Run: 2026-04-24-01KQ07XADMNNRJ4R3FH8T6JNY7

Run Details

Duration:
43.4s
Cost:
$0.001178
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="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
Rain lashed against Detective Harlow Quinn's face as she sprinted down the narrow Soho alleyway. The thunderous footsteps of her quarry echoed off the brick walls, barely audible over the drumming rain. Her lungs burned, but years of military discipline kept her pace steady, each stride measured and efficient. "Stop! Metropolitan Police!" Harlow shouted, her voice cutting through the storm. The figure in the dark hoodie didn't even glance back. Instead, they leaped over a pile of rubbish bins, landing with surprising agility on the wet cobblestones below. Harlow followed without hesitation, pushing her body through the air. Her shoulder slammed against the metal bin as she landed, sending a jolt up her arm, but she maintained her balance. The suspect was faster than expected, already cutting through the next alley, which opened onto a busier street. Neon signs from nearby bars and clubs cast a kaleidoscope of colors on the rain-slicked pavement. Harlow shielded her eyes with one hand, her gaze locked on the dark figure weaving through the sparse late-night crowd. They were heading toward the Camden area now, the streets growing progressively darker and seedier. The distinctive green neon sign of The Raven's Nest flashed in the distance, but they weren't heading there. Instead, they turned down an alley that Harlow knew led to the old abandoned Tube station. Heart pounding against her ribs, Harlow pushed harder. The suspect suddenly vanished through a barely-visible doorway beside a pawn shop. Harlow skidded to a halt, peering into the darkness. The doorway was recessed, almost hidden in the brickwork. A faint green glow emanated from within. She recognized the sign from the files - the bone token requirement for entry. This was The Veil Market, London's supernatural black market. Her training screamed caution. Her instincts screamed pursuit. The rain intensified as she stood there, water dripping from her closely cropped salt-and-pepper hair into her eyes. She wiped her face with the back of her hand, the worn leather strap of her watch slapping against her wrist. Three years ago, she'd chased a suspect into a similar situation. That chase had ended with her partner, DS Morris, disappearing under circumstances she still couldn't explain. There were whispers then, too, about the supernatural, about forces beyond human understanding. She'd dismissed them as grief-induced fantasies until now. Taking a deep breath, she stepped closer to the entrance. The air grew cooler, the smell of wet pavement giving way to something else - ozone, metal, and a faint coppery scent. From within, she could hear murmured voices and the clink of what sounded like glass bottles. Her sharp jaw clenched. This was where the answers were. This was where the people who might know what really happened to Morris were likely to be found. She reached into her jacket pocket, her fingers closing around the small, carved bone token she'd taken from a suspect earlier that day - evidence she'd kept for herself. Something told her she'd need it. The figure reappeared in the doorway, illuminated by the green glow within. They weren't looking at her, instead scanning the street as if making sure no one had followed. Harlow flattened herself against the cold brick wall, holding her breath. After a moment, the figure turned back into the darkness. The decision took approximately three seconds. Eighteen years of police work had taught her when to push, when to hold back. This was neither. This was unknown territory, but it was territory she had to enter. Morris's fate depended on it. She straightened her soaked coat, adjusted her service weapon beneath her arm, and stepped forward. The bone token felt heavy in her palm as she approached the doorway. The green neon sign above flickered, casting dancing shadows on her determined face. "Better have answers," she muttered to herself, stepping into the darkness beyond.
created_at"2026-04-24T17:16:59.709Z" 4/24/2026, 5:16:59 PM
model"z-ai/glm-4.5-air"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency2532
moderation_latency(null)
generation_time43359
tokens_prompt1140
tokens_completion1501
native_tokens_prompt991
native_tokens_completion1208
native_tokens_completion_images(null)
native_tokens_reasoning408
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"
usage0.00117762
router(null)
provider_responses
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endpoint_id"f7dc79ca-bbbd-41a1-8eef-616d981ff1cb"
id"019dc07eb5f73b66f3f4f9c4c2703b56"
is_byokfalse
latency2518
model_permaslug"z-ai/glm-4.5-air"
provider_name"SiliconFlow"
status200
user_agent"langchainjs-openai/1.0.0 ((node/v24.14.1; linux; x64))"
http_referer(null)
request_id"req-1777051019-xWR6mHQHTsAtOQ3QSEn7"
session_id(null)
api_type"completions"
id"gen-1777051019-Z83w94BP8EjIj2SD0yfv"
upstream_id"019dc07eb5f73b66f3f4f9c4c2703b56"
total_cost0.00117762
cache_discount(null)
upstream_inference_cost0
provider_name"SiliconFlow"
response_cache_source_id(null)

