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Run: 2026-09-03-01M1KC3HBC2ECY14E2VY9NRFXE
Run Details
Model:
DeepSeek V4 Flash 0731 (Reasoning, High)
Test:
Bad Writing Habits
Scenario:
Literary fiction: old friends reunite
Duration:
4m 22s
Cost:
$0.002059
Provider:
DeepInfra
Evaluation summary
Score
Evaluator
Details Link
100.00%
Adverbs in dialogue tags
(details)
91.01%
AI-ism adverb frequency
(details)
100.00%
AI-ism character names
(details)
100.00%
AI-ism location names
(details)
88.01%
AI-ism word frequency
(details)
100.00%
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)
100.00%
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)
99.05%
Passive voice overuse
(details)
91.89%
Past progressive (was/were + -ing) overuse
(details)
100.00%
Em-dash & semicolon overuse
(details)
100.00%
Purple prose (modifier overload)
(details)
100.00%
Repeated phrase echo
(details)
100.00%
Sentence length variance
(details)
51.95%
Sentence opener variety
(details)
37.04%
Adverb-first sentence starts
(details)
51.11%
Pronoun-first sentence starts
(details)
60.00%
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)
89.0021%
Overall
Model input
System
You are an expert novelist with a gift for vivid, immersive prose. You write in tight third-person limited point of view with a strong narrative voice. Your prose is clean, precise, and engaging — you favor strong verbs, concrete details, and natural-sounding dialogue. You will be given a story bible (codex) containing canonical details about characters, locations, items, and lore. Use these details to ground your writing in the established world. Stay consistent with the codex. Write only the prose of the scene. Do not include titles, chapter headings, markdown formatting, or any commentary before or after the scene.
User/Human
<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> 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.
Model response
Messages
Meta
AI
The green neon bled across
the pavement, THE RAVEN'S NEST reflected in the wet black of the street.
Rain had been falling since
six, a steady London drizzle that soaked through the shoulders of her jacket and left the delivery bag heavier than it had any right to be.
Aurora stood under the awning
and watched the letters shimmer in the puddles like something submerged.
She had lived above this
bar for three weeks.
She knew its hours by
the sounds that came through her floorboards: the first stools scraping at four, the slow tide of voices rising past nine, the last drunk
being eased
out at closing.
She had never once gone
down.
Tonight the flat had pressed
in on her. The radiator knocked.
The ceiling sloped like it
was trying
to bow.
She had sat on the
edge of the bed with her phone in her hand, the screen dark, and thought: if I stay here one more night, I'll stop existing. So she had gone down.
The door opened on a
room of amber light. Old maps covered the walls, their edges curling, pinned like specimens. Black-and-white photographs hung between them, a bridge in Prague, a woman laughing on a street corner, a man in a raincoat looking back over his shoulder.
The jukebox in the corner
played something low and French.
The man behind the bar
looked up from a glass he
was polishing
. He moved with a negotiation, a hitch in the left leg, a hand finding the counter to steady himself. Grey-streaked auburn hair, a beard trimmed close, a silver ring on his right hand catching the light. Fifty-eight, maybe. Carrying it well. Carrying it badly. "Closed?" she said. "Open."
He set the glass down
. "Quiet, but open. Can I get you something?"
She hadn't decided to stay
until she was already on the stool. "Whatever's cheap."
He poured two fingers of
whiskey and slid it across the bar. "On the house. Call it a welcome." "I'm not new," she said. "I live upstairs. Three weeks." "I know."
He leaned his forearms on
the wood. "I wondered when you'd come down." Aurora's spine stiffened.
She had built her weeks
around not being known, head down, hood up, routes mapped so she never made eye contact twice with the same person.
Being seen
felt like being caught
. "You've got your mother's eyes," the man said. "But you've got Brendan's chin. And that stubbornness he called a virtue and everyone else called a curse." The name hit her like a door slamming open.
She stared at him, the
silver ring, the maps, the careful grey at his temples. A memory surfaced from deep water: her father's study in Cardiff, the smell of pipe smoke and old paper, a man with a deep laugh hoisting her onto his knee.
She had been eight, maybe
nine, and he had told her she had the face of a girl who'd argue with a brick wall and win. "Silas," she said. "That's right."
