concerns." </bad> <good> "A word about the contract." "Of course, Mr. Blackwood. Whatever you need." "The terms seem..." A manicured nail tapped the desk. "Inadequate." "I can explain every-" "Can you?" </good> </examples> </voiceGuide> <dialogueFlow> When writing dialogue, consider that it usually has a goal in mind, which gives it a certain flow. Make dialogue sections also quite snappy in the back and forth, and don't spread the lines out as much. It's good to have details before, after, or as a chunk in-between, but we don't want to have a trail of "dialogue breadcrumbs" spread throughout a conversation. <examples> - Pattern 1 - Question/Deflection/Revelation: <good> "Where were you last night?" "Work. The usual." "Lipstick's an interesting shade for spreadsheets." </good> - Pattern 2 - Statement/Contradiction/Escalation: <good> "Your brother's clean." "Tommy doesn't touch drugs." "I'm holding his tox screen." </good> - Pattern 3 - Observation/Denial/Truth: <good> "That's a new watch." "Birthday gift." "We both know what birthdays mean in this business." </good> - Example - A Simple Coffee Order: <bad> "I'll have a coffee." "What size?" "Large, please." </bad> <good> "Black coffee.""Size?""Large. Been a long night." "That bodega shooting?" "You watch too much news." "My brother owns that store." </good> This short exchange: - Advances plot (reveals connection to crime) - Shows character (cop working late) - Creates tension (unexpected connection) - Sets up future conflict (personal stake) - Example - Dinner Scene: <bad> "Pass the salt." "Here you go." "Thanks." </bad> <good> "Salt?" "Perfect as is. Mother's recipe." "Mother always did prefer... bland things." "Unlike your first wife?" </good> - Example - Office Small Talk: <bad> "Nice weather today." "Yes, very nice." "Good for golf." </bad> <good> "Perfect golf weather." "Shame about your membership." "Temporary suspension. Board meets next week." "I know. I called the vote." </good> </examples> </dialogueFlow> <subtextGuide> - Layer dialogue with hidden meaning: <bad>"I hate you!" she yelled angrily.</bad> <good>"I made your favorite dinner." The burnt pot sat accusingly on the stove.</good> - Create tension through indirect communication: <bad>"Are you cheating on me?"</bad> <good>"Late meeting again?" The lipstick stain on his collar caught the light.</good> <examples> - Example 1 - Unspoken Betrayal: <bad> "Did you tell them about our plans?" "No, I would never betray you." "I don't believe you." </bad> <good> "Funny. Johnson mentioned our expansion plans today." "The market's full of rumors." "Mentioned the exact numbers, actually." The pen in his hand snapped. </good> - Example 2 - Failed Marriage: <bad> "You're never home anymore." "I have to work late." "I miss you." </bad> <good> "Your dinner's in the microwave. Again." "Meetings ran long." "They always do." She folded the same shirt for the third time. </good> - Example 3 - Power Struggle: <bad> "You can't fire me." "I'm the boss." "I'll fight this." </bad> <good> "That's my father's nameplate you're sitting behind." "Was." "The board meeting's on Thursday." </good> </examples> </subtextGuide> <sceneDetail> While writing dialogue makes things more fun, sometimes we need to add detail to not have it be a full on theatre piece. <examples> - Example A (Power Dynamic Scene) <good> "Where's my money?" The ledger snapped shut. "I need more time." "Interesting." He pulled out a familiar gold pocket watch. My mother's. "Time is exactly what you bargained with last month." "That was different-" "Was it?" The watch dangled between us. "Four generations of O'Reillys have wound this every night. Your mother. Your grandmother. Your great-grandmother.Shall we see who winds it next?" </good> - Example B (Action Chase) It's much better to be in the head of the character experiencing it, showing a bit of their though-process, mannerisms and personality: <good> Three rules for surviving a goblin chase in Covent Garden: Don't run straight. Don't look back. Don't let them herd you underground. I broke the first rule at Drury Lane. Rookie mistake. The fruit cart I dodged sailed into the wall behind me. Glass shattered. Someone screamed about insurance. *Tourist season's getting rough*, the scream seemed to say. Londoners adapt fast. "Oi! Market's closed!" The goblin's accent was pure East End. They're evolving. Learning. I spotted the Warren Street tube station sign ahead. *Shit.