Run: 2026-09-03-01M1KCDAJYVE5ME4K38REC0TJR

Run Details

Duration:
1m 7s
Cost:
$0.001594
Provider:
Reka

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 tunnel smelled of rust and damp stone, the kind of cold that settled into bone and stayed there. Detective Harlow Quinn ducked under the police tape and let her eyes adjust to the gloom. The abandoned Tube station beneath Camden had been sealed off for decades, but somebody had found a way in. Somebody always did. The body lay at the foot of a collapsed escalator, a man in his forties, sprawled on his back with his arms thrown wide. His coat was expensive. His shoes were polished. That was the first wrong thing. “Uniform found him at 4:15,” said a voice behind her. Sergeant Bell, a stout man with a notebook perpetually in his hand, stepped up beside her. “Looks like he fell from the top of the escalator. Cracked his skull on the landing.” Quinn didn’t answer. She crouched, careful to keep her weight off the debris-strewn floor. The man’s face was intact, pale, almost peaceful. No blood pooling beneath his head. No blood at all, actually. “Where’s the wound?” she asked. Bell flipped a page in his notebook. “Pathologist said internal bleeding. Must have landed wrong.” “Landing wrong doesn’t crack a skull without leaving a mark.” Quinn traced the line of the man’s jaw with her eyes. “His neck’s at the wrong angle for a fall. He landed on his back, but his head is turned like he was looking over his shoulder when he hit.” Bell shifted his weight. “You’re reading a lot into a dead man’s posture.” “That’s the job.” Quinn stood and swept her torch beam across the tunnel walls. Graffiti layered over faded tile, decades of it. But near the base of the escalator, something else caught the light. A symbol, clean and sharp, cut into the tile with deliberate precision. A circle with interlocking lines, like a compass rose folded in on itself. She pulled out her phone to photograph it, then stopped. A glint of metal near the victim’s outstretched hand. She crouched again, angling the torch. A small brass compass lay on the dusty floor, its casing streaked with verdigris. Quinn didn’t touch it. She studied it from where she knelt. The face was etched with the same symbol as the wall, and the needle was moving. Not settling, not pointing north. It spun in slow, lazy circles, like a dog circling before it lies down. “Bell,” she said quietly. “Did you touch this?” “Didn’t touch anything.” “Good.” She stood and stepped back. “Where’s the entry point?” “Service door off the north stairwell. Lock was picked. Clean job.” “And the victim’s ID?” “Nothing on him. No wallet, no phone, no keys.” Bell’s pen hovered over the page. “Robbery gone wrong, maybe. He came down here to meet someone, they took his things and shoved him down the escalator.” Quinn turned in a slow circle, taking in the tunnel. The dust on the floor was thick, undisturbed except for the victim’s body and the footprints of the first responders. She followed the beam of her torch to the top of the escalator. The metal steps were caked with grime, but she could see the faint smear of a shoe print near the top landing. One print. Not two. “If he was shoved, there’d be a second set of prints,” she said. “A scuffle, a push, someone bracing their weight. There’s nothing. He walked up there alone.” “So he jumped,” Bell said. “Suicide.” “Then why is his head turned like that?” Quinn walked toward the escalator, careful to keep to the edges. “And why is there no dust on his shoes?” Bell frowned. “What?” “His shoes. They’re polished. Clean. I walked through that service door and my boots are covered in grime within ten seconds. The victim walked down a tunnel that hasn’t been used in thirty years, and his shoes are immaculate. So either he floated in, or he was carried.” Bell was quiet for a moment. “Carried in and dumped?” “That’s the theory.” Quinn reached the top of the escalator and crouched. The single shoe print was there, clear in the dust. A man’s dress shoe, size ten or eleven, with a distinctive tread pattern. She could see the victim’s shoes from where she stood. Same size. Same pattern. “He walked up here,” she said slowly. “He stood at the top of the escalator. And then he fell backwards, down the stairs, landing on his back at the bottom. No defensive wounds. No signs of a struggle. He just… fell.” “Or he was pushed by someone who didn’t leave prints,” Bell offered. “There’s no second set of prints anywhere in this tunnel.” Quinn stood and walked back down, her torch sweeping the floor. “Whoever brought him here was careful. They cleaned up after themselves. But they missed the compass.” She stopped beside the body again and looked at the compass. The needle had stopped spinning. It pointed, steady