His eyes, hazel, she remembered
now, how had she forgotten hazel, studied her without pressure. "Last time I saw you, you were sixteen. Furious about something. Your father dragged you down to London for the weekend and you sulked the whole way." "I remember sulking. I don't remember you." "I'm hard to forget." A small smile. "You used to write me letters. Pages of them, in that terrible scrawl of yours, full of questions about the places I'd been. Prague. Istanbul. You wanted to know if the bridges were
really
that old, if the markets
really
smelled like spice and smoke." The whiskey sat untouched in front of her. Her throat had closed. "I sent you postcards,"
he went on
. "You sent back letters with drawings in the margins. Little birds. You were always drawing birds." "I'd forgotten," she said. And the truth of it hurt more than a lie would have. She had forgotten.
She had buried those years
so deep they had turned to sediment. "That's all right," Silas said. "I kept them."
She picked up the glass
and drank. The whiskey burned down and opened something in her chest, a room she had kept locked. "Your father wrote to me," he said. "When you got into university. Said you were going to be a lawyer. Said you'd argue with a brick wall and win." "That was the plan." "And now?"
She looked at her reflection
in the dark window behind the bottles. Straight black hair, bright blue eyes that looked, in this amber light, like borrowed things. The woman in the glass was a stranger wearing her face. "I deliver food," she said. "For a restaurant called Golden Empress. I carry bags and I don't talk to anyone and at the end of the day I come home to a flat that's not mine and I sleep."
She set the glass down
. "That's what happened to the plan." Silas didn't flinch. He just watched her, patient as a man who had spent a career reading people across tables exactly like this one. "I was going to tell you," he said quietly. "I knew. About the boy. Evan." The name was a cold stone dropped into the
warmth
. Aurora's hand went to her wrist, to the small crescent scar there, the one from childhood, from a bicycle accident, from before. She pressed her thumb into it. "I didn't need the details," Silas said. "I read the shape of it in your father's letters. He was worried. He didn't know how to reach you. Neither did I." A pause. "I should have tried harder." "It wasn't your job to save me." "No. But I was your friend." He said it simply, without
weight
, and somehow that made it heavier. "You were sixteen, and you wrote me letters, and I sent you postcards, and I thought there'd be time. I thought you'd come through it and I'd be here and we'd drink whiskey and you'd tell me about the world." He tapped the bar with one finger. "And then one day I looked up and the girl who drew birds in the margins was gone." The jukebox clicked over to something slower. A woman singing in French about love and loss, or maybe just about the rain. Aurora stared at her glass. "I stopped drawing birds," she said. "I know." "I stopped a lot of things. I let him—" She stopped. The words were there, heavy and sharp, but she couldn't put them down. "I let him make me small. That's the worst of it. Not the bruises. He was never—he was careful, he was so careful—he just made me small. And I let him." Silas said nothing. He didn't need to. The
silence
was a hand held out. "What about you?" she asked. "You said you'd be here. What happened to you?" He smiled, and the smile didn't reach his eyes. "Prague." "The photograph." "Good eye. That's the bridge. Charles Bridge, before the renovation." He gestured at the black-and-white image, the man in a raincoat looking back over his shoulder. "That's me. Younger. Stupider. Thought I was saving the world one secret at a time." "What happened?" "I got old. I got slow." He tapped his left leg. "Got a knee that sings when it rains. Retired. Came here. Made a nest." "A nest," she repeated. "A raven's nest. You know ravens? They mate for life. They remember faces. They collect shiny things and hide them away." He looked at the maps, the photographs. "I collect other people's secrets now. Same instinct. I just don't go looking for them anymore. They come to me." "Is that what this is? A place for secrets?" "This is a place for people who need to not be found." He reached under the bar and came up with a key on a plain brass ring. He set it between them. "There's a room in the back. Behind the bookshelf. No windows, no name, no records. I use it for meetings with people who can't afford to be seen." He pushed the key toward her. "If you ever need a place where no one can find you,
truly
no one, it's yours." She looked at the key. Small. Solid. Warm from the bar's heat. "I don't need to hide," she said. "Everyone needs to hide sometimes," Silas said. "Even the ones who think they don't. Especially those." The door opened behind her. Cold air swept in with the smell of rain, and a couple stumbled in laughing, shaking water from their coats. The spell broke. Aurora picked up the key. It was heavier than it looked. "Thank you," she said. Not for the key, exactly. For something she couldn't name. Silas lifted his glass. "Come down again. The bar's part of the deal." She stood. Slinging the delivery bag over her shoulder, she walked to the door, the key closed in her fist. The couple had taken a table in the corner; the woman
was laughing
, her head thrown back, unguarded in a way Aurora had forgotten people could be. "Goodnight, Rory," Silas said. She stopped. Nobody called her that anymore. Not since Cardiff. Not since before Evan, before the flat with the bowing ceiling, before she had learned to move through the world without leaving a mark. Rory had been the girl who drew birds in the margins, the girl who argued with brick walls. She turned.