* There went rule three. </good> - Example C (Crime Scene Investigation) <good> "Greek." Davies snapped photos of the symbols. "No, wait. Reverse Greek." "Someone's been watching too many horror films." I picked up a receipt from the floor. Occult supply shop in Camden. Paid by credit card. *Amateur hour*. "Could be dangerous though," Davies said. "Remember Bristol?" "Bristol was Sanskrit. And actual cultists." I pointed to the nearest symbol. "This genius wrote 'darkness' backwards but used a Sigma instead of an S. It's summoning Instagram followers at best." "Speaking of followers..." Davies pointed to heavy foot traffic in the dust. Multiple sets. All new trainers. *Ah.* "Anyone check local uni paranormal societies?" </good> - Example D (Dialogue-heavy) <good> "Found your card in her wallet." The detective slid it across the table. Worn edges. Folded corner. Three years old at least. "Standard practice. I work missing persons." "Funny thing about missing persons.Eventually they stop being missing. Turn up in the Thames. Under motorways. In pieces." "I don't-" "You found four last year. All breathing." She opened a file. "This would've been your first dead one. If we hadn't found her first." The card felt heavier somehow. </good> </examples> </sceneDetail> <sceneOpenings> KEY RULE: Never open with more than one paragraph of description, no matter how beautiful. Description should be earned through action and dialogue. Instead of opening with setting description, open with: - A character doing something specific - A line of dialogue that raises questions - An unexpected observation - A moment of tension or conflict - Start with a hook that's 1-2 sentences maximum - Follow with a smaller paragraph that provides immediate context - Vary paragraph size from the start to create visual interest </sceneOpenings> </proseGuidelines> Write a chapter based on the following instructions: <instructions> Write a fully fleshed out scene of at least 1000 words in the literary fiction genre. Two old friends who haven't seen each other in years run into each other unexpectedly at a bar. One of them has changed significantly. Through their conversation and the tension between who they were and who they've become, reveal the weight of time and unspoken regret. Use the codex entries above as your world reference for characters and setting. Only include the prose of the scene without any markdown or commentary. </instructions>
Model response
Messages
Meta
AI
The ice clinked as Aurora
slid the tumbler across the counter.
Her scar caught the green
neon glare—a thin crescent moon against pale skin.
The Raven’s Nest buzzed with
the murmur of patrons and the clatter of glasses, but her eyes stayed fixed on the condensation pooling around the rim of her drink. A mistake.
Always a mistake to let
the gin go warm. “Rory.”
The velvet drawl of his
voice froze the gin in her glass. “
You
’re twirling your napkin like a girl with a guilty secret.” She looked up. Silas leaned on his cane, the silver ring
glinting
as he tapped the worn wood. His hazel eyes missed nothing. “
I
was never good at secrets, Mr. Blackwood.” “
You
called me *
Si
* once.”
He nodded at her wrist
. “That scar. Not from a kitchen knife, is it?” Aurora froze.
The napkin bunched in her
fist. “Tourist trap in Cardiff. Stupidity,
really
.” “Hmm.”
Silas’s cane shifted, the faint
creak of his limp cutting through the bar’s ambient noise.
He didn’t look at her
scar anymore. He
was dissecting
the lie. “Tourists don’t一般 trip over broken bottles in their own hometown.”
The ghost of Evan’s hand
flared across her ribs.
She drowned it with a
gulp of gin. “
You
sound like a man who’s heard too many confessions.” “A man who’s buried too many bodies.”
Silas angled his cane between
them, a subtle barrier. “
You
left Cardiff without saying goodbye.” “
I
didn’t think you’d miss me.”
