Run: 2026-10-27-01M5YG5PBQQTTQQSSX3S74C6G1

Run Details

Duration:
41.4s
Cost:
$0.015624
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
The constable at the street entrance held out a bone token on his palm. “They took this off the dead man. The woman downstairs says we needed it to get in.” Detective Harlow Quinn took the token between finger and thumb. It was a thin disc, yellow at the edges, with a hole drilled through its centre. Someone had scratched a crescent into one face. “Did she say what it opened?” “She said it got us past the door.” Quinn looked at the stairwell behind him. Plywood covered the entrance to the disused Camden station, and a fresh police seal stretched across the boards. Two bolts lay on the pavement beside a cordless drill. “You got past without it.” “The boards weren’t there when the first car arrived.” “Who put them up?” The constable looked over his shoulder. “We’re asking.” Quinn slipped the token into an evidence bag. Beneath her coat, the worn leather strap of her watch caught on her cuff. She pulled it free and checked the time: 04:17. “Keep asking. Nobody touches the boards.” She descended through air that smelled of wet plaster and coal dust. A strip light buzzed above the ticket hall, though the station had been cut off from the grid eleven years earlier. Beyond the barriers, a woman sat on a plastic chair with a blanket around her shoulders. Red curls spilled across her round glasses as she bent over a leather satchel. Sergeant Patel stood beside her, holding a paper cup. “Detective. This is Eva Kowalski. She found him.” Eva raised her head. Freckles stood out against her pale skin. “I heard him first. I found him after that.” “What did you hear?” “A crash. Metal hitting tile.” Eva tucked a curl behind her left ear. “Then someone shouted.” “What did they shout?” “I couldn’t make out the words.” Patel handed her the cup. She gripped it without drinking. Quinn glanced at the satchel. Three books protruded from it, their pages crowded with paper slips. “Were you here for the books?” “I was here to buy one. A catalogue of protective inscriptions.” “At four in the morning?” “The seller kept his own hours.” Patel tipped his head towards the platform. “Come and see where he kept them.” The escalators had been stripped to their frames. Quinn followed Patel down a service staircase and emerged beside a platform lined with stalls. Velvet cloth covered trestle tables; glass jars held powders, teeth, and coils of dried vegetation. A rack of silver knives stood beside a crate of oranges. The fruit had begun to rot around the stems. At the far end, a man lay on his back beneath a poster for a film released twenty years ago. A forensic officer crouched beside him, sealing a swab. The dead man wore a dark suit and a waistcoat buttoned over his stomach. Blood had soaked the cloth beneath his left arm and spread into the grout. A narrow knife lay near his hand. Patel stopped outside the marked area. “Name’s Daniel Voss. Forty-eight. Passport in his inside pocket. Kowalski knew him as a bookseller.” “Cause?” “Stab wound under the arm, if the doctor agrees. The knife fits. There’s blood on the blade and his prints on the handle.” Quinn studied the body. Voss’s right hand rested palm-up, fingers curled. His left arm lay against his side, the sleeve creased where someone had bent it. Patel pointed to a stall opposite. “Kowalski says she was there when she heard the crash. By the time she reached him, he was on the floor. She called an ambulance.” “Where’s the phone?” “She used the one on the wall.” Quinn followed his gaze. A black telephone hung beside a tiled pillar. Its cord disappeared into a junction box with a cracked lid. “The line still works?” “The operator logged the call at 03:42. Kowalski gave the station name. Ambulance control sent us with the crew.” Quinn walked along the edge of the cordon. The tiles around Voss were dusty, except for a broad clean patch behind his shoulders. A scatter of pale grit lay over his shoes. “Who moved him?” Patel shook his head. “Paramedics checked for a pulse. They didn’t move him from that spot.” Quinn crouched. The clean patch had a straight edge, as though a heavy object had rested there for years. Four brass screws sat in the tile at its corners. One had been pulled loose and left in the dust. “What stood here?” Patel looked up at the poster. “A bench?” “Find it.” He sent a constable along the platform. Quinn leaned closer to Voss’s shoes. Both soles showed at their edges, coated in the same pale grit. The tops of the shoes were cleaner, apart from the scatter across the toes. “Did he walk