Run: 2026-03-15-01KKS2SY8PDEA8QYNANXRDZAQN

Run Details

Duration:
17.5s
Cost:
$0.005901
Provider:
Z.AI

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 stairwell smelled of rust and something older. Harlow Quinn clicked her torch on and descended, boots ringing against metal steps that hadn't felt foot traffic in decades. The air grew thicker with each landing, carrying a sweetness beneath the damp that turned her stomach. "Down here, Detective." The voice echoed up from somewhere below. She recognised it—Sergeant Patel from the Borough command, young, eager, still believed the job was about justice. She reached the platform and stopped. The abandoned Tube station stretched in both directions, tiles cracked and stained with decades of water damage. Emergency lighting had been strung up at intervals, casting pale pools that did nothing to touch the darkness between them. A handful of uniformed officers stood in a loose cluster near the north end, looking anywhere but at the centre of their attention. Patel approached, his notebook already open. "Call came in at half three from a maintenance worker doing routine checks on the tunnel seals. Found the body right where you see it." Quinn studied the scene without moving closer. The worn leather watch on her wrist caught the light as she raised her arm to check the time. Four-seventeen. The body lay fifteen feet from the nearest light, positioned at an odd angle against the platform edge. Male, mid-forties by the look of him, dressed in clothes that cost more than her monthly rent. "Robbery?" "That's what we're thinking. Wallet's gone, phone too. Nice watch on him though—" "Wait." Quinn held up a hand. She stepped forward, torch beam sweeping the ground in a careful arc before her feet. The tiles here were different. Cleaner. The grime of decades had been scrubbed away in patches, revealing pale ceramic beneath. "Who set up the lights?" "First responders. We needed to see what we were dealing with." "You moved anything?" "Of course not, Detective. We know procedure." She crouched near the body, keeping her distance from the pooled darkness beneath his head. His eyes were open. That struck her as wrong. Street robberies in London didn't leave victims staring at the ceiling. They left them face-down, or curled, or hidden. This man had been arranged. "Patel, come here. Look at his hands." The sergeant squatted beside her, squinting. "What about them?" "No defensive wounds. None. You see a man getting jumped in a dark tunnel, what's his first instinct?" "He fights back." "He fights back. But this man's knuckles are clean. His palms are clean. His fingernails haven't got a speck of skin or blood under them. Either our robberies have started hiring professionals who subdue victims without leaving a mark, or this man never raised a finger to defend himself." Patel flipped back a page in his notebook. "Could be he was unconscious before the robbery. Hit from behind, maybe." "Maybe. Show me the back of his head." She watched Patel circle the body, watched his face change when he saw what she'd already guessed at. "There's no wound. No blood at the back of the skull at all." "Which means the blood we're seeing came from somewhere else." Quinn stood, scanning the platform again. "Where's the entry point? Maintenance worker came from where?" "Service ladder at the south end. There's a locked gate at street level, but he had keys." "And the gate showed signs of forced entry?" "No, Detective. He used his key. Said it was already unlocked when he got here, but that happens sometimes with old locks." Quinn walked the perimeter of the crime scene, her torch picking out details the emergency lights couldn't reach. Scuff marks on the tiles—too many, too patterned. This wasn't a location people stumbled into. The foot traffic here had been deliberate, repeated. She stopped at the wall near the tunnel mouth. Something had been scratched into the tile, recently enough that the marks still showed white against the stained ceramic. A symbol. She didn't recognise it, but she'd seen similar markings before, three years ago, in the case file that still sat in her desk drawer. "Patel, did you notice anything unusual about the victim's pockets when you checked them?" "Just the missing wallet and phone. Why?" "Check again. Inside lining, hidden compartments. Men who wear suits like that don't carry their valuables where anyone can find them." While Patel worked, Quinn pulled out her phone and took three photographs of the symbol. The flash illuminated something she'd missed—a second mark, lower down, partially hidden by a fallen chunk of plaster. This one was different. A compass rose, but not any standard design she recognised. The needle pointed down. "Detective?" She turned. Patel held something up in his gloved hand. A small brass object, no bigger than a pocket watch. "Found it sewn into the lining of his jacket. Some kind of compass, but the markings are... odd." Quinn crossed the platform in four strides and took the object from him. The casing had a patina of verdigris that spoke of age, but the face was etched with symbols that looked freshly cut. She turned it in her hand, watching the needle spin and settle. It wasn't pointing north. "What is that thing?" "I don't know yet." She slipped it into her evidence bag. "But our victim wasn't here by accident, and this wasn't a robbery. Someone wanted him dead in this exact spot, and they took his wallet and phone to make it look like something it wasn't." Patel's expression shifted from confusion to something harder. "You're saying this was staged?" "I'm saying the evidence is lying to us, and we need to find out why." Quinn looked back at the symbol on the wall. "Get me everything you can find on the victim. Bank records, phone records, known associates. And Patel—" "Yes, Detective?" "Find out who else has keys to that gate."
created_at"2026-03-15T15:45:59.584Z" 3/15/2026, 3:45:59 PM
model"z-ai/glm-5-turbo-20260315"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency1555
moderation_latency(null)
generation_time17357
tokens_prompt1149
tokens_completion2006
native_tokens_prompt1020
native_tokens_completion1655
native_tokens_completion_images(null)
native_tokens_reasoning412
native_tokens_cached487
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"
usage0.005901184
router(null)
provider_responses
0
endpoint_id"9ce3b132-3a17-4fea-8092-0e8e519ed32b"
id"202603152346006a2ef5419fdc40c9"
is_byokfalse
latency1555
model_permaslug"z-ai/glm-5-turbo-20260315"
provider_name"Z.AI"
status200
user_agent"langchainjs-openai/1.0.0 ((node/v24.14.0; linux; x64))"
http_referer(null)
api_type"completions"
id"gen-1773589559-05Lv600f3jK9bYrY85cD"
upstream_id"202603152346006a2ef5419fdc40c9"
total_cost0.005901184
cache_discount0.00046752
upstream_inference_cost0
provider_name"Z.AI"

