Run: 2026-07-09-01KX4102CBXV2HWGZQQFD0JH1S

Run Details

Duration:
41.3s
Cost:
$0.038297
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 old station lay below Camden like a broken tooth under the city. Detective Harlow Quinn stepped off the maintenance stairs and into a platform that no longer existed on any Transport for London map. Tiles the colour of old teeth climbed the walls. Half the station name remained above the tracks. —DEN. Water dripped from the tunnel mouth. It struck the rails with the steady patience of a metronome. Someone had strung red-and-white police tape across the platform. It looked pathetic against the market beyond it. Stalls crowded the darkness beneath shuttered ticket windows: cages of blue moths, stoppered bottles containing weather, knives laid on velvet beside jars of teeth. A woman with a crow’s skull for a face pulled down the grille of her stall when Quinn passed. Another vendor covered a tray of black coins with a cloth. The market had gone quiet for the police. That silence bothered Quinn more than the corpse. DC Arjun Bell crouched beside it near the yellow line, his suit trousers dark at both knees. He wore latex gloves and held a torch under his chin while he stared at something on the floor. “You got here fast,” he called. Quinn checked the cracked face of her leather-watch. “You called at six twenty.” “You answered at six twenty-one.” “I was driving.” Bell rose, broad-shouldered and round-faced, his tie loosened beneath a rain-spotted collar. “You drove here?” “I drove to Camden. Your constable led me through a kebab shop and a locked cellar. Don’t make it sound heroic.” Bell looked past her towards the stairwell. “You bring the token?” Quinn opened her palm. A small disk of polished bone rested there, drilled with a hole at its centre. Black thread looped through it. The surface held a carved eye that seemed to follow movement. Bell scratched at his jaw. “Still hate that thing.” “It got us through the door.” “It got us through a wall. There wasn’t a door.” “Write that in your report.” “I enjoy employment.” Quinn pocketed the token and looked down at the dead man. He lay on his back with one arm thrown across the platform edge, fingers dangling over the tracks. He wore a burgundy velvet coat, cream shirt, and polished boots with silver buckles. Blood had soaked the left side of his chest and spread beneath him in a dark, glossy fan. The wound looked clean. Too clean. A brass compass sat near his right hand. Verdigris stained the seam around its casing. Protective sigils ringed its face in cramped, sharp lines. The needle spun in fast, frantic circles. Quinn did not touch it. “Name?” “Leon Vetch.” Bell consulted his notebook. “Human. Thirty-eight. Trader, fence, occasional information broker. Market regulars called him a rat, which I gather wasn’t affectionate.” “Who found him?” “Stallholder named Mrs Wren. Sells remedies.” “Real remedies?” Bell’s mouth tightened. “I didn’t ask.” “You should have.” “She gave him a bottle marked WOLF LUNG.” “Then you definitely should have.” Bell pointed to the corpse. “Single stab wound. No weapon. Blood loss. The pathologist won’t get down here until the market agrees not to eat him.” “Who told you that?” “A man in a fur hat with no eyelids.” Quinn bent beside the body. The smell hit her: iron, damp brick, old electricity, and a chemical sweetness beneath it. She lowered two fingers near the dead man’s throat. The skin had cooled, but not enough for the station’s temperature. No pulse. No breath. A thin streak of blood ran from Vetch’s left ear to his collar. Quinn studied his hands. His fingernails bore soot, except for the thumb and forefinger of his right hand. Those two digits remained clean. Bell watched her. “Fight with the killer?” “No bruising on the knuckles. No skin under the nails.” “He could have cleaned up.” “Not after losing that much blood.” She followed the smear beneath Vetch’s arm. It travelled three feet across the platform, then stopped. No drag marks. No footprints through it. Nothing except a small, crisp crescent in the blood, as if someone had pressed the edge of a coin there. Bell shuffled closer. “I saw that. Think it’s a stamp.” “From what?” “One of the market freaks.” Quinn lifted her eyes. At the far end of the platform, Eva Kowalski stood behind the tape with her worn leather satchel clutched against her ribs. Her curly red hair had escaped its knot and formed a bright cloud around her face. Her round glasses caught the blue flash of a forensic lamp. A uniformed constable stood beside her, pale and unhappy. “Evie,” Quinn called. “Why are you in my scene?” Eva tucked hair behind her left ear. “Your officer rang the British Museum. He asked for someone who could read symbols.” Bell folded his notebook shut. “I asked for an expert. They sent her.” “They