and unwavering, toward the wall with the symbol. “That compass is pointing at something,” she said. “It’s pointing at a wall,” Bell said. Quinn didn’t answer. She walked to the wall and ran her gloved fingers over the symbol cut into the tile. It was fresh. The edges were sharp, no weathering, no dust in the grooves. It had been cut within the last few hours. “This wasn’t here before the body was dumped,” she said. “This was made after.” “How can you tell?” “Because the dust on the floor is undisturbed, but the dust in these grooves is gone. Whoever cut this symbol did it after the dust settled. They were here, in this tunnel, after the victim was placed at the bottom of the escalator.” She looked back at the body. “They staged this. They brought him here, laid him out, cut the symbol, and left the compass as a calling card.” Bell’s pen stopped moving. “That’s a hell of a leap.” “It’s not a leap. It’s the only explanation that fits every piece of evidence.” Quinn pulled out her phone and photographed the symbol, then the compass, then the body from three angles. “The victim wasn’t killed here. There’s no blood, no impact marks, no signs of a struggle. He was killed somewhere else, dressed, and brought here. His shoes are clean because he never walked a step in this tunnel. The single print at the top of the escalator was made deliberately, to make it look like he walked up there. But whoever made it didn’t account for the dust.” “So what are you saying?” Bell asked. “This is some kind of ritual?” Quinn looked at the compass again. The needle was still pointing at the wall, steady as a heartbeat. She didn’t know what the symbol meant. She didn’t know why a brass compass would spin in circles and then lock onto a wall like a hunting dog pointing at game. But she knew, with the certainty of eighteen years on the force, that this was not a robbery and this was not a suicide. “I’m saying the evidence doesn’t add up,” she said. “And when the evidence doesn’t add up, it means someone is lying. Someone is hiding something. And someone went to a great deal of trouble to make this look like an accident.” She crouched beside the body one last time and looked at the man’s face. His eyes were closed. His expression was calm. No fear, no pain, no surprise. Whatever had happened to him, he hadn’t seen it coming. “Run his face through the system,” she said. “Check missing persons, check the ports, check the airports. Someone like this doesn’t just vanish without a trail.” Bell nodded and turned to go. Quinn stayed where she was, listening to the drip of water somewhere in the dark. The compass needle hadn’t moved. It pointed at the wall like it knew something she didn’t. She pulled out her own notebook and wrote down the symbol, copying it stroke for stroke. Then she put the notebook away and looked at the wall one more time. The tunnel was cold, but she felt a different kind of cold settle into her chest. The kind that came from looking at a puzzle and realizing the pieces didn’t fit because she was missing a whole section of the picture. She turned and followed Bell out of the tunnel, leaving the compass behind. But she knew she’d be back.
created_at"2026-09-03T10:18:10.94Z" 9/3/2026, 10:18:10 AM
model"deepseek/deepseek-v4-flash-20260731"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency2525
moderation_latency(null)
generation_time66843
tokens_prompt1112
tokens_completion2541
native_tokens_prompt1112
native_tokens_completion2230
native_tokens_completion_images(null)
native_tokens_reasoning444
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"stop"
service_tier(null)
usage0.00159412
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.19.0; linux; x64))"
http_referer(null)
request_id"req-1788430690-JdDxy5fnyU1lgznplasq"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1788430690-vwSHeXm6IIeoGQyt0NUF"
upstream_id"5f2cb6160ed148eabbbea5255672438d"
provider_responses
0
endpoint_id"497727f1-91e7-4775-a469-ccdd96e0f0d8"
id"5f2cb6160ed148eabbbea5255672438d"
is_byokfalse
latency2523
model_permaslug"deepseek/deepseek-v4-flash-20260731"
provider_name"Reka"
status200
total_cost0.00159412
cache_discount(null)
upstream_inference_cost0
provider_name"Reka"
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
totalTags21
adverbTagCount2
adverbTags
0"she said quietly [quietly]"
1"she said slowly [slowly]"
dialogueSentences48
tagDensity0.438
leniency0.875
rawRatio0.095
effectiveRatio0.083
92.86% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1401
totalAiIsmAdverbs2
found
0
adverb"slowly"
count1
1
adverb"deliberately"
count1
highlights
0"slowly"
1"deliberately"
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)
71.45% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1401
totalAiIsms8
found
0