His smile was a rusted
hinge. “
You
thought
I
’d let you burn alone?”
A laugh tore out of
her, sharp as
shattered
glass. “
You
didn’t exactly send balloons and roses when
I
turned my back on law school.” “Law is a cage for people who like to pretend they’re free.”
He gestured to the bar’s
shadowed corners, to the maps spanning centuries on peeling walls. “
You
ever notice how every escape route here leads back to a dead end?”
The bartender slammed a fresh
gin and tonic in front of her. Aurora didn’t flinch. “What’s your point,
Si
?”
His fingers drummed the ring
against the cane. “
You
’re skimming the take at Yu-Fei’s. Again.” Her chin tilted back. “And you’re still playing spy with cocktail napkins.” Silas leaned in. The gin bottle
trembled
in her hand. “Three hundred pounds short this week. Cash-in-transit van robbed off Regent’s Street.
You
were within shouting distance when it went down.” Aurora’s
pulse
thrummed in her throat. The air between them thickened with
unspoken
years. “Let me guess.”
She set the glass down
slowly
. “
You
want me to fix it. For old time’s sake.” “For the sake of you not ending up like
Laila
’s sister.” The name hung, a blade unsheathed. Her breath hitched. *
Laila
*. The name she’d buried with her mother’s ashes. The scar on her wrist burned. Silas kept talking, smooth as a lie he’d rehearsed for decades. “A ‘bystander’ who didn’t *
quite
* see the license plate. A restaurant worker with a habit of ‘losing’ money. Someone with your particular set of… talents.” The front door swung open. Footsteps. Two of them. Heavy. “
Not interested,” Aurora said, but her voice frayed at the edges
. Silas’s cane moved a fraction, blocking her exit. “He’s here, by the way. Evan.” The
footsteps
halted. “
You
told him,” she whispered. “**
I
** didn’t.”
His gaze flicked to the
door. “But he’s been asking about people who know you. People who *
knew
* you.” Aurora was on her feet, coat slipping on. “Stay out of this.” “*
You
* stay out of this.”
The cane thudded, final
. “Or
I
’ll have to bury another body.”
She didn’t look back as
the door slammed. Silas stared at the empty seat, the half-drunk gin.
His cane clattered against the
floor as movement flooded his legs—*
the old reflexes
*—too late. The man in the doorway wore Evan’s face, but his eyes gleamed with something new. Professional. “Mr. Blackwood,”
he said, voice syrup-thick with
menace, “we need to talk about your knee.” The secret room’s bookshelf ground open behind him, a
whisper
of oiled gears. Silas didn’t move.
He could hear the clock
ticking in his skull. Three more seconds. Two. A shadow engulfed him.
Somewhere in the distance, the
gin bottle
shattered
.
