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Run: 2026-03-18-01KM0A70S5YKK0RA9AEQTCKT0S
Run Details
Model:
GPT-5.4 Mini (Reasoning, Low)
Test:
Bad Writing Habits
Scenario:
Mystery: examining a crime scene
Duration:
15.3s
Cost:
$0.013973
Provider:
OpenAI
Evaluation summary
Score
Evaluator
Details Link
100.00%
Adverbs in dialogue tags
(details)
92.97%
AI-ism adverb frequency
(details)
100.00%
AI-ism character names
(details)
100.00%
AI-ism location names
(details)
83.61%
AI-ism word frequency
(details)
66.67%
Cliché density
(details)
100.00%
Emotion telling (show vs. tell)
(details)
100.00%
Filter word density
(details)
100.00%
Gibberish response detection
(details)
100.00%
Markdown formatting overuse
(details)
100.00%
Missing dialogue indicators (quotation marks)
(details)
13.77%
Name drop frequency
(details)
100.00%
Narrator intent-glossing
(details)
100.00%
"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)
100.00%
Em-dash & semicolon overuse
(details)
99.64%
Purple prose (modifier overload)
(details)
100.00%
Repeated phrase echo
(details)
100.00%
Sentence length variance
(details)
51.44%
Sentence opener variety
(details)
25.06%
Adverb-first sentence starts
(details)
100.00%
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)
100.00%
Useless dialogue additions
(details)
100.00%
Dialogue tag variety (said vs. fancy)
(details)
84.4388%
Overall
Model input
System
You are an expert fiction writer. Always keep the following rules in mind: - Write in past tense and use General English spelling, grammar, and colloquialisms/slang. - Write in active voice - Always follow the "show, don't tell" principle. - Avoid adverbs and cliches and overused/commonly used phrases. Aim for fresh and original descriptions. - Convey events and story through dialogue. - Mix short, punchy sentences with long, descriptive ones. Drop fill words to add variety. - Skip "he/she said said" dialogue tags and convey people's actions or face expressions through their speech - Avoid mushy dialog and descriptions, have dialogue always continue the action, never stall or add unnecessary fluff. Vary the descriptions to not repeat yourself. - Put dialogue on its own paragraph to separate scene and action. - Reduce indicators of uncertainty like "trying" or "maybe" When writing text: - NEVER conclude the scene on your own, follow the beat instructions very closely. - NEVER end with foreshadowing. - NEVER write further than what I prompt you with. - AVOID imagining possible endings, NEVER deviate from the instructions. - STOP EARLY if the continuation contains what was required in the instructions. You do not need to fill out the full amount of words possible.
User/Human
Take into account the following glossary of characters/locations/items/lore... when writing your response: <codex> <character id="4416" name="Detective Harlow Quinn" aliases="Quinn, Detective Quinn, Harlow" pronouns="she/her" species="Human" storyRole="Antagonist"> <eyeColor>brown</eyeColor> <hair>closely cropped salt-and-pepper</hair> <height>5'9"</height> <age>41</age> <jawline>sharp jaw</jawline> <watch>worn leather watch on her left wrist</watch> <bearing>military precision</bearing> <description>A Metropolitan Police detective with 18 years of decorated service who suspects the clique is involved in criminal activity.</description> <backstory>She lost her partner, DS Morris, during a case three years ago under unexplained circumstances that had supernatural origins she doesn't yet understand.</backstory> </character> <character id="4414" name="Eva Kowalski" aliases="Eva, Evie" pronouns="she/her" species="Human" storyRole="Best Friend"> <eyeColor>green</eyeColor> <hair>curly red</hair> <height>5'4"</height> <age>26</age> <glasses>round glasses</glasses> <satchel>worn leather satchel full of books</satchel> <freckles>freckled complexion</freckles> <nervousHabit>tucking hair behind her left ear</nervousHabit> <description>Aurora's childhood friend and an occult researcher.</description> <backstory>Moved to London two years before Aurora and works as a research assistant at the British Museum's restricted archives. She holds a master's degree in Ancient History from Oxford.</backstory> </character> <location id="856" name="The Veil Market" aliases="Veil Market, the Market, underground market" realm="Earth"> <currentLocation>abandoned Tube station beneath Camden</currentLocation> <entryRequirement>bone token</entryRequirement> <schedule>moves locations every full moon</schedule> <description>A hidden supernatural black market that sells enchanted goods, banned alchemical substances, and information.</description> </location> <item id="2004" name="Veil Compass" aliases="the Compass, shadow compass" type="Tool" origin="The Veil Market"> <casingMaterial>small brass compass</casingMaterial> <faceMarkings>face etched with protective sigils</faceMarkings> <needle>points toward the nearest supernatural rift or portal</needle> <patina>casing has a patina of verdigris</patina> <creator>crafted by a Shade artisan</creator> <description>A compass attuned to supernatural energy.</description> </item> </codex> Continue the story using the following instructions: <instructions> Write a fully fleshed out scene of at least 1000 words in the mystery genre. A detective arrives at a crime scene in an unusual location. Something is wrong — the evidence doesn't add up. A colleague is present, offering a different interpretation. Through careful observation and deduction, the detective begins to see what others have missed. 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 stairwell dropped beneath Camden
in a wet,
echoing
throat of concrete and rust.
