Run: 2026-02-19-01KHT0K43MRWVAK40ABTJWJWW5

Run Details

Duration:
51.9s
Cost:
$0.007324
Provider:
SiliconFlow

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 air in the abandoned Tube station was thick and cold, a damp weight that settled deep in the bones. It smelled of wet concrete, ozone, and something else. Something faintly acrid, like burnt sugar. Detective Harlow Quinn’s boots crunched on grit as she descended the final set of stairs from the street-level access point. The beam of her torch cut a sharp, white path through the oppressive dark, scattering across curved tile walls slick with condensation. A uniformed constable nodded at her from the bottom of the steps, his face pale in the stark light. “Down here, Ma’am. Detective Miller’s already with the… witness.” Quinn raised an eyebrow. A witness? In a place like this? She moved past him, her strides long and measured, echoing in the cavernous space. The tracks had been ripped up long ago, leaving a wide, dusty trench running down the centre of the platform. On the far side, near the mouth of a pitch-black tunnel, a small pool of light illuminated the scene. DS Miller, a young detective with more enthusiasm than sense, was crouched over a shape on the ground. Standing a few feet away, hugging a worn leather satchel to her chest, was a young woman with a riot of curly red hair and round glasses that magnified wide, green eyes. She looked completely out of place, a splatter of colour in a monochrome world of decay. Quinn stopped a few metres from the body, her gaze sweeping the entire area. No other footprints but theirs in the thick layer of dust. No signs of a struggle. No discarded syringes or bottles. The silence was absolute, broken only by the distant hum of the city above and a faint, rhythmic dripping from somewhere deep in the tunnels. “Miller. Report.” He stood up, brushing dust from the knees of his trousers. “Ma’am. Victim is male, approximately thirty years of age. No ID. Looks like your standard Camden junkie, got his hands on a bad batch and wandered down here to die. Coroner’s on the way.” Quinn’s eyes flickered to the woman. “And her?” “Eva Kowalski. She found him. Says she’s an urban explorer, likes photographing forgotten places. Got a bit of a shock.” Miller gave her a dismissive glance. “She’s pretty shaken up.” Quinn approached the woman, her expression unreadable. “Ms. Kowalski.” The woman flinched, tucking a stray strand of hair behind her ear. A nervous habit. “Detective.” “You were just exploring?” “Yes. I know it’s trespassing, but I… I study these places. The history. I was taking photos and I… I tripped. My torch fell and when I picked it up, I saw him.” Her voice was a low whisper, trembling slightly. Quinn studied her. The satchel looked heavy, full. The woman’s clothes were academic, not practical for urban exploration. A corduroy skirt, a woollen cardigan over a blouse. Her shoes were sensible flats, scuffed but not caked in the grime of the tunnels. “You’re a long way from the usual photo spots,” Quinn said, her tone flat. “I like the quiet ones.” Eva Kowalski adjusted her glasses. “The ones with stories.” Quinn turned back to the body. Miller’s explanation was lazy, a convenient box to tick. But the scene felt… staged. Too clean. She crouched, the worn leather of her watch strap creaking softly. The victim lay on his back, fully clothed in jeans and a hoodie. His eyes were wide open, staring at the arched brick ceiling. But it wasn’t the eyes that held her attention. It was his skin. It was taut, stretched thin over his bones, grey and desiccated like a piece of fruit left in the sun for a week. He looked like a mummy. “Bad batch, you said?” Quinn asked, not looking at Miller. “Yes, Ma’am. Fentanyl analogues, probably. Can cause rapid dehydration.” “Rapid enough to turn a man into a jerky in a matter of hours?” She gestured to the victim’s face. The skin was pulled back from the teeth in a rictus of terror, but there were no tears, no tracks of fluid on the cheeks. Nothing. Miller fell silent. He knelt again, peering closer. “Well. Maybe not that rapid. But it’s not impossible.” Quinn’s gaze fell to the victim’s outstretched hand. The fingers