Run: 2026-09-23-01M37J2J9D8HKMPK9451V4J02Q

Run Details

Duration:
57.3s
Cost:
$0.030508
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="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

AI
Detective Harlow Quinn reached the bottom of the station stairs with grit in her teeth and the sound of a generator rattling somewhere below. A patrol officer stood beside a rusted ticket gate, holding up the cordon tape so she could pass. Beyond him, an enamel sign announced CAMDEN SOUTH in letters the Underground had stopped using decades ago. “How long has the body been here?” “Found at half five. Station staff called it in.” “There are no station staff.” The officer glanced down the stairs behind her. “The people doing the survey, ma’am. They were checking the foundations.” Quinn crossed the gate. Her shoes clicked over loose mosaic tiles. The station smelled of damp concrete, hot dust from the floodlights, and something sweeter beneath it: burnt sugar, or candle wax. On the platform, a photographer crouched beside a man in a grey coat. The man lay on his back near an old advertising wall, one arm stretched above his head. Blood had soaked through his shirt and spread beneath his shoulder. A row of empty trestle tables stood against the opposite wall. Each carried a scrap of coloured cloth, and one held a cluster of candle stubs fused to the wood. DS Malik waited beside the tables, his notebook open. “Welcome to the strangest car boot sale in London.” Quinn stopped short of the body. Her worn watch brushed her coat cuff as she folded her arms. “You’ve spoken to the survey crew?” “Three of them. They came down through the service entrance at five twenty-eight. Found him like this. Nobody saw anyone leave.” “And the tables?” “Unlicensed market. Sellers cleared out when something went wrong.” Malik pointed his pen towards a staircase at the far end. “We found blood on the steps. One of them stabbed him, ran up there.” Quinn looked at the staircase. The first six steps shone with water. A slow leak dripped from a pipe above them and struck the same tread, over and over. “How much blood?” “One print. Partial shoe. Forensics are on it.” She walked round the body without crossing the markers. The man’s coat hung open. Its right lapel had folded beneath him, and a narrow wound showed through his shirt below the collarbone. His eyes faced the tiled wall. Dried blood darkened two fingers of his left hand. His right hand held a small disc, pale against his skin. “Age?” “Forties, give or take. No wallet. No phone.” “What’s in his hand?” Malik checked his notes. “Bone, according to the photographer. Hasn’t been collected yet.” The disc had a hole through its centre. Someone had carved three short lines along one edge, deep enough to catch shadow. “Robbery seems thin if they left anything worth taking.” Malik tilted his head towards the tables. “Depends what they were selling.” Quinn followed his gaze. An open wooden case held a velvet depression the size of a pocket watch. Dust outlined where its contents had rested. At the next table, torn brown paper bore a grease-pencil price: TWO FOR A MEMORY. Someone had scored out MEMORY and written NAME beneath it. “Student performance art?” Malik offered. “Under a station with no public entrance?” “That’s why it’s unlicensed.” Quinn crouched beside the victim. The photographer lowered his camera and shifted back to give her a clear view. A fine line of pale grit marked the man’s coat sleeve. The grit lay across a broad smear of blood, not beneath it. She looked at his shoes. Both soles carried dry grey dust in their grooves. “Platform’s wet.” “Pipe’s been leaking since the place shut,” Malik answered. “Could’ve walked round it.” “Everywhere?” The damp reached from the track edge to the wall. Her own shoes left dark prints where dust met water. The victim’s shoes had left none that she could see. At the ticket gate, a voice rose over the generator. “I told them I knew him. You can’t keep asking me to wait up there.” Quinn stood. A young woman had come past the patrol officer, clutching the strap of a worn leather satchel. Curly red hair sprang loose around round glasses. She tucked it behind her left ear as she took in the body, the cameras, the blood. Malik moved to intercept her. “Miss Kowalski. We’ve got your details. You need to stay behind the tape.” “I gave him a name to ask for. If that’s him, I need to see his face.” Quinn stepped between them. “You can look from here. Don’t come closer.” The woman fixed on the man’s grey coat. Her fingers tightened around the satchel strap. “That’s Daniel.” “You knew him as Daniel what?” “I didn’t. He contacted me at work. I was meant to meet him here this morning.” “Where do