Detective Harlow Quinn eased down
the last step and stopped where the air changed. Up top, buses groaned and late-night traffic hissed through rain. Down here, the station breathed cold and old iron, the kind of cold that clung to the back of the neck and refused to leave.
A line of portable lamps
threw pale bars across the platform. Half the tiles had fallen away.
The sign above the tunnel
mouth still hung crooked, one letter missing so the station name read like a bad joke.
Someone had strung tape across
the far end, though it looked ornamental against the dark. Uniforms clustered near the stairs, their faces washed flat by the lights.
Eva Kowalski stood beside a
folded tarp and a canvas evidence tent, one hand hooked into the strap of her worn leather satchel.
She had her round glasses
on and her curly red hair tucked behind her left ear, then slipping loose again as her fingers returned to it.
She looked small in the
station’s stale mouth, but her eyes tracked everything.
Books and old paper often
did that to a person. “You took your time,” Eva called.
Quinn’s gaze swept the platform
before it landed on her. “You dragged me under Camden at two in the morning and called it urgent. That usually meant blood.” Eva’s mouth twitched. “You’ve never been a fan of surprises.”
Quinn brushed past a constable
and ducked under the tape.
Her worn leather watch tapped
once against her wrist as she checked the scene.
A dead man lay near
the platform edge, supine, one arm bent in a way that suggested the fall had snapped it. He wore a black coat, expensive shoes, no overcoat despite the cold.
His face held that waxen
slackness that came after life left too
quickly
.
A crowd-control officer stood by
the stairs with a notebook clenched in both hands.
Another uniform covered one nostril
with a sleeve and stared at the body like it might get up and accuse him. Quinn crouched. “What have we got?” “Male, mid-thirties, no wallet, no phone on the body,”
the officer blurted
. “No obvious trauma beyond the fall. He came down the steps wrong, hit the platform, and broke his neck.” “Wrong?” Quinn lifted her eyes. “That’s your forensic term?” The officer flushed and looked away. Eva stepped closer to the body but kept her shoes clear of the pooled water around him. “He was found like this?” “A trench run on the far side, one witness heard a shout and came back to find him,” the officer said. “Station was being used for the market tonight. Then everyone scattered when they saw police moving in aboveground.” Quinn looked across the platform. Crates sat in the shadows under tarps. A broken ticket barrier leaned against a wall, and behind it, a scattering of grit marked a path toward the service door. Not a lot of blood.
Too little for a man
who had dropped from standing height and snapped his neck on stone.
She touched the dead man’s
sleeve with two fingers. The wool felt damp, but not from rain. Something else had soaked it from the inside and dried in patches. Her
eyes narrowed
. “No mud on his cuffs,” she said. The officer blinked. “What?” “Stairs. Wet night. He came down from street level, and you’re telling me he pitched forward on the platform. His sleeves should have picked up grime. His knees too.”