The man behind the bar
had gone back to polishing a glass, the silver ring
glinting
, the maps and photographs watching over him like the ghosts of every place he had ever been. In the street, the green neon hummed overhead, bleeding into the puddles. She looked up at her window, the dark rectangle of the flat, the sloped ceiling that bowed like a held breath.
Then she looked down at
her hand, at the brass key catching the neon light. She didn't go upstairs. She went back inside.
created_at
"2026-09-03T10:12:50.17Z"
9/3/2026, 10:12:50 AM
model
"deepseek/deepseek-v4-flash-20260731"
app_id
182717
external_user
(null)
streamed
true
cancelled
false
latency
659
moderation_latency
(null)
generation_time
262259
tokens_prompt
846
tokens_completion
12012
native_tokens_prompt
895
native_tokens_completion
11043
native_tokens_completion_images
(null)
native_tokens_reasoning
8896
native_tokens_cached
0
num_media_prompt
(null)
num_input_audio_prompt
(null)
num_media_completion
0
num_search_results
(null)
num_fetches
(null)
web_search_engine
(null)
origin
"https://ncbench.com/"
is_byok
false
finish_reason
"stop"
native_finish_reason
"stop"
service_tier
(null)
usage
0.00205934
router
(null)
user_agent
"langchainjs-openai/1.0.0 ((node/v24.19.0; linux; x64))"
http_referer
(null)
request_id
"req-1788430370-spmkNKNn8oYWGonGpWlW"
session_id
(null)
preset_id
(null)
api_type
"completions"
id
"gen-1788430370-SV1axnYwJRb0S2xNzeQM"
upstream_id
"chatcmpl-RQRmPy3jXT3kc3YsCIll46FF"
provider_responses
0
endpoint_id
"c1980fff-0a72-4bce-8d62-a7d3fc582200"
id
"chatcmpl-RQRmPy3jXT3kc3YsCIll46FF"
is_byok
false
latency
138
model_permaslug
"deepseek/deepseek-v4-flash-20260731"
provider_name
"DeepInfra"
status
200
total_cost
0.00205934
cache_discount
(null)
upstream_inference_cost
0
provider_name
"DeepInfra"
response_cache_source_id
(null)
data_region
"global"
workspace_id
"97e315e5-d303-487d-83c1-83180e8a13d4"
Evaluation details
Result
Evaluator
Details
Meta Data
100.00%
Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags
30
adverbTagCount
1
adverbTags
0
"he said quietly [quietly]"
dialogueSentences
64
tagDensity
0.469
leniency
0.938
rawRatio
0.033
effectiveRatio
0.031
91.01%
AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount
1668
totalAiIsmAdverbs
3
found
0
adverb
"really"
count
2
1
adverb
"truly"
count
1
highlights
0
"really"
1
"truly"
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)
88.01%
AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount
1668
totalAiIsms
4
found
0
word
"warmth"
count
1
1
word
"weight"
count
1
2
word
"silence"
count
1
3
word
"glinting"
count
1
highlights
0
"warmth"
1
"weight"
2
"silence"
3
"glinting"
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
113
matches
(empty)
100.00%
Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount
0
hedgeCount
0
narrationSentences
113
filterMatches
(empty)
hedgeMatches
(empty)
100.00%
Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences
145
gibberishSentences
0
adjustedGibberishSentences
0
longSentenceCount
0
runOnParagraphCount
0
giantParagraphCount
0
wordSaladCount
0
repetitionLoopCount
0
controlTokenCount
0
repeatedSegmentCount
0
maxSentenceWordsSeen
47
ratio
0
matches
(empty)
100.00%
Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans
0
markdownWords
0
totalWords
1666
ratio
0
matches
(empty)
100.00%
Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions
26
unquotedAttributions
0
matches
(empty)
100.00%
Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions
20
wordCount
1053
uniqueNames
7
maxNameDensity
0.66
worstName
"Silas"
maxWindowNameDensity
1.5
worstWindowName
"Silas"
discoveredNames
London
1
Prague
1
French
2
Aurora
6
Cardiff
2
Silas
7
Evan
1
persons
0
"Aurora"
1
"Silas"
2
"Evan"
places
0
"London"
1
"Prague"
2
"French"
3
"Cardiff"
globalScore
1
windowScore
1
100.00%
Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences
59
glossingSentenceCount
1
matches
0
"felt like being caught"
100.00%
"Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches
0
per1kWords
0
wordCount
1666
matches