you work?” “The British Museum. Restricted archives.” Eva Kowalski swallowed. “He said he had an object I could identify.” Malik closed his notebook against his palm. “And you came to an abandoned station?” “He gave me an address on Chalk Farm Road. I found the entrance after the police cars arrived.” “What object?” Quinn asked. Eva looked past her at the wooden case, then at the man’s hand. “I don’t know. He wouldn’t put it in writing.” Quinn watched her gaze settle on the bone disc. Eva drew her satchel closer. “You recognise that?” “No.” The answer came before Quinn had finished speaking. Eva adjusted her glasses and looked at the floor. Malik held out an arm towards the stairs. “Up you go. We’ll speak to you when we’ve finished here.” Eva let the patrol officer guide her back to the gate. Quinn turned to the wall the dead man faced. Old tiles framed an advertisement for soap, its painted family smiling through hairline cracks. At first glance the blood beside it looked like a handprint left by someone bracing themselves. Four streaks ran across the blue border. “Who examined this?” “Photographed it. No usable prints visible.” Malik joined her. “Victim put his hand out after the stabbing. Fell backwards.” Quinn held her own hand beside the marks without touching them. The streaks lay at shoulder height for the dead man. Each one ran towards the smiling family, but the beads at their ends had collected along the side of the streaks, against the direction gravity should have pulled them. “Get me the first photograph of this wall.” The photographer scrolled through his camera and held up the screen. Quinn compared the image with the tiles in front of her. Nothing had changed since the scene team arrived. A bead of blood sat in a grout line, round and thick, while another had dried in a hook against the edge of a tile. “Could the platform slope?” Malik asked. “Not enough for blood to climb a wall.” She moved along the advertisement. Its bottom edge met a band of black tiles. Most grout lines held decades of grime. One line had no grime at all. A pale grain of mortar clung to it. Quinn followed the clean line upward, around the advertisement and down its far side. Malik leaned in. “Maintenance panel.” “Where’s the handle?” “Painted over. Could be a hatch for wiring.” Quinn stepped back. The entire advertisement sat inside that narrow clean border. At floor level, a curved scratch crossed the wet dust. It began beneath the left corner of the frame and swept out towards the victim’s shoulder. A second scratch ran beside it, packed with pale grit like the grit on his sleeve. “He wasn’t stabbed here,” she said. Malik looked down at the pool beneath the man. “There’s enough blood to fill a bucket.” “Blood from the wound soaked his shirt. It ran out when someone put him down. Look at his shoes.” Malik crouched, keeping his hands clear of the body. “Dust.” “No wet prints leading in. No drag mark across the platform. His coat picked up grit on top of the blood, along that sleeve. He came through the wall after he was hurt.” Malik rose and studied the advertisement. He reached towards the edge, then stopped when Quinn caught his wrist. “Don’t touch it.” “It’s tile, Quinn.” A brass glint caught her eye beneath the nearest table. She crouched and found a small compass lodged against one leg, its casing green with verdigris. Protective-looking marks covered the face. Its needle pointed towards the advertisement. Quinn left it where it lay. “Photograph that too.” Malik peered over her shoulder. “A compass?” “I can see that.” “North’s behind us.” Quinn checked the compass against the direction of the stairs, then shifted her position to look at it from another angle. The needle held on the wall. A fresh nick shone through the corrosion on the casing; someone had struck it against something hard. She stood and returned to the blood marks. One of the victim’s stained fingertips fitted the lowest streak, but his hand had not come to rest anywhere near the wall. He had touched it while he still stood. “The panel moved,” Quinn said. “Those drops ran down when it faced another direction. Then someone turned it back.” Malik’s eyes moved from the dried beads to the clean grout and the scratches at their feet. The generator coughed; in the gap before it caught again, Quinn heard air hiss through the narrow seam beside the soap advertisement. Malik lifted his radio. “Scene team, hold your positions. Nobody uses the far stairs. I want the wall documented from top to bottom.” Quinn took one pace back so the photographer could get past her. She pointed to the clean grout, then to the curved marks in the dust. “Start there. I want every inch of that seam before anyone opens it.”
