Run: 2026-03-11-01KKFG454VPY4H5JWC1CTM5GWP

Run Details

Duration:
1m 10s
Cost:
$0.000993
Provider:
Together

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="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="4417" name="Tomás Herrera" aliases="Tommy, Tomás, Herrera" pronouns="he/him" species="Human" storyRole="Support"> <eyeColor>warm brown</eyeColor> <hair>short curly dark brown</hair> <height>5'10"</height> <age>29</age> <skinTone>olive skin</skinTone> <scar>scar running along his left forearm from a knife attack</scar> <medallion>Saint Christopher medallion around his neck</medallion> <birthplace>Seville, Spain</birthplace> <description>A former paramedic who provides off-the-books medical care for the clique.</description> <backstory>Born in Seville, Spain. He moved to London to work for the NHS but lost his license after administering unauthorized treatments to supernatural patients.</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> <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> </codex> Write a fully fleshed out scene of at least 1000 words in the thriller genre. A detective is pursuing a suspect through rain-soaked city streets at night. The chase takes them from the street level down into an underground market. The detective must decide whether to follow the suspect into unfamiliar and potentially dangerous territory. 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

AI
The London rain was always aggressive, a relentless curtain that blurred the neon signs with static ruins of color. Harlow Quinn ran through the puddles of Camden High Street, water soaking through her boots to drip down the hem of her trench coat. Her breath came in sharp, wet pants, each inhale tasting of burnt rubber and the city exhale. She kept her eyes on the figure ahead, a shadow dissolving from the gloom of the hallway lights. It wasn't the suspect anymore; it was a rumor written on the back of a wet receipt and thrown into the gutter. Harlow's hands were gripping the collar of her jacket until her knuckles were white. She hadn't felt this adrenaline in over two years. That was when the power had died. The time when she had followed them down the stairs. The ghost of her partner, Thomas Morris, the scar on his arm, the body in the morgue that looked nothing like the man she loved. She knew she had to confront the darkness if she was to survive her last three years. She tugged at the strap of her belt. The leather weight of the watch on her left wrist pulsed against her skin. The second hand ticked over with a mechanical snap, a sound that pierced the thundering rain. Four o'clock. The graveyard tilt of the world. Her boot hit water that reflected the green neon of the streetlamp in front of her. She stepped over it. The water was deeper than it looked, cold and dirty. The suspect was absorbed by the darkness of the abandoned Tube station beneath Camden. The walls looked different. They were not the cracked concrete of the street. They were glazed tiles, black and white, reflecting the flickering crown litzich of the city. She moved to the edge of the station entrance, the air thick with the smell of ozone. The station was empty. She could tell it was empty. She felt something move inside her, a memory. The memory of the body. The memory of the door. She knew she was on the edge. The suspect turned and looked at her. His left hand twitched. The scar along the forearm was visible. He didn't say anything. He just nodded. She knew what he wanted. She knew what he needed. She knew the truth was not here. The truth was outside. She could leave. She could close the door. She could say nothing. But she didn't. She looked at the station. It was the entrance. There was no gate. There was no sign. She stepped down. The tiles were cold. She was standing at the edge of the market. She saw a man on the floor. He was bleeding. He was crying. She saw the token. He placed it on the table. It was a bone. The bone token was a rule for the clique. She knew she should have stopped. She should have gone back to the car. She should have called in support. But she didn't. She stepped into the market. The door was open. The light was on. She stepped inside. The dark swallowed her. She knew she had no choice. She felt the rain on her skin. The smell of blood. The pain in her heart. She steadied herself. She looked at the man. He was the only person left. The rest were gone. She had to know the answer. She had to find the token. She had to make the choice. She took the token. She held it tight. She stepped forward. The door closed behind her. The light was on. She was alone in the market. The air was cold. The light was green. The walls were covered in old maps. She moved through them. She felt the weight of her badge. She felt the weight of her grief. She wanted to stop. She wanted to run. But she didn't. She didn't know what it would mean if she stopped. She was a detective. She had one word for this. She knew. She felt it. She walked further. The light was dim. The floor was wet. She saw a shadow. It looked like a man. It looked like a ghost. She moved closer. She saw the token. It was a bone. She broke the token. It crumbled into dust. She dropped it. The dust fell. She stood there. She looked at the wall. She saw the maps. She knew the answer. She was a detective. She knew the world. She knew the truth. She opened the door. She stepped out. The rain was still falling. She was alone again.
created_at"2026-03-11T22:26:21.479Z" 3/11/2026, 10:26:21 PM
model"qwen/qwen3.5-9b-20260310"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency738
moderation_latency(null)
generation_time70026
tokens_prompt914
tokens_completion6603
native_tokens_prompt870
native_tokens_completion6038
native_tokens_completion_images(null)
native_tokens_reasoning5541
native_tokens_cached0
num_media_prompt(null)
num_input_audio_prompt(null)
num_media_completion0
num_search_results(null)
origin"https://ncbench.com/"
is_byokfalse
finish_reason"stop"
native_finish_reason"stop"
usage0.0009927
router(null)
provider_responses
0
endpoint_id"00d506d9-a5e9-4382-a2b9-d54732365594"
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latency738
model_permaslug"qwen/qwen3.5-9b-20260310"
provider_name"Together"
status200
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api_type"completions"
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provider_name"Together"

