Run: 2026-09-23-01M37HS6N4RKRMK91A261Z3GKN

Run Details

Duration:
41.7s
Cost:
$0.022098
Provider:
OpenAI

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 turned the Camden pavement black and filled its cracks with silver. Detective Harlow Quinn stepped off the kerb as a bus pulled away, its tyres throwing a sheet of water across her trousers. On the opposite side of the road, Tomás Herrera looked back. He stopped beneath the awning of a closed phone shop. For one second, they faced each other through the rain and the bus’s red exhaust haze. Quinn lifted her warrant card. “Herrera. We need to talk.” He ran. Quinn shoved the card into her coat and cut between two taxis. A horn blasted against her shoulder. Herrera cleared a stack of crates outside a restaurant, landed in the road and turned into a passage beside a shuttered arcade. “You’ve got a patient waiting?” Quinn called. He glanced back. His wet curls clung to his forehead. “Go home, Detective.” At The Raven’s Nest, an hour earlier, he had told her he hadn’t seen the man in the photograph. Then she had spotted the same man’s blood on the cuff of his jacket. Herrera had left through the bar’s front door before she could ask about it. She had waited until he reached the street to follow. Now his jacket caught on a nail in the passage wall. He tore free and kept moving. Quinn took the corner wide, avoiding a bin he had kicked into her path. Her shoes struck broken glass. Ahead, Herrera vaulted a low chain across a service lane and landed badly. His hand went to his ribs. “Stop running and let me see that cuff.” “No.” “Whose blood is it?” Herrera pushed through a gap between two buildings. “Not mine.” Quinn caught the chain at thigh height and stepped over it. The lane ended at a street crowded with people spilling out of late bars. Herrera entered the crowd with his shoulders hunched, one hand pressed to his side. A woman in a clear plastic poncho blocked Quinn’s way. Quinn turned sideways, slipped past her and spotted Herrera’s dark head near the pedestrian crossing. He had stopped. A delivery lorry ground through the junction, cutting off his route. Quinn closed the distance. Herrera looked at the lorry, then at her. “You searched the wrong man.” “Then give me the right one.” “Ask him yourself.” He stepped off the pavement behind the lorry. Quinn followed, but a cyclist shot through the gap, his handlebars clipping her arm. She caught herself against the lorry’s wet flank. When it passed, Herrera had reached the far side and was heading towards a brick wall painted with a fading advertisement for cigarettes. No exit. Quinn eased her pace and pulled her phone from her pocket. Herrera ran straight at the wall. A narrow iron gate sat in its shadow, almost lost beneath ivy and fly-posters. He grabbed the bars. For a moment Quinn thought it was locked. Then he fed something small through a slot beside the latch. The gate snapped open. “Herrera!” He twisted through. A length of black cord caught on the latch and broke. Something pale bounced across the pavement. Quinn reached the gate as it slammed shut. Beyond the bars, a stairwell dropped into darkness. Herrera’s footsteps struck metal below. She tried the handle. It held firm. At her feet lay a disc of bone with a hole drilled through it. The broken cord still trailed from one side. Quinn picked it up. A shallow cut ran across its face: three lines crossed by a fourth. She put it into the slot. The latch clicked. Quinn pulled the gate open and looked down. The stairs descended between tiled walls stained brown by years of water. A single bulb burned at the first landing. Herrera’s footsteps faded beneath a low mechanical hum. Her radio crackled when she pressed it. “Control, Quinn. I’m at a gated access off Parkway, east side. Suspect has gone below street level. Send a unit to the entrance.” Static swallowed the reply. She tried again and caught only the first syllable of her own name before the signal died. Quinn looked back. A taxi rolled past the mouth of the lane, its roof light glowing through the rain. The gate hung open against her hand. She could wait on the street for another officer and lose Herrera, or go down without one. Three years ago, DS Morris had followed a man through a service door while Quinn took the front of the building. She still remembered the blank face of the door when she reached it. She had spent months pulling at every thread in the case and had found nothing that explained