She drew her hand back
and glanced at his shoes. “But the leather’s clean. Same on the soles.” Eva crouched beside her. “His coat’s dusted, not stained. He didn’t tumble. He was placed.” The officer gave a short, nervous laugh. “Placed? Into a station full of people?” Quinn’s gaze moved to the man’s neck. The collar hid most of it, but a purple crescent broke beneath his jawline, too neat for a fall.
She hooked a finger into
the coat and turned the collar wider. Bruising ringed the throat in a hard band. “Strangled,” she murmured. “Then dropped.” The officer frowned. “The pathologist hasn’t—” “I don’t need a pathologist to see a hand around a neck.” Quinn stood and looked toward the tunnel. “Where’s the rest of him?” Eva straightened too, and her satchel thumped against her hip. “You mean the missing blood?” Quinn turned. Eva faced the body with her brows knit tight. “There isn’t enough to match the neck injury. Not for a full strangulation, not if the pressure lasted long enough to kill. The floor should have taken a lot more.” Quinn’s eyes travelled the platform edge again, then the tiles, then the drain grating along the wall. “Exactly.” The officer swallowed. “We thought maybe the body was moved after death.” “Moved where?” Quinn snapped. “The entire station’s underground. If someone dragged him through the market, he’d have left a trail. You’d have seen fibres, blood, shoe marks, broken tarps. Where are they?” Eva reached into her satchel and drew out a small notebook with cracked black covers. “There are prints, but not on the body. On the barrier.” Quinn followed her glance to the barrier near the service door. A smudged ring marked one metal rail, a handprint almost rubbed away.
She crossed to it and
knelt. The print sat high, thumb pressed awkwardly inward, as if the hand had gripped while someone leaned back hard. “Left hand,” she said. Eva looked up from her notes. “You can tell?” “The thumb’s on the inside edge. The mark’s deep on the heel and light on the fingers. Whoever made it clutched the rail to steady themselves.” Quinn tapped the smear. “But the dead man didn’t reach this far. He fell at the platform edge.” The officer shifted from one foot to the other. “Maybe he ran.” Quinn didn’t answer.
She looked down at the
platform edge where the paint had chipped away to bare concrete. A drag mark streaked from the body toward the edge, too broad for a shoe and too shallow for a heel.
She crouched again and ran
two fingers through the dust. Ash. Not soot. Fine grey ash with a faint silver
glint
under the lamp. Eva saw it too. “That’s not from the station.” “No.” Quinn brushed it between her fingers. “That came from something burned hot and fast.” The officer’s face tightened. “A cigarette?” Quinn rose
slowly
. “You’ve got a dead man with bruises around his throat, ash on the platform, no blood trail, no sign he fell, and a missing wallet. You want to call that a cigarette?” A
pulse
throbbed
in the officer’s jaw. “Then tell me what you think it was.” Quinn walked to the platform edge and peered into the black gap beside the tracks.
Her torch beam caught a
strip of wall, damp and silvered with mineral streaks, then a smear on the sleepers.
She followed it to a
patch of scorched tile tucked under the lip of the platform. “Whoever killed him didn’t do it here,” she said. “They did enough to make it look like a fall, then shifted the body to the edge.” The officer crossed his arms. “That still doesn’t explain the blood.” “It does if he bled somewhere else.” Quinn turned back toward the service door. “A room. A back passage. Somewhere close enough to carry him and clean up fast.” Eva’s eyes moved to the evidence tent, then to the cluster of sealed bags on a table. “There was a stall back there selling alchemical reagents. The stall’s gone now, but the air smells wrong.” Quinn’s head tilted. “Wrong how?” “Copper. Bitter herbs. And something burned beneath it.” Quinn walked to the table. A paper evidence tag lay beside a broken glass ampoule, its neck snapped clean.
She picked it up with
a gloved hand and held it toward the light. Residue lined the inside in a dark green smear. “Enchanted tincture,” Eva said. Quinn looked at her. “You know that for certain?” Eva nodded once and adjusted her glasses. “The colour means copper salts. The smell under it suggests a binding agent. I’ve seen similar compounds in restricted archive notes from the forties. They used them to seal things. Doors. Rooms. Sometimes mouths.” Quinn set the ampoule down. “Then this wasn’t a mugging.” The officer let out a sharp breath through his nose. “You’re both talking like this place belongs in a museum display. It’s just a station under Camden.” Eva’s gaze cut to him. “Under Camden, yes. And beneath that, a market that shifts with the moon and sells things your paperwork doesn’t know how to name.” He stared at her. Quinn watched the officer’s face change, the scepticism sliding into unease. Good. Unease kept people honest.