created_at
"2026-03-25T10:20:29.547Z"
3/25/2026, 10:20:29 AM
model
"qwen/qwen3-32b-04-28"
app_id
182717
external_user
(null)
streamed
true
cancelled
false
latency
350
moderation_latency
(null)
generation_time
30606
tokens_prompt
4641
tokens_completion
3209
native_tokens_prompt
4217
native_tokens_completion
2788
native_tokens_completion_images
(null)
native_tokens_reasoning
2028
native_tokens_cached
0
num_media_prompt
(null)
num_input_audio_prompt
(null)
num_media_completion
0
num_search_results
(null)
origin
"https://ncbench.com/"
is_byok
false
finish_reason
"stop"
native_finish_reason
"stop"
usage
0.001118
router
(null)
provider_responses
0
endpoint_id
"6b8c829d-3094-45e7-8139-0a67e09060c3"
id
"cmpl-3d54af3e2b7249ae8b5ea87ebb7f6a22"
is_byok
false
latency
82
model_permaslug
"qwen/qwen3-32b-04-28"
provider_name
"DeepInfra"
status
200
user_agent
"langchainjs-openai/1.0.0 ((node/v24.14.0; linux; x64))"
http_referer
(null)
api_type
"completions"
id
"gen-1774434029-Ahln5LEyM5LbM9DFlmD7"
upstream_id
"cmpl-3d54af3e2b7249ae8b5ea87ebb7f6a22"
total_cost
0.001118
cache_discount
(null)
upstream_inference_cost
0
provider_name
"DeepInfra"
Evaluation details
Result
Evaluator
Details
Meta Data
100.00%
Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags
12
adverbTagCount
0
adverbTags
(empty)
dialogueSentences
33
tagDensity
0.364
leniency
0.727
rawRatio
0
effectiveRatio
0
85.73%
AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount
701
totalAiIsmAdverbs
2
found
0
adverb
"really"
count
1
1
adverb
"slowly"
count
1
highlights
0
"really"
1
"slowly"
100.00%
AI-ism character names
Target: 0 AI-default names (16 tracked, −20% each)
codexExemptions
0
"Blackwood"
found
(empty)
100.00%
AI-ism location names
Target: 0 AI-default location names (33 tracked, −20% each)
codexExemptions
(empty)
found
(empty)
21.54%
AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount
701
totalAiIsms
11
found
0
word
"velvet"
count
1
1
word
"glinting"
count
1
2
word
"shattered"
count
2
3
word
"trembled"
count
1
4
word
"pulse"
count
1
5
word
"unspoken"
count
1
6
word
"footsteps"
count
2
7
word
"flicked"
count
1
8
word
"whisper"
count
1
highlights
0
"velvet"
1
"glinting"
2
"shattered"
3
"trembled"
4
"pulse"
5
"unspoken"
6
"footsteps"
7
"flicked"
8
"whisper"
100.00%
Cliché density
Target: ≤1 cliche(s) per 800-word window
totalCliches
0
maxInWindow
0
found
(empty)
highlights
(empty)
100.00%
Emotion telling (show vs. tell)
Target: ≤3% sentences with emotion telling
emotionTells
0
narrationSentences
60
matches
(empty)
100.00%
Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount
0
hedgeCount
0
narrationSentences
60
filterMatches
(empty)
hedgeMatches
(empty)
94.93%
Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences
81
gibberishSentences
1
adjustedGibberishSentences
1
longSentenceCount
0
runOnParagraphCount
0
giantParagraphCount
0
wordSaladCount
0
repetitionLoopCount
0
controlTokenCount
0
maxSentenceWordsSeen
29
ratio
0.012
matches
0
"“Tourists don’t一般 trip over broken bottles in their own hometown.”"
100.00%
Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans
7
markdownWords
9
totalWords
700
ratio
0.013
matches
0
"Si"
1
"Laila"
2
"quite"
3
"I"
4
"knew"
5
"You"
6
"the old reflexes"
100.00%
Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions
8
unquotedAttributions
0
matches
(empty)
57.41%
Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions
18
wordCount
432
uniqueNames
5
maxNameDensity
1.85
worstName
"Silas"
maxWindowNameDensity
2.5
worstWindowName
"Silas"
discoveredNames
Aurora
6
Raven
1
Nest
1
Evan
2
Silas
8
persons
0
"Aurora"
1
"Raven"
2
"Nest"
3
"Evan"
4
"Silas"
places
(empty)
globalScore
0.574
windowScore
0.833
100.00%
Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences
37
glossingSentenceCount
0
matches
(empty)
57.14%
"Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches
1
per1kWords
1.429
wordCount
700
matches
0
"Not interested,” Aurora said, but her voice frayed at the edges"
100.00%
Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount
0
totalSentences
81
matches
(empty)
100.00%
Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs
40
mean
17.5
std
11.9
cv
0.68
sampleLengths
0
64
1
24
2
23
3
8
4
19
5
14
6
38
7
27
8
22
9
6
10
13
11
25
12
41
13
19
14
15
15
12
16
31
17
14
18
19
19
17
20
18
21
36
22
10
23
11
24
14
25
3
26
5
27
21
28
12
29
16
30
8
31
23
32
16
33
15
34
13
35
12
36
3
37
1
38
4
39
8
100.00%
Passive voice overuse
Target: ≤2% passive sentences
passiveCount
0
totalSentences
60
matches
(empty)
100.00%
Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount
1
totalVerbs
74
matches
0
"was dissecting"
72.31%
Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount
3
semicolonCount
0
flaggedSentences
2
totalSentences
81
ratio
0.025
matches
0
"Her scar caught the green neon glare—a thin crescent moon against pale skin."