what happened on the other side. Below her, metal scraped against stone. Quinn drew her torch and started down. The stairs turned twice. Water dripped from an exposed pipe and collected in the centres of the treads. At the second landing, someone had scratched an arrow into the tile beside the words NO TRAINS. A fresh muddy print crossed the arrow. Herrera had left it with his right shoe. Quinn followed the prints to a steel door with a round window. Yellow light leaked through the glass. She raised her torch and saw shelves beyond it, then a moving figure that vanished when the light touched the pane. She pushed the door open. A man stood behind a wire-mesh counter, sharpening a knife against a whetstone. A strip of green cloth covered his left eye. Beside him, a heap of umbrellas dripped into a bucket. “Token.” He held out his hand. Quinn showed him the disc without letting go. “Which way did Herrera go?” The knife stopped moving. “Token.” “He came through here. Short dark hair, grey jacket. I’m a police officer.” The man set the knife on the counter. “I heard you the first time.” From somewhere beyond him came a woman’s cry, cut short by a burst of laughter. Quinn leaned towards the mesh. Past the counter, a tiled corridor opened onto a platform crowded with stalls. Red lamps hung from the old station signs. She saw a cage of birds with white feathers and black beaks, and a glass case full of watches whose hands moved in different directions. People passed between the stalls without looking towards the door. Herrera crossed the far end of the platform. Quinn struck the mesh with her palm. “Move.” The man looked at her worn leather watch. “You’ll want to cover that.” “Why?” “It has a face.” Quinn stared at him. He pointed at the disc between her fingers. “Pay, or stand in the doorway.” She pushed the token through the mesh. He dropped it into a wooden box with a dozen others and stepped aside. Quinn passed him, keeping her torch low. The corridor smelled of hot metal, damp wool and cloves. Her shoes sounded loud on the tile. At its end, the old platform stretched beneath a vaulted roof where paint peeled from the ribs in broad, pale strips. Goods filled every space where passengers might once have stood. A woman measured blue powder into paper twists. Two men argued over a sealed jar that knocked against the counter from the inside. Under a station clock with no hands, a child in a red coat counted coins into a seller’s palm. Quinn searched the crowd. Herrera had disappeared behind a curtain of hanging copper pans. She took a step towards it and stopped. The entrance lay behind her, past the man with the knife and the stairwell that had swallowed her radio signal. Ahead, the crowd pressed around a passage she could not see into. She checked the baton at her hip, slipped her phone deeper into her coat and went after Herrera.
created_at"2026-09-23T16:32:33.453Z" 9/23/2026, 4:32:33 PM
model"openai/gpt-6-sol-20260922"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency12259
moderation_latency(null)
generation_time41684
tokens_prompt1104
tokens_completion1894
native_tokens_prompt984
native_tokens_completion2013
native_tokens_completion_images0
native_tokens_reasoning448
native_tokens_cached0
num_media_prompt(null)
num_input_audio_prompt(null)
num_media_completion0
num_search_results(null)
num_fetches(null)
web_search_engine(null)
origin"https://ncbench.com/"
is_byokfalse
finish_reason"stop"
native_finish_reason"completed"
service_tier"default"
usage0.022098
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.20.0; linux; x64))"
http_referer(null)
request_id"req-1790181153-6Bru5SpIfA3vxB0doX6j"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1790181153-xkdA0o3pBZy3YGgZwmLP"
upstream_id"resp_065607f9c2ce9fc9016ab3ff218fe487d1b5aba81f62f935e4"
provider_responses
0
endpoint_id"1cfc7d9d-4404-4b8e-9ee4-58ae45c9dcd4"
id"resp_065607f9c2ce9fc9016ab3ff218fe487d1b5aba81f62f935e4"
is_byokfalse
latency993
model_permaslug"openai/gpt-6-sol-20260922"
provider_name"OpenAI"
status200
total_cost0.022098
cache_discount(null)
upstream_inference_cost0
provider_name"OpenAI"
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
totalTags2
adverbTagCount0
adverbTags(empty)
dialogueSentences22
tagDensity0.091
leniency0.182
rawRatio0
effectiveRatio0
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1287
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)
84.46% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1287
totalAiIsms4