through the dust and fall backwards?” she asked. “Looks that way.” “Then why’s it on his soles and not on his trousers?” Patel examined the trouser cuffs. Dark wool brushed the tile; no pale streaks marked it. “He brushed against something on his way down.” “Both feet?” Patel’s mouth tightened. “Or someone put it there.” Quinn pointed beyond the body. A thin white line crossed the platform from the clean patch towards the track. It broke where the paramedics had walked, then resumed beside a drainage grille. “Get a photograph before anyone else crosses it.” The forensic officer raised her camera. Quinn waited for the flash, then traced the line with her eyes. It ended at the lip of the platform, where a smear of white marked the edge. A constable returned. “Bench is behind the bookstall, ma’am. Turned on its side.” The bookstall stood five metres away, screened from the body by hanging rugs. Quinn walked around it. A wooden bench leaned against the wall, its iron feet chipped where the screws had held them. White grit clung to the underside. On the wall above it, a rectangular space showed through the grime. A framed print lay face down on the floor. Patel lifted the frame by its edge. The print showed the station in service, passengers in coats waiting beneath a clock. The glass had cracked across the clock face. “That’s your crash,” he said. “Could be.” The lower corner of the frame was wet. Quinn touched the tile beside it with a gloved finger. Water had gathered in a shallow groove and run towards the platform. “Where did this come from?” A pipe ran down the wall. Its valve had been turned shut, but water beaded around the joint. Beneath it stood an empty metal bucket. Patel peered into the bucket. “Cleaner heard the commotion, dropped the frame and ran?” “Then the bucket would have fallen too.” “Someone closed the valve.” Quinn looked at the wall behind the bench. A dark handprint marked the tile just above the floor. Four fingers pointed upwards; the thumb angled towards the pipe. “Photograph that as well.” Eva appeared at the end of the stall, escorted by the constable. “I told the sergeant about the leak.” Patel turned. “You told me the pipe was dripping.” “It was. The bucket was half full when I arrived.” “Who emptied it?” “I don’t know.” Quinn indicated the handprint. “Did you touch that wall?” Eva bent to look, keeping her hands inside the blanket. “No. Daniel’s stall was over there.” She pointed to a table piled with books. “He kept the catalogue under the counter. He didn’t leave it out with the others.” “Was he at the stall when you arrived?” “I saw his coat. He was wearing it.” “That wasn’t my question.” Eva pressed her lips together. “I saw him from the stairs. He stood by the table with his back to me. I called his name, but he didn’t answer. Then the lights went out.” “For how long?” “I counted to ten. I heard the crash at six.” Patel folded his arms. “You didn’t mention the lights before.” “You asked where I found him.” “I asked what happened.” “You asked whether I touched the knife.” Quinn turned back to the bench. Water had darkened one end of the wooden seat. The other remained dry, though dust covered both ends. “Did you see anyone else?” “Not on the platform.” Quinn looked at her. “Where, then?” “On the stairs. A man passed me on his way up. He wore a porter’s jacket.” “What colour?” “Blue. Brass buttons.” “Did he speak to you?” “He told me the market was closed.” Patel’s eyes moved to the rows of unattended stalls. “Convenient. A stranger nobody else saw.” “There were people here when I arrived,” Eva answered. “I passed three at the ticket barriers.” “Names?” “I didn’t ask.” Quinn left them at the bench and returned to the body. The forensic officer had opened Voss’s coat. His shirt beneath the waistcoat was white, except for the blood at his side. A thin brass chain crossed his chest and vanished into a pocket. “What’s on the chain?” Quinn asked. The officer drew out a small compass with a gloved hand. Verdigris mottled its brass casing, and tiny symbols circled the face. The needle pointed towards the far wall. “Don’t open it,” Eva called. Patel stepped aside as she approached. “It’s a compass,” he said. “I can see that.” Quinn took a closer look at the symbols. Their lines had been cut into the metal, not painted. “What does it show?” “Not north.” Patel held out his hand. “Then you can explain it at the station.” Eva kept her eyes on the compass. “It points to a rift. An opening between places.” Patel gave a short laugh. Quinn watched the needle. As the officer turned the casing, the needle swung and settled towards the same patch of