sent the only person foolish enough to take a call before breakfast,” Eva muttered. Quinn lifted the tape. “Come through. Don’t touch anything. Don’t step in the blood.” Eva ducked beneath it and stopped near the compass. Her green eyes sharpened behind the lenses. “Oh.” “That means something,” Bell noted. “It means I’d like not to be standing beside it.” “You know what it is?” “A Veil Compass.” Eva pointed without lowering her satchel. “Shade-made. It detects rifts. Doors between places that shouldn’t connect.” Bell looked at the flooded tunnel. “There’s a tunnel.” “No.” Eva’s freckled face had gone tight. “A rift doesn’t mean an entrance. It means a tear. It can open in a mirror, inside a cupboard, under somebody’s tongue.” The constable made a wet choking noise from behind them. Quinn looked at the spinning needle. “Why did Vetch have it?” “People use them to find crossings. Smugglers. Grave robbers. Cults. Anyone who wants to get from one locked room to another without dealing with locks.” Bell tapped his pen against his notebook. “So he found a doorway down here, somebody stabbed him over it, end of story.” Quinn kept her gaze on the body. “If he found a doorway, why is the compass still here?” “Could have dropped it.” “He kept his hand around it while he died.” Bell glanced down. “His hand’s open.” “Now it is.” Quinn drew a pair of evidence forceps from her kit. She caught the compass by its outer ring and lifted it. The needle bucked harder, then snapped north-east. Not towards the tunnel. Towards the dead man’s chest. Eva’s breath caught. “Put it down.” Quinn held the compass above Vetch’s wound. The needle struck against the glass face, fixed there with such force that the casing vibrated between the forceps. Bell stared. “That’s not possible.” “Your report is getting interesting.” Quinn passed the compass to Eva. “Hold it above his left shoulder.” Eva swallowed and did it. The needle spun loose. “Over his boots.” It pointed to the tunnel. “Over his chest.” The needle locked again. Bell crouched. “You think there’s something inside him?” “I think somebody wanted us to find this body where we found it.” “You don’t leave a body in a public market if you want to hide it.” “No.” Quinn ran her torch along the blood fan. “You leave it here if you want witnesses. You leave a weaponless stabbing, a compass, and a corpse beside a tunnel because you want everyone to look at the tunnel.” Eva stared at Vetch’s velvet coat. “The blood is wrong.” Bell threw up one hand. “Thank Christ. Somebody else sees it.” “Don’t celebrate.” Eva knelt carefully, keeping clear of the stains. “It’s too dark at the edges. Human blood oxidises, but this…” She leaned closer. “It smells burnt.” Quinn had smelled it too. That sweet chemical note. “Where’s the blood spatter?” she asked. Bell scanned the tiles. “There.” Three droplets marked the wall at knee height. A fourth sat on the underside of a bench. All lay to Vetch’s right. “The wound is on his left,” Quinn said. “He turned when he got stabbed.” “Then the spray would curve. These drops travelled straight.” Bell looked from the stains to the corpse. His earlier certainty drained from his face. Quinn set her torch against the tiles and examined the platform edge. The yellow line had peeled in long strips. Beneath it, someone had scratched fresh marks into the concrete: four parallel cuts, each no longer than a finger. They began at the yellow line. They ended at Vetch’s heel. “Eva.” Eva shifted closer. “Know those?” Her glasses slipped down her nose. She pushed them back with one knuckle, then went still. “They’re warding marks,” she whispered. “Or part of them.” “Part?” “They’re upside down.” Bell gave a short laugh that held no humour. “Upside down wards. Great. That clears it up.” Eva looked at him. “A ward pushes something away. Turn it wrong, it does the opposite.” Quinn followed the line of cuts. There were four at the platform edge. Four more hidden beneath Vetch’s coat hem. Another set beneath the bench, where the blood droplets sat in a neat row. Not random. Not a struggle. A shape. She stepped backwards until her calves touched the ticket barrier. From there, the marks connected across the platform in a wide circle, broken only by the corpse at its centre. A circle with its mouth open towards the tracks. Quinn looked at the tunnel. Water kept falling somewhere inside it. The sound had changed. It no longer struck rail or stone. It landed softly, like drops falling into deep water. “Bell,” she called. He turned from the body. “Get everyone off this platform. No panic. No shouting.” His eyes narrowed. “Why?” Quinn pointed at the clean fingers on Vetch’s right hand. “He didn’t die holding the compass. He used it to find the rift.” She pointed at the bloodless crescent near his body. “Then someone opened it inside him.”