She took another step toward
the service door. The lock hung open, snapped, but the frame showed no fresh pry marks. The metal around the latch had a faint blackening, like it had
been kissed
by flame and cooled too fast. “Someone opened this with force,” she said. “Or magic,” Eva put in. Quinn looked over her shoulder. “You saying that, or your archive notes?” Eva tucked hair behind her ear again, then let her hand fall. “Both.” Quinn gave the door a long look, then the tunnel beyond. Cold drifted from the gap in little breathy slips.
She crouched and examined the
threshold. A line of pale dust crossed the floor, broken in two places by boot prints. One print showed the edge of a heel with a worn-down sole. The other sank deeper, dragged at the toe. She pointed. “Two people went through here. One steady, one fighting.” The officer leaned in. “How can you tell?” “Because the fighting one stepped off-balance and caught the frame.” Quinn tapped a scrape on the painted metal. “See that? Knuckles. He or she hit the door on the way in or out. The print depth changes too. The heavier person stayed upright. The other stumbled.” Eva peered into the dark corridor beyond the door. “That passage leads to the old signal room.” “Then that’s where the body was held.” Quinn’s
eyes narrowed
. “But not for long.” The officer looked from Quinn to Eva and back again,
as if searching for a more comfortable explanation
. “Then where’s the missing item? If this was a robbery, what did they take?” Quinn didn’t answer straight away.
She reached into the service
door’s shadow and picked something from the floor. A small object flashed brass under the lamp before she rolled it in her palm. Eva leaned closer. “A compass.” Quinn turned it over. The casing had a green patina, and the face carried protective sigils scratched so fine they almost disappeared into the metal. The needle inside
quivered
once, then settled, pointing
not north but into the tunnel wall
. “The needle’s wrong,” the officer muttered. “It wasn’t built for north.” Eva’s voice had gone quiet. “That’s a Veil compass.” Quinn raised one brow. “You know that from the archives too?” “No.” Eva watched the needle tremble against the glass. “I know it because it points at things that shouldn’t sit still. Rifts. Openings. Places where the air thins.” Quinn held the compass out and the needle jerked harder, angling toward the service corridor. “Nearest supernatural rift or portal,”
she said, tasting the words
like grit. “So someone brought this here, and someone else wanted it gone.” The officer took a step back. “You can’t be serious.” Quinn met his eye. “You called this a fall. It was a theft with a body attached.” Eva opened her notebook and flipped a page. “If the compass pointed there, the old signal room might not have been the target. It might have been the access point.” Quinn looked at the door, then at the ash on her glove, then at the dead man on the platform. The bruises on his throat, the clean shoes, the missing blood. The empty handprint on the barrier. The burned edge on the latch. The whole scene had
been dressed
to fool a hurried eye. She slipped the compass into her coat pocket and started toward the corridor. “Hold up,” the officer called. Quinn stopped without turning. He swallowed. “There’s something else. When we found him, his mouth was stuffed with paper.” Quinn turned back
slowly
. “Paper.” Eva’s fingers stilled at the edge of her notebook. “Yeah.” The officer rubbed a hand over his mouth. “Looks like a scrap from a receipt. Or a note. Forensics bagged it already.” Quinn glanced at the body, then at the service door, then at the platform edge where the ash still
shimmered
under the lights. Her eyes settled on the dead man’s
clenched fist
. “Open his hand,” she said. “Now.”