found
0
word"footsteps"
count2
1
word"mechanical"
count1
2
word"measured"
count1
highlights
0"footsteps"
1"mechanical"
2"measured"
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
narrationSentences118
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount0
narrationSentences118
filterMatches
0"watch"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences138
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen25
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1287
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions3
unquotedAttributions0
matches(empty)
43.89% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions48
wordCount1178
uniqueNames8
maxNameDensity2.12
worstName"Quinn"
maxWindowNameDensity3.5
worstWindowName"Quinn"
discoveredNames
Camden1
Harlow1
Quinn25
Tomás1
Herrera17
Raven1
Nest1
Morris1
persons
0"Harlow"
1"Quinn"
2"Tomás"
3"Herrera"
4"Morris"
places
0"Raven"
globalScore0.439
windowScore0.5
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences93
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1287
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences138
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs59
mean21.81
std20.81
cv0.954
sampleLengths
045
126
25
35
42
540
67
713
857
955
108
111
124
1310
1439
1539
164
1713
186
193
2053
2113
226
2341
241
2520
2628
2739
286
293
3036
317
3223
3321
3443
3557
366
377
3850
3939
405
4132
426
4313
445
4513
4614
4776
488
498
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount0
totalSentences118
matches(empty)
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount1
totalVerbs193
matches
0"was heading"
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences138
ratio0
matches(empty)
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount1180
adjectiveStacks0
stackExamples(empty)
adverbCount18
adverbRatio0.015254237288135594
lyAdverbCount4
lyAdverbRatio0.003389830508474576
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences138
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences138
mean9.33
std5.51
cv0.591
sampleLengths
012
122
211
310
416
55
65
72
812
96
1022
117
123
137
143
1519
1614
1714
1810
1911
206
2114
225
2313
246
258
261
274
288
292
3011
3114
3214
3310
3415
353
3611
374
388
395
406
413
428
4314
448
4523
462
4711
486
4914
54.59% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats3
diversityRatio0.34057971014492755
totalSentences138
uniqueOpeners47
57.97% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount2
totalSentences115
matches
0"Then she had spotted the"
1"Then he fed something small"
ratio0.017
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount30
totalSentences115
matches
0"He stopped beneath the awning"
1"He glanced back."
2"His wet curls clung to"
3"She had waited until he"
4"He tore free and kept"
5"Her shoes struck broken glass."
6"His hand went to his"
7"He had stopped."
8"He stepped off the pavement"
9"She caught herself against the"
10"He grabbed the bars."
11"He twisted through."
12"She tried the handle."
13"It held firm."
14"She put it into the"
15"Her radio crackled when she"
16"She tried again and caught"
17"She could wait on the"
18"She still remembered the blank"
19"She had spent months pulling"
ratio0.261
64.35% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount91
totalSentences115
matches
0"Detective Harlow Quinn stepped off"
1"He stopped beneath the awning"
2"Quinn lifted her warrant card."
3"Quinn shoved the card into"
4"A horn blasted against her"
5"Herrera cleared a stack of"
6"He glanced back."
7"His wet curls clung to"
8"Herrera had left through the"
9"She had waited until he"
10"He tore free and kept"
11"Quinn took the corner wide,"
12"Her shoes struck broken glass."
13"His hand went to his"
14"Herrera pushed through a gap"
15"Quinn caught the chain at"
16"The lane ended at a"
17"Herrera entered the crowd with"
18"A woman in a clear"
19"Quinn turned sideways, slipped past"
ratio0.791
43.48% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount1
totalSentences115
matches
0"Now his jacket caught on"
ratio0.009
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences55
technicalSentenceCount1
matches
0"The entrance lay behind her, past the man with the knife and the stairwell that had swallowed her radio signal."
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags2
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags1
fancyCount0
fancyTags(empty)
dialogueSentences22
tagDensity0.045
leniency0.091
rawRatio0
effectiveRatio0
91.6245%