Run: 2026-09-02-01M1H5JZJDRNTJ75W2KWTJ5BKM

Run Details

Duration:
56.6s
Cost:
$0.000376
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="4417" name="Tomás Herrera" aliases="Tommy, Tomás, Herrera" pronouns="he/him" species="Human" storyRole="Support"> <eyeColor>warm brown</eyeColor> <hair>short curly dark brown</hair> <height>5'10"</height> <age>29</age> <skinTone>olive skin</skinTone> <scar>scar running along his left forearm from a knife attack</scar> <medallion>Saint Christopher medallion around his neck</medallion> <birthplace>Seville, Spain</birthplace> <description>A former paramedic who provides off-the-books medical care for the clique.</description> <backstory>Born in Seville, Spain. He moved to London to work for the NHS but lost his license after administering unauthorized treatments to supernatural patients.</backstory> </character> <location id="854" name="The Raven's Nest" aliases="the Nest, Raven, Silas' bar" realm="Earth"> <signColor>distinctive green neon sign above the entrance</signColor> <secretRoom>hidden back room accessible through a bookshelf, used for clandestine meetings</secretRoom> <description>A dimly lit bar in Soho, London. The walls are covered with old maps and black-and-white photographs.</description> </location> <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> </codex> Continue the story using the following instructions: <instructions> Write a fully fleshed out scene of at least 1000 words in the thriller genre. A detective is pursuing a suspect through rain-soaked city streets at night. The chase takes them from the street level down into an underground market. The detective must decide whether to follow the suspect into unfamiliar and potentially dangerous territory. 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 rain came down in sheets, turning Camden High Street into a river of neon reflections. Detective Harlow Quinn kept her stride even, her eyes locked on the grey hoodie two figures ahead. Ten years of foot pursuits had taught her one thing above all: never sprint until you're ready to catch. "Stop! Police!" The hoodie flinched. Mistake. Her suspect took the corner at twice the speed she expected, boots skidding across wet pavement, and vanished down the service alley behind the kebab shop. Quinn gave chase now, her leather jacket heavy with rainwater, her cropped hair plastered to her scalp. The alley swallowed her whole—brick walls close enough to touch, a single caged bulb buzzing overhead. She could hear him, the slap of shoes on concrete, the ragged pull of his breath. "Oi, mate, let's not make this harder than it needs to be!" She closed the gap as he hit a rusted gate. He vaulted it. She followed, palms burning on the wet metal, landing on gravel on the other side with a grunt. The alley opened onto a set of stairs leading down—old Tube architecture, the kind of derelict entrance the council had board up a decade ago. Except the boards were gone. And the warning paint had been peeled away to reveal a doorway that looked scrubbed clean. The suspect hesitated at the top of the steps. "Last chance." Quinn unclipped her cuffs with one hand, kept the other free. "You know how many times I've played this scene? It always ends with you in the back of a van." He turned, just enough for her to catch the white flash of his face. Young. Early twenties. Terrified. "You don't understand," he said. "He'll kill me for leading you down. He'll kill me either way." "Who will?" Instead of answering, the kid bolted down the stairs. Quinn reached the landing in four strides and stopped. The passage beyond opened into a vaulted chamber lit by sodium lamps strung along iron beams. Market stalls lined both sides of a disused platform. Hundreds of stalls. And none of them were selling anything she recognized. A woman with eyes like opals was haggling over glass vials of something that glowed faintly blue. A man three stalls down wore a suit of mended chainmail under a rain coat, browsing a rack of what looked like dried bat wings. At the far end of the platform, a child with too many fingers was handing change to a customer whose face she couldn't quite focus on. Quinn's hand drifted to the radio on her shoulder. Static. Only static. "Hello, Detective." She spun. The kid was gone. In his place stood a tall man in a charcoal coat, silver hair combed back, a bone-white coin turning between his fingers. He smiled like a knife. "First time at the Veil Market. I can always tell." "Metropolitan Police." She