created_at"2026-07-09T18:07:18.511Z" 7/9/2026, 6:07:18 PM
model"openai/gpt-5.6-terra-20260709"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency3442
moderation_latency(null)
generation_time40869
tokens_prompt1149
tokens_completion2782
native_tokens_prompt1009
native_tokens_completion2385
native_tokens_completion_images0
native_tokens_reasoning207
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"
usage0.0382975
router(null)
provider_responses
0
endpoint_id"3cc89000-ae34-4dde-9c7d-5ce009c8af0b"
id"resp_0125e3db9a266d84016a4fe3569ed48194948324aeef3bd09b"
is_byokfalse
latency420
model_permaslug"openai/gpt-5.6-terra-20260709"
provider_name"OpenAI"
status200
user_agent"langchainjs-openai/1.0.0 ((node/v24.18.0; linux; x64))"
http_referer(null)
request_id"req-1783620438-kcoHVshWh2vknCnZttpL"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1783620438-ojWMNBruJNea2FRUI1hP"
upstream_id"resp_0125e3db9a266d84016a4fe3569ed48194948324aeef3bd09b"
total_cost0.0382975
cache_discount(null)
upstream_inference_cost0
provider_name"OpenAI"
response_cache_source_id(null)
data_region"global"

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags14
adverbTagCount1
adverbTags
0"Eva knelt carefully [carefully]"
dialogueSentences89
tagDensity0.157
leniency0.315
rawRatio0.071
effectiveRatio0.022
93.92% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1645
totalAiIsmAdverbs2
found
0
adverb"carefully"
count1
1
adverb"softly"
count1
highlights
0"carefully"
1"softly"
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)
75.68% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1645
totalAiIsms8
found
0
word"velvet"
count3
1
word"silence"
count1
2
word"pulse"
count1
3
word"grave"
count1
4
word"vibrated"
count1
5
word"scanned"
count1
highlights
0"velvet"
1"silence"
2"pulse"
3"grave"
4"vibrated"
5"scanned"
100.00% Cliché density
Target: ≤1 cliche(s) per 800-word window
totalCliches1
maxInWindow1
found
0
label"eyes widened/narrowed"
count1
highlights
0"eyes narrowed"
100.00% Emotion telling (show vs. tell)
Target: ≤3% sentences with emotion telling
emotionTells0
narrationSentences138
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount1
narrationSentences138
filterMatches
0"watch"
hedgeMatches
0"seemed to"
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences213
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen30
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1645
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions14
unquotedAttributions0
matches(empty)
16.67% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions71
wordCount1059
uniqueNames10
maxNameDensity2.27
worstName"Quinn"
maxWindowNameDensity4.5
worstWindowName"Eva"
discoveredNames
Camden1
Harlow1
Quinn24
Transport1
London1
Arjun1
Bell20
Vetch8
Eva13
Kowalski1
persons
0"Camden"
1"Harlow"
2"Quinn"
3"Arjun"
4"Bell"
5"Vetch"
6"Eva"
7"Kowalski"
places
0"London"
globalScore0.367
windowScore0.167
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences82
glossingSentenceCount1
matches
0"eye that seemed to follow movement"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1645
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount1
totalSentences213
matches
0"force that the"
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs132
mean12.46
std11.83
cv0.949
sampleLengths
013
139
21
317
471
58
68
736
86
913
105
113
1215
1321
1411
154
1631
179
186
1910
205
213
2211
2350
246
258
2623
275
281
2924
303
316
322
336
343
358
365
3726
384
399
4044
4113
4223
437
4410
455
466
4743
4810
492
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount0
totalSentences138
matches(empty)
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs171
matches(empty)
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount1
semicolonCount0
flaggedSentences1
totalSentences213
ratio0.005
matches
0"—DEN."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount1066
adjectiveStacks0
stackExamples(empty)
adverbCount21
adverbRatio0.019699812382739212
lyAdverbCount4
lyAdverbRatio0.00375234521575985
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences213
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences213
mean7.72
std5.25
cv0.68
sampleLengths
013
122
29
38
41
56
611
79
88
924
1019
1111
128
138
1417
1519
166
178
185
195
203
2112
223
2321
247
254
264
2715
285
2911
305
314
326
3310
345
353
3611
3718
3814
3918
404
412
428
437
449
457
465
471
486
4918
52.74% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats11
diversityRatio0.3474178403755869
totalSentences213
uniqueOpeners74
27.32% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount1
totalSentences122
matches
0"All lay to Vetch’s right."
ratio0.008
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount26
totalSentences122
matches
0"It struck the rails with"
1"It looked pathetic against the"
2"He wore latex gloves and"
3"He lay on his back"
4"He wore a burgundy velvet"
5"She lowered two fingers near"
6"His fingernails bore soot, except"
7"She followed the smear beneath"
8"It travelled three feet across"
9"Her curly red hair had"
10"Her round glasses caught the"
11"Her green eyes sharpened behind"
12"She caught the compass by"
13"It pointed to the tunnel."
14"She leaned closer"
15"His earlier certainty drained from"
16"They began at the yellow"
17"They ended at Vetch’s heel."
18"Her glasses slipped down her"
19"She pushed them back with"
ratio0.213
21.48% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount107
totalSentences122
matches
0"The old station lay below"
1"Detective Harlow Quinn stepped off"
2"Tiles the colour of old"
3"Water dripped from the tunnel"
4"It struck the rails with"
5"Someone had strung red-and-white police"
6"It looked pathetic against the"
7"Stalls crowded the darkness beneath"
8"A woman with a crow’s"
9"Another vendor covered a tray"
10"The market had gone quiet"
11"That silence bothered Quinn more"
12"DC Arjun Bell crouched beside"
13"He wore latex gloves and"
14"Quinn checked the cracked face"
15"Bell rose, broad-shouldered and round-faced,"
16"Bell looked past her towards"
17"Quinn opened her palm."
18"A small disk of polished"
19"The surface held a carved"
ratio0.877
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences122
matches(empty)
ratio0
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences35
technicalSentenceCount0
matches(empty)
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags14
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags8
fancyCount3
fancyTags
0"Eva muttered (mutter)"
1"Bell noted (note)"
2"she whispered (whisper)"
dialogueSentences89
tagDensity0.09
leniency0.18
rawRatio0.375
effectiveRatio0.067
86.2603%