1
"His cane clattered against the floor as movement flooded his legs—*the old reflexes*—too late."
100.00%
Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount
435
adjectiveStacks
0
stackExamples
(empty)
adverbCount
7
adverbRatio
0.016091954022988506
lyAdverbCount
1
lyAdverbRatio
0.0022988505747126436
100.00%
Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences
81
echoCount
0
echoWords
(empty)
100.00%
Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences
81
mean
8.64
std
5.6
cv
0.648
sampleLengths
0
11
1
13
2
29
3
2
4
9
5
13
6
11
7
3
8
15
9
5
10
8
11
10
12
9
13
2
14
6
15
6
16
16
17
7
18
5
19
10
20
9
21
8
22
10
23
16
24
6
25
6
26
6
27
7
28
10
29
15
30
27
31
14
32
12
33
3
34
4
35
8
36
7
37
4
38
8
39
3
40
7
41
21
42
6
43
8
44
9
45
10
46
17
47
3
48
1
49
8
65.43%
Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats
2
diversityRatio
0.4074074074074074
totalSentences
81
uniqueOpeners
33
100.00%
Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount
2
totalSentences
52
matches
0
"Always a mistake to let"
1
"Somewhere in the distance, the"
ratio
0.038
81.54%
Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount
18
totalSentences
52
matches
0
"Her scar caught the green"
1
"She looked up."
2
"His hazel eyes missed nothing."
3
"He nodded at her wrist"
4
"He didn’t look at her"
5
"He was dissecting the lie."
6
"She drowned it with a"
7
"His smile was a rusted"
8
"He gestured to the bar’s"
9
"His fingers drummed the ring"
10
"Her chin tilted back."
11
"She set the glass down"
12
"Her breath hitched."
13
"His gaze flicked to the"
14
"She didn’t look back as"
15
"His cane clattered against the"
16
"he said, voice syrup-thick with"
17
"He could hear the clock"
ratio
0.346
0.00%
Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount
48
totalSentences
52
matches
0
"The ice clinked as Aurora"
1
"Her scar caught the green"
2
"The Raven’s Nest buzzed with"
3
"The velvet drawl of his"
4
"She looked up."
5
"Silas leaned on his cane,"
6
"His hazel eyes missed nothing."
7
"He nodded at her wrist"
8
"The napkin bunched in her"
9
"Silas’s cane shifted, the faint"
10
"He didn’t look at her"
11
"He was dissecting the lie."
12
"The ghost of Evan’s hand"
13
"She drowned it with a"
14
"Silas angled his cane between"
15
"His smile was a rusted"
16
"A laugh tore out of"
17
"He gestured to the bar’s"
18
"The bartender slammed a fresh"
19
"Aurora didn’t flinch."
ratio
0.923
0.00%
Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount
0
totalSentences
52
matches
(empty)
ratio
0
100.00%
Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences
11
technicalSentenceCount
0
matches
(empty)
0.00%
Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags
12
uselessAdditionCount
3
matches
0
"Aurora said, but her voice frayed at the edges"
1
"The cane thudded, final"
2
"he said, voice syrup-thick with menace,"
100.00%
Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags
3
fancyCount
1
fancyTags
0
"she whispered (whisper)"
dialogueSentences
33
tagDensity
0.091
leniency
0.182
rawRatio
0.333
effectiveRatio
0.061
81.2014%