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags0
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount772
totalAiIsmAdverbs0
found(empty)
highlights(empty)
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)
61.14% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount772
totalAiIsms6
found
0
word"gloom"
count1
1
word"weight"
count3
2
word"pulsed"
count1
3
word"mechanical"
count1
highlights
0"gloom"
1"weight"
2"pulsed"
3"mechanical"
100.00% Cliché density
Target: ≤1 cliche(s) per 800-word window
totalCliches0
maxInWindow0
found(empty)
highlights(empty)
100.00% Emotion telling (show vs. tell)
Target: ≤3% sentences with emotion telling
emotionTells0
narrationSentences121
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount0
hedgeCount0
narrationSentences121
filterMatches(empty)
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences121
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
maxSentenceWordsSeen25
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords772
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions1
unquotedAttributions0
matches(empty)
100.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions9
wordCount772
uniqueNames8
maxNameDensity0.26
worstName"Camden"
maxWindowNameDensity0.5
worstWindowName"Camden"
discoveredNames
London1
Quinn1
Camden2
High1
Street1
Thomas1
Morris1
Tube1
persons
0"Quinn"
1"Thomas"
2"Morris"
places
0"London"
1"Camden"
2"High"
3"Street"
globalScore1
windowScore1
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences46
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount772
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences121
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs29
mean26.62
std23.95
cv0.9
sampleLengths
0100
182
246
372
452
558
620
716
813
923
1036
1113
1216
1318
1418
158
1612
176
1833
198
2013
2115
2225
2319
246
2512
2616
2712
284
93.66% Passive voice overuse
Target: ≤2% passive sentences
passiveCount4
totalSentences121
matches
0"was absorbed"
1"were glazed"
2"were gone"
3"were covered"
0.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount5
totalVerbs147
matches
0"were gripping"
1"was standing"
2"was bleeding"
3"was crying"
4"was still falling"
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount1
flaggedSentences1
totalSentences121
ratio0.008
matches
0"It wasn't the suspect anymore; it was a rumor written on the back of a wet receipt and thrown into the gutter."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount772
adjectiveStacks0
stackExamples(empty)
adverbCount9
adverbRatio0.011658031088082901
lyAdverbCount1
lyAdverbRatio0.0012953367875647669
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences121
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences121
mean6.38
std4.59
cv0.72
sampleLengths
019
124
217
318
422
514
69
77
810
925
1017
118
1214
1316
142
156
1616
174
1810
1914
204
219
2215
2317
244
256
268
275
285
297
307
314
327
334
343
355
365
377
384
393
405
414
423
435
444
454
464
473
484
499
25.00% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats50
diversityRatio0.09917355371900827
totalSentences121
uniqueOpeners12
0.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount0
totalSentences119
matches(empty)
ratio0
0.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount79
totalSentences119
matches
0"Her breath came in sharp,"
1"She kept her eyes on"
2"It wasn't the suspect anymore;"
3"She hadn't felt this adrenaline"
4"She knew she had to"
5"She tugged at the strap"
6"Her boot hit water that"
7"She stepped over it."
8"They were not the cracked"
9"They were glazed tiles, black"
10"She moved to the edge"
11"She could tell it was"
12"She felt something move inside"
13"She knew she was on"
14"His left hand twitched."
15"He didn't say anything."
16"He just nodded."
17"She knew what he wanted."
18"She knew what he needed."
19"She knew the truth was"
ratio0.664
0.00% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount114
totalSentences119
matches
0"The London rain was always"
1"Harlow Quinn ran through the"
2"Her breath came in sharp,"
3"She kept her eyes on"
4"It wasn't the suspect anymore;"
5"Harlow's hands were gripping the"
6"She hadn't felt this adrenaline"
7"That was when the power"
8"The time when she had"
9"The ghost of her partner,"
10"She knew she had to"
11"She tugged at the strap"
12"The leather weight of the"
13"The second hand ticked over"
14"The graveyard tilt of the"
15"Her boot hit water that"
16"She stepped over it."
17"The water was deeper than"
18"The suspect was absorbed by"
19"The walls looked different."
ratio0.958
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences119
matches(empty)
ratio0
0.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences17
technicalSentenceCount4
matches
0"The London rain was always aggressive, a relentless curtain that blurred the neon signs with static ruins of color."
1"The ghost of her partner, Thomas Morris, the scar on his arm, the body in the morgue that looked nothing like the man she loved."
2"The second hand ticked over with a mechanical snap, a sound that pierced the thundering rain."
3"Her boot hit water that reflected the green neon of the streetlamp in front of her."
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags0
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags0
75.9935%