word"gloom"
count1
1
word"weight"
count3
2
word"traced"
count1
3
word"glint"
count1
4
word"etched"
count1
5
word"unwavering"
count1
highlights
0"gloom"
1"weight"
2"traced"
3"glint"
4"etched"
5"unwavering"
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
narrationSentences93
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount0
hedgeCount1
narrationSentences93
filterMatches(empty)
hedgeMatches
0"happened to"
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences119
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen68
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1401
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions17
unquotedAttributions0
matches(empty)
50.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions31
wordCount830
uniqueNames7
maxNameDensity1.57
worstName"Quinn"
maxWindowNameDensity3.5
worstWindowName"Bell"
discoveredNames
Harlow1
Quinn13
Tube1
Camden1
Sergeant1
Bell13
Graffiti1
persons
0"Harlow"
1"Quinn"
2"Camden"
3"Sergeant"
4"Bell"
5"Graffiti"
places(empty)
globalScore0.717
windowScore0.5
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences59
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1401
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences119
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs46
mean30.46
std22.36
cv0.734
sampleLengths
057
138
242
333
45
515
650
713
859
925
1060
118
123
1310
1411
154
1636
1769
1828
196
2028
213
2248
2310
2449
2541
2612
2737
2827
298
307
3143
3214
334
3470
3510
36100
3713
3873
3941
4038
4126
4237
4330
4441
4519
93.94% Passive voice overuse
Target: ≤2% passive sentences
passiveCount3
totalSentences93
matches
0"been sealed"
1"was etched"
2"were caked"
67.55% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount3
totalVerbs151
matches
0"was still pointing"
1"was, listening"
2"was missing"
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences119
ratio0
matches(empty)
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount831
adjectiveStacks0
stackExamples(empty)
adverbCount19
adverbRatio0.02286401925391095
lyAdverbCount4
lyAdverbRatio0.0048134777376654635
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences119
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences119
mean11.77
std9.99
cv0.848
sampleLengths
019
116
219
33
424
54
64
76
810
916
1016
113
1211
138
146
155
165
177
188
1921
2029
214
229
2314
248
2512
2612
2713
2810
299
306
3114
324
337
3416
355
3614
374
384
393
406
414
4211
434
4415
4521
4610
4720
4813
4922
59.66% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats9
diversityRatio0.40336134453781514
totalSentences119
uniqueOpeners48
42.74% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount1
totalSentences78
matches
0"Then she put the notebook"
ratio0.013
86.67% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount26
totalSentences78
matches
0"His coat was expensive."
1"His shoes were polished."
2"She crouched, careful to keep"
3"She pulled out her phone"
4"She crouched again, angling the"
5"She studied it from where"
6"It spun in slow, lazy"
7"she said quietly"
8"She stood and stepped back"
9"She followed the beam of"
10"She could see the victim’s"
11"she said slowly"
12"She stopped beside the body"
13"It pointed, steady and unwavering,"
14"She walked to the wall"
15"It was fresh."
16"It had been cut within"
17"She looked back at the"
18"She didn’t know what the"
19"She didn’t know why a"
ratio0.333
17.69% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount69
totalSentences78
matches
0"The tunnel smelled of rust"
1"Detective Harlow Quinn ducked under"
2"The abandoned Tube station beneath"
3"Somebody always did."
4"The body lay at the"
5"His coat was expensive."
6"His shoes were polished."
7"That was the first wrong"
8"Sergeant Bell, a stout man"
9"Quinn didn’t answer."
10"She crouched, careful to keep"
11"The man’s face was intact,"
12"Bell flipped a page in"
13"Quinn traced the line of"
14"Bell shifted his weight."
15"Quinn stood and swept her"
16"Graffiti layered over faded tile,"
17"A symbol, clean and sharp,"
18"A circle with interlocking lines,"
19"She pulled out her phone"
ratio0.885
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences78
matches(empty)
ratio0
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences36
technicalSentenceCount1
matches
0"The kind that came from looking at a puzzle and realizing the pieces didn’t fit because she was missing a whole section of the picture."
77.38% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags21
uselessAdditionCount2
matches
0"Quinn walked, careful to keep to the edges"
1"Quinn stood, her torch sweeping the floor"
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags11
fancyCount0
fancyTags(empty)
dialogueSentences48
tagDensity0.229
leniency0.458
rawRatio0
effectiveRatio0
85.3315%