were curled, but not clenched. Beside them, half-hidden in the dust, lay a small object. A compass. It was made of brass, about the size of a pocket watch, with a greenish patina blooming across its casing. She picked it up with a gloved hand. The face was etched with strange, spiralling sigils that meant nothing to her. The needle inside didn’t point North. It spun lazily, then settled, pointing directly at the solid brick wall of the tunnel opposite them. “What do you make of this, Ms. Kowalski?” Quinn held up the compass. “You like stories. This one have a chapter?” Eva took a hesitant step forward, her eyes fixed on the object. “That’s… that’s not for navigation.” “No?” “It’s a Veil Compass. It’s attuned to… energy. It points to weak spots. Doorways.” Miller scoffed. “Doorways? It’s a broken toy, probably dropped by another explorer.” Quinn ignored him. She watched Eva’s face. The fear in her eyes had been replaced by a dawning, academic horror. “What kind of doorways?” Quinn pressed. “The kind between places. The… the Veil. It’s a market down here, isn’t it? Or it was. They move. Full moon.” Eva spoke quickly, her words tumbling over each other. “This man wasn’t killed by a drug. Look at the residue around his mouth.” Quinn leaned in. A fine, crystalline powder dusted the victim’s lips and chin. It wasn’t white like a chemical. It shimmered, almost iridescent in her torchlight. “It’s not a substance, not in the chemical sense,” Eva continued, her voice dropping to a conspiratorial hush. “It’s a byproduct. A parasitic entity latched onto him. It… it fed. Drained him. The crystallisation is the waste.” Miller stood up, shaking his head. “This is ridiculous. A parasitic entity? Ma’am, she’s a crank. We’re dealing with a straightforward overdose.” “Is it?” Quinn’s voice was low and sharp. She stood, slipping the compass into an evidence bag. “Then explain this.” She pointed the torch at the dust around the body. There were no scuff marks. No drag marks. The dust was undisturbed except for the victim’s own outline. “He didn’t fall. He didn’t struggle. He was placed here, Miller. Like a statue in an exhibit.” She looked from the desiccated corpse to the blank brick wall the compass had indicated. Then she looked at Eva Kowalski, who was now pale and trembling, her hand pressed to her mouth. Three years ago, DS Morris had been found in a locked room. The official report said heart failure. But Harlow had seen him. She’d seen the same grey, desiccated skin. The same look of silent, impossible terror on his partner’s face. She hadn’t been able to explain it then. She’d buried it, filed it away as a trauma-induced hallucination. Until now. “Miller, get this scene locked down. I want a full forensic sweep. I want them to test that powder for everything known to man, and when that comes back negative, I want them to test for everything unknown to man.” “Ma’am?” “You heard me. And get Ms. Kowalski a cup of tea. She’s coming with me to the station. We’re not finished with her story.” Quinn sealed the evidence bag with a decisive snap. The needle inside was still pointing at the wall, a silent, screaming accusation against the ordinary world.
created_at"2026-02-19T03:55:09.821Z" 2/19/2026, 3:55:09 AM
model"z-ai/glm-4.6" 4/6/2001, 12:00:00 AM
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency1213
moderation_latency(null)
generation_time51741
tokens_prompt1149
tokens_completion4085
native_tokens_prompt1021
native_tokens_completion3645
native_tokens_completion_images(null)
native_tokens_reasoning1912
native_tokens_cached960
num_media_prompt(null)
num_input_audio_prompt(null)
num_media_completion0
num_search_results(null)
origin"https://ncbench.com/"
is_byokfalse
finish_reason"stop"
native_finish_reason"stop"
usage0.00732369
router(null)
provider_responses
0
endpoint_id"2a87c474-6f6a-457f-8d8c-2afc71fb9fad"
id"019c740993245ba733bf3f6e15e23060"
is_byokfalse
latency1213
model_permaslug"z-ai/glm-4.6" 4/6/2001, 12:00:00 AM
provider_name"SiliconFlow"
status200
api_type"completions"
id"gen-1771473309-3CES3Udoeq7ixUYCCnFZ"
upstream_id"019c740993245ba733bf3f6e15e23060"
total_cost0.00732369
cache_discount(null)
upstream_inference_cost0
provider_name"SiliconFlow"