raised her badge. "I'm pursuing a suspect who came through this entrance." "He came through. You need a token." He flipped the bone coin in the air. Caught it. "Nobody gets in without one. Nobody. The wardens on the platform see yours and let you pass. They see yours missing, well." He spread his hands. Quinn's grip tightened on her badge. "Then how did he—" "He had one. Bought it three weeks ago for a favour I won't describe in mixed company." The silver-haired man pocketed the coin. "You can walk back up those stairs and forget what you saw. Everyone does. It's the sensible option." "And the other option?" He pointed across the platform, toward a stall hung with dried herbs and a sign reading FORTUNES TOLD, LIES SOLD. An old woman behind it was watching them with interest. "You find someone willing to part with a token, trade something worth having, and follow that boy to wherever he's going. Assuming the wardens don't take a liking to your bones first." The word BONES hung between them longer than it should have. Quinn scanned the platform. The suspect's grey hoodie was already a hundred metres away, threading between stalls, heading for a black archway at the far end marked with a chalk sigil. If she lost him now— She thought of Morris. Three years. Case file still open. Still a hole where answers should be. A market for things the city didn't want to know about. A boy who'd said he will kill me like the name meant something. Somewhere in here, maybe, were answers of her own. "How much for a token?" she asked. The silver-haired man laughed, and the sound rolled through the vaults like distant thunder. "Straight to it. I like that." He fished in his coat and produced a second coin, holding it up between thumb and forefinger. "One token. One price. Not money. Memory." "Memory." "The Market deals in the rarest stock. Money's common. What's rare is a person willing to give up something true." His eyes caught the sodium light. "Twenty years of service, I'd wager. Some part of that, freely surrendered. A name. A face. A promise. The Market chooses what it takes, and the Market is not kind." Rain dripped down the back of her neck from the stairwell, cold as fingers. Above her, the city hummed, oblivious. Down here, the opal-eyed woman was watching now too, and so was the chainmail man, and half the platform had gone quiet in that particular way a crowd goes quiet when it smells a bargain. The kid slipped through the black archway and was gone. "Detective," the silver-haired man said softly. "You're looking at it like you've already lost something. Most people negotiate. Most people walk away. You're doing neither." He rolled the bone coin across his knuckles. "So. What'll it be?"
created_at"2026-09-02T13:40:27.35Z" 9/2/2026, 1:40:27 PM
model"z-ai/glm-5.3-flash-20260826"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency2121
moderation_latency(null)
generation_time56616
tokens_prompt1104
tokens_completion1414
native_tokens_prompt997
native_tokens_completion1265
native_tokens_completion_images(null)
native_tokens_reasoning18
native_tokens_cached256
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)
usage0.000375665
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.19.0; linux; x64))"
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request_id"req-1788356427-4PFWSOqN0vTV9wKHbRid"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1788356427-3xUoLavowzZXzlNC0XZl"
upstream_id"20260902214027cea4b02d8fc04d7a"
provider_responses
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endpoint_id"8e9fe48b-2f91-41c3-a8a7-e4a93a8c4ff0"
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is_byokfalse
latency2121
model_permaslug"z-ai/glm-5.3-flash-20260826"
provider_name"Z.AI"
status200
total_cost0.000375665
cache_discount0.00003072
upstream_inference_cost0
provider_name"Z.AI"
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
adverbTagCount1
adverbTags
0"haired man said softly [softly]"
dialogueSentences27
tagDensity0.444
leniency0.889
rawRatio0.083
effectiveRatio0.074
94.82% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount965
totalAiIsmAdverbs1
found
0
adverb"softly"
count1
highlights
0"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)
94.82% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount965
totalAiIsms1
found
0
word"scanned"
count1
highlights
0"scanned"
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
narrationSentences67
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount0
hedgeCount0
narrationSentences67