(empty)
100.00%
Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount
0
totalSentences
145
matches
(empty)
100.00%
Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs
65
mean
25.63
std
21.35
cv
0.833
sampleLengths
0
65
1
49
2
50
3
5
4
56
5
13
6
44
7
3
8
14
9
14
10
19
11
10
12
15
13
35
14
26
15
80
16
3
17
44
18
7
19
52
20
12
21
23
22
31
23
8
24
23
25
29
26
4
27
2
28
38
29
50
30
24
31
15
32
38
33
37
34
7
35
83
36
27
37
6
38
2
39
55
40
14
41
14
42
10
43
2
44
41
45
2
46
25
47
4
48
48
49
9
99.05%
Passive voice overuse
Target: ≤2% passive sentences
passiveCount
2
totalSentences
113
matches
0
"being eased"
1
"Being seen"
2
"being caught"
91.89%
Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount
3
totalVerbs
185
matches
0
"was trying"
1
"was polishing"
2
"was laughing"
100.00%
Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount
0
semicolonCount
1
flaggedSentences
1
totalSentences
145
ratio
0.007
matches
0
"The couple had taken a table in the corner; the woman was laughing, her head thrown back, unguarded in a way Aurora had forgotten people could be."
100.00%
Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount
1059
adjectiveStacks
0
stackExamples
(empty)
adverbCount
29
adverbRatio
0.027384324834749764
lyAdverbCount
5
lyAdverbRatio
0.004721435316336166
100.00%
Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences
145
echoCount
0
echoWords
(empty)
100.00%
Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences
145
mean
11.49
std
9.55
cv
0.831
sampleLengths
0
18
1
31
2
16
3
9
4
34
5
6
6
8
7
3
8
9
9
30
10
5
11
9
12
11
13
26
14
10
15
13
16
19
17
17
18
2
19
3
20
3
21
3
22
6
23
8
24
12
25
2
26
12
27
7
28
5
29
5
30
9
31
6
32
3
33
26
34
6
35
8
36
18
37
9
38
15
39
30
40
26
41
3
42
17
43
27
44
7
45
7
46
45
47
8
48
4
49
7
51.95%
Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats
18
diversityRatio
0.38620689655172413
totalSentences
145
uniqueOpeners
56
37.04%
Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount
1
totalSentences
90
matches
0
"Then she looked down at"
ratio
0.011
51.11%
Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount
38
totalSentences
90
matches
0
"She had lived above this"
1
"She knew its hours by"
2
"She had never once gone"
3
"She had sat on the"
4
"He moved with a negotiation,"
5
"He set the glass down"
6
"She hadn't decided to stay"
7
"He poured two fingers of"
8
"He leaned his forearms on"
9
"She had built her weeks"
10
"She stared at him, the"
11
"She had been eight, maybe"
12
"His eyes, hazel, she remembered"
13
"Her throat had closed."
14
"he went on"
15
"She had forgotten."
16
"She had buried those years"
17
"She picked up the glass"
18
"She looked at her reflection"
19
"She set the glass down"
ratio
0.422
60.00%
Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount
72
totalSentences
90
matches
0
"The green neon bled across"
1
"Rain had been falling since"
2
"Aurora stood under the awning"
3
"She had lived above this"
4
"She knew its hours by"
5
"She had never once gone"
6
"Tonight the flat had pressed"
7
"The radiator knocked."
8
"The ceiling sloped like it"
9
"She had sat on the"
10
"The door opened on a"
11
"The jukebox in the corner"
12
"The man behind the bar"
13
"He moved with a negotiation,"
14
"He set the glass down"
15
"She hadn't decided to stay"
16
"He poured two fingers of"
17
"He leaned his forearms on"
18
"Aurora's spine stiffened."
19
"She had built her weeks"
ratio
0.8
0.00%
Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount
0
totalSentences
90
matches
(empty)
ratio
0
100.00%
Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences
37
technicalSentenceCount
1
matches
0
"Rory had been the girl who drew birds in the margins, the girl who argued with brick walls."
100.00%
Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags
30
uselessAdditionCount
0
matches
(empty)
100.00%
Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags
18
fancyCount
1
fancyTags
0
"she repeated (repeat)"
dialogueSentences
64
tagDensity
0.281
leniency
0.563
rawRatio
0.056
effectiveRatio
0.031
89.0021%