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags3
adverbTagCount0
adverbTags(empty)
dialogueSentences35
tagDensity0.086
leniency0.171
rawRatio0
effectiveRatio0
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount973
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)
74.31% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount973
totalAiIsms5
found
0
word"stomach"
count1
1
word"echoed"
count1
2
word"scanning"
count1
3
word"standard"
count1
4
word"etched"
count1
highlights
0"stomach"
1"echoed"
2"scanning"
3"standard"
4"etched"
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
narrationSentences53
matches(empty)
88.95% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount2
hedgeCount0
narrationSentences53
filterMatches
0"watch"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences85
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
maxSentenceWordsSeen49
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords970
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions3
unquotedAttributions0
matches(empty)
79.82% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions19
wordCount570
uniqueNames6
maxNameDensity1.4
worstName"Quinn"
maxWindowNameDensity2
worstWindowName"Quinn"
discoveredNames
Quinn8
Sergeant1
Patel7
Borough1
Tube1
London1
persons
0"Quinn"
1"Sergeant"
2"Patel"
places
0"Borough"
1"London"
globalScore0.798
windowScore1
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences41
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount970
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences85
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs48
mean20.21
std18.01
cv0.891
sampleLengths
045
13
224
36
460
56
625
762
81
913
101
1140
125
1311
143
157
1648
177
186
193
2018
213
2249
2320
248
2518
2613
2725
2817
298
3022
3141
3254
3314
347
3521
3651
371
3820
3918
4047
414
424
4346
4413
4541
462
479
78.78% Passive voice overuse
Target: ≤2% passive sentences
passiveCount4
totalSentences53
matches
0"been scrubbed"
1"been arranged"
2"been scratched"
3"was etched"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount1
totalVerbs103
matches
0"wasn't pointing"
42.02% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount3
semicolonCount0
flaggedSentences3
totalSentences85
ratio0.035
matches
0"She recognised it—Sergeant Patel from the Borough command, young, eager, still believed the job was about justice."
1"Scuff marks on the tiles—too many, too patterned."
2"The flash illuminated something she'd missed—a second mark, lower down, partially hidden by a fallen chunk of plaster."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount576
adjectiveStacks0
stackExamples(empty)
adverbCount18
adverbRatio0.03125
lyAdverbCount4
lyAdverbRatio0.006944444444444444
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences85
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences85
mean11.41
std8.16
cv0.715
sampleLengths
08
120
217
33
47
517
66
717
820
923
106
1125
127
1319
141
1518
1617
171
1813
191
205
2115
225
231
2414
255
2611
273
287
2915
304
315
3211
338
345
357
366
373
3818
393
4049
418
4212
438
4418
4513
4616
479
4817
498
87.84% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats2
diversityRatio0.5411764705882353
totalSentences85
uniqueOpeners46
0.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount0
totalSentences49
matches(empty)
ratio0
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount12
totalSentences49
matches
0"She recognised it—Sergeant Patel from"
1"She reached the platform and"
2"She stepped forward, torch beam"
3"She crouched near the body,"
4"His eyes were open."
5"They left them face-down, or"
6"She watched Patel circle the"
7"She stopped at the wall"
8"She didn't recognise it, but"
9"She turned it in her"
10"It wasn't pointing north."
11"She slipped it into her"
ratio0.245
0.00% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount47
totalSentences49
matches
0"The stairwell smelled of rust"
1"Harlow Quinn clicked her torch"
2"The air grew thicker with"
3"The voice echoed up from"
4"She recognised it—Sergeant Patel from"
5"She reached the platform and"
6"The abandoned Tube station stretched"
7"Emergency lighting had been strung"
8"A handful of uniformed officers"
9"Patel approached, his notebook already"
10"Quinn studied the scene without"
11"The worn leather watch on"
12"The body lay fifteen feet"
13"Quinn held up a hand."
14"She stepped forward, torch beam"
15"The tiles here were different."
16"The grime of decades had"
17"She crouched near the body,"
18"His eyes were open."
19"That struck her as wrong."
ratio0.959
100.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount1
totalSentences49
matches
0"While Patel worked, Quinn pulled"
ratio0.02
53.57% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences24
technicalSentenceCount3
matches
0"The air grew thicker with each landing, carrying a sweetness beneath the damp that turned her stomach."
1"Emergency lighting had been strung up at intervals, casting pale pools that did nothing to touch the darkness between them."
2"Male, mid-forties by the look of him, dressed in clothes that cost more than her monthly rent."
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags3
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags0
86.1764%