filterMatches(empty)
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences82
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen36
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords963
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions6
unquotedAttributions0
matches(empty)
99.28% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions15
wordCount690
uniqueNames9
maxNameDensity1.01
worstName"Quinn"
maxWindowNameDensity1.5
worstWindowName"Quinn"
discoveredNames
Camden1
High1
Street1
Harlow1
Quinn7
Tube1
Caught1
Morris1
Rain1
persons
0"Harlow"
1"Quinn"
2"Morris"
3"Rain"
places
0"Camden"
1"High"
2"Street"
globalScore0.993
windowScore1
33.72% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences43
glossingSentenceCount2
matches
0"looked like dried bat wings"
1"quite focus on"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount963
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences82
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs36
mean26.75
std19.45
cv0.727
sampleLengths
052
12
230
349
443
546
69
733
818
917
102
119
1237
139
1468
1512
162
1733
1810
1915
2043
2110
2241
234
2462
2511
2636
2717
2833
297
3044
311
3256
3355
3410
3537
84.32% Passive voice overuse
Target: ≤2% passive sentences
passiveCount4
totalSentences67
matches
0"were gone"
1"been peeled"
2"was gone"
3"was gone"
0.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount5
totalVerbs113
matches
0"were selling"
1"was haggling"
2"was handing"
3"was watching"
4"was watching"
38.33% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount3
semicolonCount0
flaggedSentences3
totalSentences82
ratio0.037
matches
0"The alley swallowed her whole—brick walls close enough to touch, a single caged bulb buzzing overhead."
1"The alley opened onto a set of stairs leading down—old Tube architecture, the kind of derelict entrance the council had board up a decade ago."
2"If she lost him now—"
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount697
adjectiveStacks0
stackExamples(empty)
adverbCount22
adverbRatio0.03156384505021521
lyAdverbCount4
lyAdverbRatio0.005738880918220947
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences82
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences82
mean11.74
std8.76
cv0.746
sampleLengths
016
117
219
32
43
51
626
717
816
916
1022
113
1218
1325
145
1516
169
1713
1820
1914
201
212
221
235
2412
252
269
279
2816
299
303
319
3217
3325
3426
359
361
372
382
392
404
4122
425
4310
446
459
4615
472
4826
496
95.12% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats2
diversityRatio0.5853658536585366
totalSentences82
uniqueOpeners48
100.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount2
totalSentences56
matches
0"Instead of answering, the kid"
1"Somewhere in here, maybe, were"
ratio0.036
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount15
totalSentences56
matches
0"Her suspect took the corner"
1"She could hear him, the"
2"She closed the gap as"
3"He vaulted it."
4"She followed, palms burning on"
5"He turned, just enough for"
6"He smiled like a knife."
7"She raised her badge"
8"He flipped the bone coin"
9"He spread his hands"
10"He pointed across the platform,"
11"She thought of Morris."
12"He fished in his coat"
13"His eyes caught the sodium"
14"He rolled the bone coin"
ratio0.268
76.07% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount43
totalSentences56
matches
0"The rain came down in"
1"Detective Harlow Quinn kept her"
2"The hoodie flinched."
3"Her suspect took the corner"
4"Quinn gave chase now, her"
5"The alley swallowed her whole—brick"
6"She could hear him, the"
7"She closed the gap as"
8"He vaulted it."
9"She followed, palms burning on"
10"The alley opened onto a"
11"The suspect hesitated at the"
12"Quinn unclipped her cuffs with"
13"He turned, just enough for"
14"Quinn reached the landing in"
15"The passage beyond opened into"
16"Hundreds of stalls."
17"A woman with eyes like"
18"A man three stalls down"
19"Quinn's hand drifted to the"
ratio0.768
89.29% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount1
totalSentences56
matches
0"If she lost him now—"
ratio0.018
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences26
technicalSentenceCount1
matches
0"A woman with eyes like opals was haggling over glass vials of something that glowed faintly blue."
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
totalTags3
fancyCount1
fancyTags
0"haired man said softly (hair say)"
dialogueSentences27
tagDensity0.111
leniency0.222
rawRatio0.333
effectiveRatio0.074
90.1918%