created_at
"2026-03-18T11:10:09.203Z"
3/18/2026, 11:10:09 AM
model
"openai/gpt-5.4-mini-20260317"
app_id
182717
external_user
(null)
streamed
true
cancelled
false
latency
1582
moderation_latency
(null)
generation_time
14946
tokens_prompt
1149
tokens_completion
3359
native_tokens_prompt
1009
native_tokens_completion
2937
native_tokens_completion_images
0
native_tokens_reasoning
166
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
"completed"
usage
0.01397325
router
(null)
provider_responses
0
endpoint_id
"9ee065b2-3d1c-43bc-bdd7-28af3b148282"
id
"resp_0a3b5712f5df0ee30169ba8811488c8193afde8f449920589b"
is_byok
false
latency
195
model_permaslug
"openai/gpt-5.4-mini-20260317"
provider_name
"OpenAI"
status
200
user_agent
"langchainjs-openai/1.0.0 ((node/v24.14.0; linux; x64))"
http_referer
(null)
api_type
"completions"
id
"gen-1773832209-5CCADIcLHcZTaRwg6a5H"
upstream_id
"resp_0a3b5712f5df0ee30169ba8811488c8193afde8f449920589b"
total_cost
0.01397325
cache_discount
(null)
upstream_inference_cost
0
provider_name
"OpenAI"
Evaluation details
Result
Evaluator
Details
Meta Data
100.00%
Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags
26
adverbTagCount
1
adverbTags
0
"Quinn turned back [back]"
dialogueSentences
85
tagDensity
0.306
leniency
0.612
rawRatio
0.038
effectiveRatio
0.024
92.97%
AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount
2135
totalAiIsmAdverbs
3
found
0
adverb
"quickly"
count
1
1
adverb
"slowly"
count
2
highlights
0
"quickly"
1
"slowly"
100.00%
AI-ism character names
Target: 0 AI-default names (17 tracked, −20% each)
codexExemptions
(empty)
found
(empty)
100.00%
AI-ism location names
Target: 0 AI-default location names (33 tracked, −20% each)
codexExemptions
(empty)
found
(empty)
83.61%
AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount
2135
totalAiIsms
7
found
0
word
"echoing"
count
1
1
word
"glint"
count
1
2
word
"pulse"
count
1
3
word
"throbbed"
count
1
4
word
"comfortable"
count
1
5
word
"quivered"
count
1
6
word
"shimmered"
count
1
highlights
0
"echoing"
1
"glint"
2
"pulse"
3
"throbbed"
4
"comfortable"
5
"quivered"
6
"shimmered"
66.67%
Cliché density
Target: ≤1 cliche(s) per 800-word window
totalCliches
3
maxInWindow
2
found
0
label
"eyes widened/narrowed"
count
2
1
label
"clenched jaw/fists"
count
1
highlights
0
"eyes narrowed"
1
"clenched fist"
100.00%
Emotion telling (show vs. tell)
Target: ≤3% sentences with emotion telling
emotionTells
0
narrationSentences
149
matches
(empty)
100.00%
Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount
1
hedgeCount
1
narrationSentences
149
filterMatches
0
"watch"
hedgeMatches
0
"started to"
100.00%
Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences
208
gibberishSentences
0
adjustedGibberishSentences
0
longSentenceCount
0
runOnParagraphCount
0
giantParagraphCount
0
wordSaladCount
0
repetitionLoopCount
0
controlTokenCount
0
maxSentenceWordsSeen
39
ratio
0
matches
(empty)
100.00%
Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans
0
markdownWords
0
totalWords
2135
ratio
0
matches
(empty)
100.00%
Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions
23
unquotedAttributions
0
matches
(empty)
13.77%
Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions
63
wordCount
1358
uniqueNames
5
maxNameDensity
2.72
worstName
"Quinn"
maxWindowNameDensity
4.5
worstWindowName
"Quinn"
discoveredNames
Camden
1
Harlow
1
Quinn
37
Kowalski
1
Eva
23
persons
0
"Harlow"
1
"Quinn"
2
"Kowalski"
3
"Eva"
places
(empty)
globalScore
0.138
windowScore
0.167
100.00%
Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences
95
glossingSentenceCount
1
matches
0
"as if searching for a more comfortable explanation"
100.00%
"Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches
1
per1kWords
0.468
wordCount
2135
matches
0
"not north but into the tunnel wall"
100.00%
Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount
1
totalSentences
208
matches
0
"held that waxen"
100.00%
Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs
95
mean
22.47
std
17.68
cv
0.787
sampleLengths
0
63
1
65
2
72
3
6
4
28
5
10
6
71
7
35
8
6
9
31
10
9
11
6
12
22
13
39
14
56
15
32
16
7
17
4
18
47
19
15
20
14
21
46
22
5
23
6
24
24
25
15
26
2
27
39
28
18
29
12
30
32
31
26
32
48
33
4
34
9
35
44
36
12
37
50
38
1
39
13
40
9
41
15
42
6
43
35
44
15
45
51
46
26
47
11
48
29
49
35
100.00%
Passive voice overuse
Target: ≤2% passive sentences
passiveCount
2
totalSentences
149
matches
0
"been kissed"
1
"been dressed"
100.00%
Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount
0
totalVerbs
227
matches
(empty)
100.00%
Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount
0
semicolonCount
0
flaggedSentences
0
totalSentences
208
ratio
0
matches
(empty)
99.64%
Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount
1361
adjectiveStacks
0
stackExamples
(empty)
adverbCount
55
adverbRatio
0.04041146216017634
lyAdverbCount
5
lyAdverbRatio
0.0036737692872887582
100.00%
Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences
208
echoCount
0
echoWords
(empty)
100.00%
Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences
208
mean
10.26
std
7.12
cv
0.694
sampleLengths
0
14
1
14
2
10
3
25
4
11
5
6
6
21
7
15
8
12
9
23
10
26
11
13
12
10
13
6
14
10
15
18
16
3
17
7
18
10
19
14
20
22
21
12
22
13
23
14
24
21
25
2
26
4
27
12
28
19
29
5
30
4
31
6
32
17
33
5
34
21
35
18
36
5
37
7
38
22
39
5
40
17
41
9
42
8
43
12
44
3
45
7
46
3
47
1
48
39
49
8
51.44%
Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats
8
diversityRatio
0.3317307692307692
totalSentences
208
uniqueOpeners
69
25.06%
Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount
1
totalSentences
133
matches
0
"Too little for a man"
ratio
0.008
100.00%
Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount
22
totalSentences
133
matches
0
"She had her round glasses"
1
"She looked small in the"
2
"Her worn leather watch tapped"
3
"He wore a black coat,"
4
"His face held that waxen"
5
"She touched the dead man’s"
6
"Her eyes narrowed."
7
"She drew her hand back"
8
"She hooked a finger into"
9
"She crossed to it and"
10
"She looked down at the"
11
"She crouched again and ran"
12
"Her torch beam caught a"
13
"She followed it to a"
14
"She picked it up with"
15
"He stared at her."
16
"She took another step toward"
17
"She crouched and examined the"
18
"She reached into the service"
19
"she said, tasting the words"
ratio
0.165
0.00%
Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount
123
totalSentences
133
matches
0
"The stairwell dropped beneath Camden"
1
"Detective Harlow Quinn eased down"
2
"A line of portable lamps"
3
"The sign above the tunnel"
4
"Someone had strung tape across"
5
"Uniforms clustered near the stairs,"
6
"Eva Kowalski stood beside a"
7
"She had her round glasses"
8
"She looked small in the"
9
"Books and old paper often"
10
"Quinn’s gaze swept the platform"
11
"Eva’s mouth twitched."
12
"Quinn brushed past a constable"
13
"Her worn leather watch tapped"
14
"A dead man lay near"
15
"He wore a black coat,"
16
"His face held that waxen"
17
"A crowd-control officer stood by"
18
"Another uniform covered one nostril"
19
"the officer blurted"
ratio
0.925
0.00%
Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount
0
totalSentences
133
matches
(empty)
ratio
0
100.00%
Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences
61
technicalSentenceCount
2
matches
0
"A dead man lay near the platform edge, supine, one arm bent in a way that suggested the fall had snapped it."
1
"The officer looked from Quinn to Eva and back again, as if searching for a more comfortable explanation."
100.00%
Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags
26
uselessAdditionCount
0
matches
(empty)
100.00%
Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags
14
fancyCount
4
fancyTags
0
"the officer blurted (blurt)"
1
"she murmured (murmur)"
2
"Quinn snapped (snap)"
3
"the officer muttered (mutter)"
dialogueSentences
85
tagDensity
0.165
leniency
0.329
rawRatio
0.286
effectiveRatio
0.094
84.4388%