Run: 2026-02-26-01KJBM1NPVEWS6DEVQNVHJSYF1

Run Details

Duration:
1m 29s
Cost:
$0.019947
Provider:
Alibaba

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="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> Continue the story using the following instructions: <instructions> 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. </instructions>

Model response

AI
Rain hammered the asphalt of Camden High Street, turning the road into a slick black mirror that reflected the neon signs of the city. Detective Harlow Quinn pushed her collar up against the biting wind. Water streamed down her closely cropped salt-and-pepper hair, matting it against her skull. She checked her wrist. The worn leather watch showed 2:14 AM. Eighteen years on the force hadn't prepared her for the cold bite of this specific night. Her lungs burned with every intake of air. The city smelled of wet wool and exhaust. A shadow darted into the alleyway ahead. Tomás Herrera. He moved like a man who knew the weight of a knife, his shoulders hunched against the downpour. Quinn didn't shout. She didn't need to. The sound of her boots splashing in the gutters announced her presence. She sprinted, her military bearing holding her stride even as fatigue set in. Her heart hammered against her ribs. Quinn rounded the corner of a shuttered shop. The neon sign of a nearby kebab house buzzed, casting a sickly pink light over the wet brickwork. She saw him pause near the mouth of a subway entrance. The metal grating was rusted, painted over with layers of peeling grey. The Veil Market. She knew the rumors. She knew the files marked 'Restricted'. She closed the distance. Her breath plumed in the air, white and fleeting. Tomás turned. The Saint Christopher medallion swung against his chest, catching the light. His olive skin gleamed with sweat and rain. The scar running along his left forearm stood out against the dark fabric of his jacket. He didn't run. He leaned against the concrete pillar, hands in his pockets. "You're fast for your age, Detective." Quinn stopped ten feet away. Her hand hovered near her holster. She kept her eyes locked on his chest. "Turn around, Tomás. Hands where I can see them." "You want to arrest me? For what? Healing a man the NHS turned away?" "For unauthorized practice. For lying to the coroner. For covering up deaths." Tomás shook his head. Water dripped from his curls. "You don't know what you're chasing." "I know the pattern. I know Morris." The name hung in the air, heavy and sharp. Tomás flinched. The medallion stilled against his sternum. "Morris found something he couldn't explain. You found something you can't control." Quinn took a step forward. The rain soaked her coat, weighing down the shoulders. "Open the gate." "There is no gate." Tomás gestured to the dark maw of the station. "There is only the threshold." "I'm crossing it." "Without a token, you're dead." Quinn pulled a small, jagged piece of bone from her pocket. She had taken it from the evidence locker three days ago. It pulsed with a faint, cold heat against her palm. She held it up. The bone glowed in the dim light, a sickly violet hue. "I have my own." Tomás looked at the bone, then back to her eyes. His expression hardened. "That belongs to the dead." "It belongs to the Metropolitan Police." "It belongs to the Market." Quinn stepped onto the metal grating. The iron groaned under her weight. She walked down the first few steps. The air grew stale, smelling of damp earth and ozone. The sound of the city faded, replaced by a low hum vibrating through the soles of her boots. "You think you're hunting me." Tomás pushed off the wall. He moved into the shadows of the stairwell. "You're hunting yourself." "I'm hunting the truth." "The truth eats people." Quinn reached the bottom of the stairs. The platform stretched out into darkness. Shapes moved in the periphery. Vendors? Shadows? She couldn't tell. The bone in her hand grew warmer. Tomás stood at the edge of the platform. He held a lantern. The flame inside burned blue. "One step further, and there is no going back." Quinn tightened her grip on the bone. She looked at the darkness ahead. She thought of Morris. She thought of the file that ended three years ago. "I don't care." She stepped off the concrete ledge. Her boot landed on the cobblestones of the underground station. The blue light flared.
created_at"2026-02-26T00:02:14.88Z" 2/26/2026, 12:02:14 AM
model"qwen/qwen3.5-27b-20260224"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency1332
moderation_latency(null)
generation_time88827
tokens_prompt1140
tokens_completion9004
native_tokens_prompt1066
native_tokens_completion8178
native_tokens_completion_images(null)
native_tokens_reasoning7231
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"
usage0.019947
router(null)
provider_responses
0
endpoint_id"f3f88554-0c22-4d57-973b-0dec948808e8"
id"chatcmpl-419106a8-49c4-9780-b958-b27fa81a454b"
is_byokfalse
latency1332
model_permaslug"qwen/qwen3.5-27b-20260224"
provider_name"Alibaba"
status200
api_type"completions"
id"gen-1772064134-cUcQGYSa70AkR2HGK20j"
upstream_id"chatcmpl-419106a8-49c4-9780-b958-b27fa81a454b"
total_cost0.019947
cache_discount(null)
upstream_inference_cost0
provider_name"Alibaba"