wall. “Put it on the tile,” Quinn said. The officer placed it beside the body. The needle held its position. Quinn crossed to the wall. Damp streaked the tiles beneath an advertising frame. A service door stood to the left, its padlock coated with rust. To the right, a section of tile looked newer than the rest, though dirt had settled into the grout. Patel rattled the padlock. “Solid.” Quinn studied the newer section. The bottom row sat a fraction proud of the floor. A narrow scrape ran across the tile in front of it, interrupted by the white line of grit. She knelt and pressed her fingers against the grout. The lower edge shifted. “Get me a light.” Patel handed over his torch. Quinn shone it into the gap beneath the tiles. A strip of rubber showed behind them, compressed against the floor. “Not a repair,” she said. “A door.” Patel crouched beside her. He found a recessed catch near the advertising frame and pulled it. The tiled panel swung inwards on hidden hinges, dragging a short arc through the dust. Beyond it lay a narrow room with shelves built into the walls. A single lamp burned over a table. The air carried the metallic smell of blood. Patel stepped through first. Quinn followed, careful of the floor. A pool had dried beneath the table, and a second knife lay in it. Its handle was clean black wood; its blade had disappeared beneath a folded cloth. On the table stood a metal bucket, filled to the rim with pink water. A wet cloth hung over its side. Patel stared at it. “The bucket from the platform.” “Another one. Eva’s was empty.” Quinn pointed to a pair of parallel marks in the blood. They crossed the floor towards the door, spaced the width of a man’s shoulders. At the threshold, the marks vanished beneath pale grit. Patel looked back towards Voss. “They dragged him out.” “And put a different knife beside him.” The sergeant moved towards the table. Quinn held out an arm. “Stop. Look at the floor.” A shoeprint marked the blood beside the bucket. Its heel had a square notch missing from the outer edge. Another print, fainter, led towards a shelf at the back. Patel lifted his torch. “There’s something under the shelf.” Quinn followed the beam. A folded blue jacket lay wedged against the wall. One brass button had come loose and rested in the blood beside the notched heel mark. From the platform, Eva’s voice reached them. “That was his jacket.” Quinn turned. “Whose?” “Daniel’s porter. The man on the stairs.” Patel looked from the jacket to the body outside. “You knew him?” Eva gripped the strap of her satchel. “I knew his face. Daniel called him Morris.” Quinn’s hand closed around the doorframe. “Did he give you a first name?” “No.” “Did he have a mark on his face?” Eva frowned. “A scar. Here.” She touched the skin below her right ear. Quinn took a photograph from her wallet and held it out. The paper had softened at the folds. Eva leaned into the light. “That’s him,” she said. “That’s the man I passed on the stairs.”
created_at"2026-10-27T10:58:21.183Z" 10/27/2026, 10:58:21 AM
model"openai/gpt-6.1-terra-20261026"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency3718
moderation_latency(null)
generation_time41342
tokens_prompt1112
tokens_completion3355
native_tokens_prompt1009
native_tokens_completion2923
native_tokens_completion_images0
native_tokens_reasoning151
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"
usage0.015624
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.22.1; linux; x64))"
http_referer(null)
request_id"req-1793098701-c36xtdvtP9YzYJ8Et1YQ"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1793098701-U27SSpzRWmpPm8imoAXE"
upstream_id"resp_0720f478ffb408e2016ae083cd41f887d1bbcc5e7b559b696e"
provider_responses
0
endpoint_id"2d2ad10f-098e-4bbf-aa95-11f705b2b9a2"
id"resp_0720f478ffb408e2016ae083cd41f887d1bbcc5e7b559b696e"
is_byokfalse
latency268
model_permaslug"openai/gpt-6.1-terra-20261026"
provider_name"OpenAI"
status200
total_cost0.015624
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
totalTags12
adverbTagCount0
adverbTags(empty)
dialogueSentences109
tagDensity0.11
leniency0.22
rawRatio0
effectiveRatio0
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount2159
totalAiIsmAdverbs0
found(empty)
highlights(empty)
80.00% AI-ism character names
Target: 0 AI-default names (17 tracked, −20% each)
codexExemptions(empty)
found
0"Patel"
100.00% AI-ism location names
Target: 0 AI-default location names (33 tracked, −20% each)
codexExemptions(empty)
found(empty)
90.74% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount2159
totalAiIsms4
found
0
word"velvet"
count1
1
word"stomach"
count1
2
word"pulse"
count1
3