created_at"2026-09-23T16:37:40.287Z" 9/23/2026, 4:37:40 PM
model"openai/gpt-6-sol-20260922"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency19105
moderation_latency(null)
generation_time57216
tokens_prompt1112
tokens_completion2518
native_tokens_prompt1009
native_tokens_completion2849
native_tokens_completion_images0
native_tokens_reasoning808
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"
usage0.030508
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.20.0; linux; x64))"
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request_id"req-1790181460-JgjQorZS217f389QItbS"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1790181460-4ffGkPVF8kZbdFvVYioa"
upstream_id"resp_0f0302d194f8dd04016ab4005475c887d1a450808df49b4af2"
provider_responses
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endpoint_id"1cfc7d9d-4404-4b8e-9ee4-58ae45c9dcd4"
id"resp_0f0302d194f8dd04016ab4005475c887d1a450808df49b4af2"
is_byokfalse
latency408
model_permaslug"openai/gpt-6-sol-20260922"
provider_name"OpenAI"
status200
total_cost0.030508
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
totalTags9
adverbTagCount0
adverbTags(empty)
dialogueSentences66
tagDensity0.136
leniency0.273
rawRatio0
effectiveRatio0
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1621
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)
90.75% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1621
totalAiIsms3
found
0
word"mosaic"
count1
1
word"velvet"
count1
2
word"glint"
count1
highlights
0"mosaic"
1"velvet"
2"glint"
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
narrationSentences112
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount0
narrationSentences112
filterMatches
0"watch"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences169
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen33
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1621
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions9
unquotedAttributions0
matches(empty)
50.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions48
wordCount1123
uniqueNames6
maxNameDensity1.96
worstName"Quinn"
maxWindowNameDensity3.5
worstWindowName"Quinn"
discoveredNames
Harlow1
Quinn22
Underground1
Malik18
Kowalski1
Eva5
persons
0"Harlow"
1"Quinn"
2"Underground"
3"Malik"
4"Kowalski"
5"Eva"
places(empty)
globalScore0.52
windowScore0.5
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences87
glossingSentenceCount1
matches
0"looked like a handprint left by someone b"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1621
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences169
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs102
mean15.89
std16.56
cv1.042
sampleLengths
059
17
29
35
48
511
632
771
89
99
1018
116
1221
133
1434
1529
163
178
1858
191
208
214
224
239
2422
259
267
275
2850
295
307
314
3256
332
3413
351
3630
3710
3815
3944
405
4113
4217
434
448
4515
462
476
4816
494
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount0
totalSentences112
matches(empty)
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs178
matches(empty)
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount2
flaggedSentences2
totalSentences169
ratio0.012
matches
0"A fresh nick shone through the corrosion on the casing; someone had struck it against something hard."
1"The generator coughed; in the gap before it caught again, Quinn heard air hiss through the narrow seam beside the soap advertisement."
94.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount1125
adjectiveStacks1
stackExamples
0"over loose mosaic tiles."
adverbCount16
adverbRatio0.014222222222222223
lyAdverbCount3
lyAdverbRatio0.0026666666666666666
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences169
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences169
mean9.59
std5.73
cv0.597
sampleLengths
024
118
217
37
49
55
68
711
84
97
1021
1113
1217
1311
1411
1519
169
179
186
1912
206
2121
223
2320
2414
255
267
2717
283
298
309
315
3218
336
349
3511
361
378
384
394
409
418
4214
439
447
455
464
4714
487
4915
68.44% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats1
diversityRatio0.41420118343195267
totalSentences169
uniqueOpeners70
0.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount0
totalSentences105
matches(empty)
ratio0
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount19
totalSentences105
matches
0"Her shoes clicked over loose"
1"Her worn watch brushed her"
2"She walked round the body"
3"Its right lapel had folded"
4"His eyes faced the tiled"
5"His right hand held a"
6"She looked at his shoes."
7"Her own shoes left dark"
8"She tucked it behind her"
9"Her fingers tightened around the"
10"She moved along the advertisement."
11"Its bottom edge met a"
12"It began beneath the left"
13"He reached towards the edge,"
14"She crouched and found a"
15"Its needle pointed towards the"
16"She stood and returned to"
17"He had touched it while"
18"She pointed to the clean"
ratio0.181
26.67% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount91
totalSentences105
matches
0"Detective Harlow Quinn reached the"
1"A patrol officer stood beside"
2"The officer glanced down the"
3"Quinn crossed the gate."
4"Her shoes clicked over loose"
5"The station smelled of damp"
6"The man lay on his"
7"Blood had soaked through his"
8"A row of empty trestle"
9"Each carried a scrap of"
10"DS Malik waited beside the"
11"Quinn stopped short of the"
12"Her worn watch brushed her"
13"Malik pointed his pen towards"
14"Quinn looked at the staircase."
15"The first six steps shone"
16"A slow leak dripped from"
17"She walked round the body"
18"The man’s coat hung open."
19"Its right lapel had folded"
ratio0.867
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences105
matches(empty)
ratio0
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences50
technicalSentenceCount0
matches(empty)
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags9
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags5
fancyCount0
fancyTags(empty)
dialogueSentences66
tagDensity0.076
leniency0.152
rawRatio0
effectiveRatio0
87.6618%