Evaluation details

Result Evaluator Details Meta Data
85.71% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags12
adverbTagCount2
adverbTags
0"a low whisper trembling slightly [slightly]"
1"Eva spoke quickly [quickly]"
dialogueSentences35
tagDensity0.343
leniency0.686
rawRatio0.167
effectiveRatio0.114
80.24% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1265
totalAiIsmAdverbs5
found
0
adverb"completely"
count1
1
adverb"slightly"
count1
2
adverb"softly"
count1
3
adverb"lazily"
count1
4
adverb"quickly"
count1
highlights
0"completely"
1"slightly"
2"softly"
3"lazily"
4"quickly"
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)
40.71% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1265
totalAiIsms15
found
0
word"weight"
count1
1
word"oppressive"
count1
2
word"stark"
count1
3
word"eyebrow"
count1
4
word"measured"
count1
5
word"echoing"
count1
6
word"silence"
count1
7
word"rhythmic"
count1
8
word"standard"
count1
9
word"flickered"
count1
10
word"unreadable"
count1
11
word"whisper"
count1
12
word"etched"
count1
13
word"crystalline"
count1
14
word"shimmered"
count1
highlights
0"weight"
1"oppressive"
2"stark"
3"eyebrow"
4"measured"
5"echoing"
6"silence"
7"rhythmic"
8"standard"
9"flickered"
10"unreadable"
11"whisper"
12"etched"
13"crystalline"
14"shimmered"
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
filterCount2
hedgeCount0
narrationSentences93
filterMatches
0"watch"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences115
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
maxSentenceWordsSeen41
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1261
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions6
unquotedAttributions0
matches(empty)
59.09% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions36
wordCount880
uniqueNames8
maxNameDensity1.82
worstName"Quinn"
maxWindowNameDensity3
worstWindowName"Quinn"
discoveredNames
Tube1
Harlow2
Quinn16
Miller7
Eva6
Kowalski2
North1
Morris1
persons
0"Harlow"
1"Quinn"
2"Miller"
3"Eva"
4"Kowalski"
5"Morris"
places(empty)
globalScore0.591
windowScore0.667
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences64
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches1
per1kWords0.793
wordCount1261
matches
0"No other footprints but"
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences115
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs40
mean31.53
std25.22
cv0.8
sampleLengths
077
119
29
364
466
560
62
745
88
930
109
1116
124
1341
1442
1514
1614
1798
1810
199
2046
2117
2291
2321
2417
251
2614
2712
2826
2944
3026
3137
3222
3365
3433
3559
362
3740
381
3950
75.08% Passive voice overuse
Target: ≤2% passive sentences
passiveCount8
totalSentences93
matches
0"been ripped"
1"was crouched"
2"was pulled"
3"were curled"
4"was made"
5"was etched"
6"been replaced"
7"been found"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs139
matches(empty)
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences115
ratio0
matches(empty)
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount884
adjectiveStacks0
stackExamples(empty)
adverbCount25
adverbRatio0.02828054298642534
lyAdverbCount10
lyAdverbRatio0.011312217194570135
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences115
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences115
mean10.97
std8.33
cv0.76
sampleLengths
020
19
26
320
422
519
69
74
82
95
1014
1120
1219
1318
1432
1516
1614
1711
185
195
2025
212
2211
2334
246
252
2626
274
287
292
3012
313
321
334
3441
353
365
3710
389
3915
4014
4110
424
436
449
454
461
472
4811
4913
51.59% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats9
diversityRatio0.3565217391304348
totalSentences115
uniqueOpeners41
39.22% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount1
totalSentences85
matches
0"Then she looked at Eva"
ratio0.012
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount25
totalSentences85
matches
0"It smelled of wet concrete,"
1"She moved past him, her"
2"She looked completely out of"
3"He stood up, brushing dust"
4"Her voice was a low"
5"Her shoes were sensible flats,"
6"She crouched, the worn leather"
7"His eyes were wide open,"
8"It was his skin."
9"It was taut, stretched thin"
10"He looked like a mummy."
11"She gestured to the victim’s"
12"He knelt again, peering closer."
13"It was made of brass,"
14"She picked it up with"
15"It spun lazily, then settled,"
16"She watched Eva’s face."
17"It wasn’t white like a"
18"It shimmered, almost iridescent in"
19"She stood, slipping the compass"
ratio0.294
42.35% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount71
totalSentences85
matches
0"The air in the abandoned"
1"It smelled of wet concrete,"
2"Something faintly acrid, like burnt"
3"Detective Harlow Quinn’s boots crunched"
4"The beam of her torch"
5"A uniformed constable nodded at"
6"Quinn raised an eyebrow."
7"She moved past him, her"
8"The tracks had been ripped"
9"DS Miller, a young detective"
10"She looked completely out of"
11"Quinn stopped a few metres"
12"The silence was absolute, broken"
13"He stood up, brushing dust"
14"Quinn’s eyes flickered to the"
15"Miller gave her a dismissive"
16"Quinn approached the woman, her"
17"The woman flinched, tucking a"
18"A nervous habit."
19"Her voice was a low"
ratio0.835
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences85
matches(empty)
ratio0
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences36
technicalSentenceCount1
matches
0"Standing a few feet away, hugging a worn leather satchel to her chest, was a young woman with a riot of curly red hair and round glasses that magnified wide, gr…"
0.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags12
uselessAdditionCount4
matches
0"Quinn said, her tone flat"
1"Quinn asked, not looking at Miller"
2"Eva spoke quickly, her words tumbling over each other"
3"Eva continued, her voice dropping to a conspiratorial hush"
64.29% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags5
fancyCount3
fancyTags
0"Quinn pressed (press)"
1"Eva spoke quickly (speak)"
2"Eva continued (continue)"
dialogueSentences35
tagDensity0.143
leniency0.286
rawRatio0.6
effectiveRatio0.171
81.2761%