word"traced"
count1
highlights
0"velvet"
1"stomach"
2"pulse"
3"traced"
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
narrationSentences171
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount0
narrationSentences171
filterMatches
0"watch"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences268
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen29
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords2159
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions26
unquotedAttributions0
matches(empty)
33.33% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions78
wordCount1475
uniqueNames6
maxNameDensity2.24
worstName"Quinn"
maxWindowNameDensity4
worstWindowName"Quinn"
discoveredNames
Harlow1
Quinn33
Camden1
Patel26
Voss5
Eva12
persons
0"Harlow"
1"Quinn"
2"Patel"
3"Eva"
places(empty)
globalScore0.381
windowScore0.333
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences124
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount2159
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences268
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs179
mean12.06
std11.78
cv0.976
sampleLengths
014
117
234
36
48
535
65
79
84
96
102
1131
126
1363
149
158
1611
179
184
1916
204
216
2210
2316
246
2511
265
276
287
297
3058
3129
3235
336
3415
351
3623
3726
386
3925
403
417
4223
434
4419
4532
463
474
4812
4939
99.11% Passive voice overuse
Target: ≤2% passive sentences
passiveCount3
totalSentences171
matches
0"been stripped"
1"been pulled"
2"been turned"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs246
matches(empty)
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount4
flaggedSentences4
totalSentences268
ratio0.015
matches
0"Velvet cloth covered trestle tables; glass jars held powders, teeth, and coils of dried vegetation."
1"Dark wool brushed the tile; no pale streaks marked it."
2"Four fingers pointed upwards; the thumb angled towards the pipe."
3"Its handle was clean black wood; its blade had disappeared beneath a folded cloth."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount1476
adjectiveStacks0
stackExamples(empty)
adverbCount13
adverbRatio0.008807588075880758
lyAdverbCount0
lyAdverbRatio0
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences268
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences268
mean8.06
std4.57
cv0.568
sampleLengths
014
117
210
316
48
56
68
77
818
910
105
119
124
136
142
158
1614
179
186
1912
2021
2116
2214
239
248
254
267
279
284
2913
303
314
326
335
345
355
3611
376
3811
395
406
417
427
438
4415
4515
4611
479
4820
499
48.13% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats5
diversityRatio0.2947761194029851
totalSentences268
uniqueOpeners79
0.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount0
totalSentences158
matches(empty)
ratio0
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount19
totalSentences158
matches
0"It was a thin disc,"
1"She pulled it free and"
2"She descended through air that"
3"She gripped it without drinking."
4"His left arm lay against"
5"Its cord disappeared into a"
6"He sent a constable along"
7"It broke where the paramedics"
8"It ended at the lip"
9"Its valve had been turned"
10"She pointed to a table"
11"His shirt beneath the waistcoat"
12"Their lines had been cut"
13"She knelt and pressed her"
14"He found a recessed catch"
15"Its handle was clean black"
16"They crossed the floor towards"
17"Its heel had a square"
18"She touched the skin below"
ratio0.12
26.46% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount137
totalSentences158
matches
0"The constable at the street"
1"Detective Harlow Quinn took the"
2"It was a thin disc,"
3"Someone had scratched a crescent"
4"Quinn looked at the stairwell"
5"Plywood covered the entrance to"
6"The constable looked over his"
7"Quinn slipped the token into"
8"She pulled it free and"
9"She descended through air that"
10"A strip light buzzed above"
11"Sergeant Patel stood beside her,"
12"Eva raised her head."
13"Freckles stood out against her"
14"Eva tucked a curl behind"
15"Patel handed her the cup."
16"She gripped it without drinking."
17"Quinn glanced at the satchel."
18"Patel tipped his head towards"
19"The escalators had been stripped"
ratio0.867
31.65% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount1
totalSentences158
matches
0"To the right, a section"
ratio0.006
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences65
technicalSentenceCount0
matches(empty)
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags12
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags9
fancyCount0
fancyTags(empty)
dialogueSentences109
tagDensity0.083
leniency0.165
rawRatio0
effectiveRatio0
86.9804%