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags3
adverbTagCount0
adverbTags(empty)
dialogueSentences22
tagDensity0.136
leniency0.273
rawRatio0
effectiveRatio0
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount697
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)
64.13% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount697
totalAiIsms5
found
0
word"weight"
count2
1
word"fleeting"
count1
2
word"maw"
count1
3
word"pulsed"
count1
highlights
0"weight"
1"fleeting"
2"maw"
3"pulsed"
100.00% Cliché density
Target: ≤1 cliche(s) per 800-word window
totalCliches1
maxInWindow1
found
0
label"hung in the air"
count1
highlights
0"hung in the air"
100.00% Emotion telling (show vs. tell)
Target: ≤3% sentences with emotion telling
emotionTells0
narrationSentences73
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount0
narrationSentences73
filterMatches
0"watch"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences93
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
maxSentenceWordsSeen24
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords697
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions4
unquotedAttributions0
matches(empty)
66.67% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions27
wordCount562
uniqueNames12
maxNameDensity1.6
worstName"Quinn"
maxWindowNameDensity3
worstWindowName"Tomás"
discoveredNames
Camden1
High1
Street1
Harlow1
Quinn9
Herrera1
Veil1
Market1
Saint1
Christopher1
Morris1
Tomás8
persons
0"Harlow"
1"Quinn"
2"Herrera"
3"Saint"
4"Christopher"
5"Morris"
6"Tomás"
places
0"Camden"
1"High"
2"Street"
globalScore0.699
windowScore0.667
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences47
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount697
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences93
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs33
mean21.12
std20.72
cv0.981
sampleLengths
091
165
262
313
450
56
619
79
814
912
1015
117
1217
1312
1417
1518
163
175
1847
194
2018
216
225
2347
2421
254
264
2730
2817
299
3027
313
3220
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount1
totalSentences73
matches
0"was rusted"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs92
matches(empty)
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences93
ratio0
matches(empty)
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount309
adjectiveStacks0
stackExamples(empty)
adverbCount5
adverbRatio0.016181229773462782
lyAdverbCount3
lyAdverbRatio0.009708737864077669
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences93
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences93
mean7.49
std4.25
cv0.567
sampleLengths
024
111
213
34
47
516
68
78
87
92
1018
113
124
1312
1413
156
168
1718
1811
1912
203
214
226
234
249
252
2611
278
2816
293
3010
316
325
336
348
359
3614
3712
384
395
406
417
429
432
446
4512
465
479
483
4913
40.32% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats9
diversityRatio0.27956989247311825
totalSentences93
uniqueOpeners26
0.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount0
totalSentences68
matches(empty)
ratio0
49.41% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount29
totalSentences68
matches
0"She checked her wrist."
1"Her lungs burned with every"
2"He moved like a man"
3"She didn't need to."
4"She sprinted, her military bearing"
5"Her heart hammered against her"
6"She saw him pause near"
7"She knew the rumors."
8"She knew the files marked"
9"She closed the distance."
10"Her breath plumed in the"
11"His olive skin gleamed with"
12"He didn't run."
13"He leaned against the concrete"
14"Her hand hovered near her"
15"She kept her eyes locked"
16"She had taken it from"
17"It pulsed with a faint,"
18"She held it up."
19"His expression hardened."
ratio0.426
0.00% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount66
totalSentences68
matches
0"Detective Harlow Quinn pushed her"
1"Water streamed down her closely"
2"She checked her wrist."
3"The worn leather watch showed"
4"Her lungs burned with every"
5"The city smelled of wet"
6"A shadow darted into the"
7"He moved like a man"
8"Quinn didn't shout."
9"She didn't need to."
10"The sound of her boots"
11"She sprinted, her military bearing"
12"Her heart hammered against her"
13"Quinn rounded the corner of"
14"The neon sign of a"
15"She saw him pause near"
16"The metal grating was rusted,"
17"The Veil Market."
18"She knew the rumors."
19"She knew the files marked"
ratio0.971
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences68
matches(empty)
ratio0
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences22
technicalSentenceCount1
matches
0"Rain hammered the asphalt of Camden High Street, turning the road into a slick black mirror that reflected the neon signs of the city."
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags3
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags0
84.0178%