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags2
adverbTagCount0
adverbTags(empty)
dialogueSentences2
tagDensity1
leniency1
rawRatio0
effectiveRatio0
84.30% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount637
totalAiIsmAdverbs2
found
0
adverb"suddenly"
count1
1
adverb"really"
count1
highlights
0"suddenly"
1"really"
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)
5.81% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount637
totalAiIsms12
found
0
word"footsteps"
count1
1
word"echoed"
count1
2
word"measured"
count1
3
word"efficient"
count1
4
word"kaleidoscope"
count1
5
word"pounding"
count1
6
word"pawn"
count1
7
word"jaw clenched"
count1
8
word"scanning"
count1
9
word"flickered"
count1
10
word"dancing"
count1
11
word"determined"
count1
highlights
0"footsteps"
1"echoed"
2"measured"
3"efficient"
4"kaleidoscope"
5"pounding"
6"pawn"
7"jaw clenched"
8"scanning"
9"flickered"
10"dancing"
11"determined"
100.00% Cliché density
Target: ≤1 cliche(s) per 800-word window
totalCliches1
maxInWindow1
found
0
label"jaw/fists clenched"
count1
highlights
0"jaw clenched"
100.00% Emotion telling (show vs. tell)
Target: ≤3% sentences with emotion telling
emotionTells0
narrationSentences50
matches(empty)
85.71% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount1
narrationSentences50
filterMatches
0"watch"
hedgeMatches
0"happened to"
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences50
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen28
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords640
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions4
unquotedAttributions0
matches(empty)
66.67% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions21
wordCount634
uniqueNames12
maxNameDensity1.26
worstName"Harlow"
maxWindowNameDensity3
worstWindowName"Harlow"
discoveredNames
Detective1
Harlow8
Quinn1
Soho1
Camden1
Raven1
Nest1
Tube1
Veil1
Market1
London1
Morris3
persons
0"Harlow"
1"Quinn"
2"Raven"
3"Nest"
4"Veil"
5"Morris"
places
0"Soho"
1"Camden"
2"London"
globalScore0.869
windowScore0.667
38.89% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences45
glossingSentenceCount2
matches
0"sounded like glass bottles"
1"as if making sure no one had followed"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount640
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences50
matches(empty)
74.03% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs14
mean45.71
std18.7
cv0.409
sampleLengths
049
111
259
354
449
545
631
787
848
963
1050
1141
1241
1312
98.25% Passive voice overuse
Target: ≤2% passive sentences
passiveCount1
totalSentences50
matches
0"was recessed"
11.32% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount3
totalVerbs106
matches
0"were heading"
1"weren't heading"
2"weren't looking"
0.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount3
semicolonCount0
flaggedSentences3
totalSentences50
ratio0.06
matches
0"She recognized the sign from the files - the bone token requirement for entry."
1"The air grew cooler, the smell of wet pavement giving way to something else - ozone, metal, and a faint coppery scent."
2"She reached into her jacket pocket, her fingers closing around the small, carved bone token she'd taken from a suspect earlier that day - evidence she'd kept for herself."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount637
adjectiveStacks0
stackExamples(empty)
adverbCount17
adverbRatio0.026687598116169546
lyAdverbCount8
lyAdverbRatio0.012558869701726845
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences50
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences50
mean12.8
std5.44
cv0.425
sampleLengths
015
117
217
311
410
518
610
721
818
916
1020
1115
1218
1316
148
1512
169
179
187
1914
209
214
224
2318
2421
2511
2616
2713
288
2910
3022
3116
324
336
3418
3529
366
3712
3817
3911
4010
416
4215
433
4412
455
4615
4713
4813
4912
65.33% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats4
diversityRatio0.44
totalSentences50
uniqueOpeners22
100.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount2
totalSentences50
matches
0"Instead, they leaped over a"
1"Instead, they turned down an"
ratio0.04
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount13
totalSentences50
matches
0"Her lungs burned, but years"
1"Her shoulder slammed against the"
2"They were heading toward the"
3"She recognized the sign from"
4"Her training screamed caution."
5"Her instincts screamed pursuit."
6"She wiped her face with"
7"She'd dismissed them as grief-induced"
8"Her sharp jaw clenched."
9"She reached into her jacket"
10"They weren't looking at her,"
11"She straightened her soaked coat,"
12"she muttered to herself, stepping"
ratio0.26
40.00% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount42
totalSentences50
matches
0"Rain lashed against Detective Harlow"
1"The thunderous footsteps of her"
2"Her lungs burned, but years"
3"Harlow shouted, her voice cutting"
4"The figure in the dark"
5"Harlow followed without hesitation, pushing"
6"Her shoulder slammed against the"
7"The suspect was faster than"
8"Neon signs from nearby bars"
9"Harlow shielded her eyes with"
10"They were heading toward the"
11"The distinctive green neon sign"
12"Heart pounding against her ribs,"
13"The suspect suddenly vanished through"
14"Harlow skidded to a halt,"
15"The doorway was recessed, almost"
16"A faint green glow emanated"
17"She recognized the sign from"
18"This was The Veil Market,"
19"Her training screamed caution."
ratio0.84
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences50
matches(empty)
ratio0
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences34
technicalSentenceCount1
matches
0"The suspect was faster than expected, already cutting through the next alley, which opened onto a busier street."
0.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags2
uselessAdditionCount1
matches
0"Harlow shouted, her voice cutting through the storm"
0.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags2
fancyCount2
fancyTags
0"Harlow shouted (shout)"
1"she muttered (mutter)"
dialogueSentences2
tagDensity1
leniency1
rawRatio1
effectiveRatio1
72.3437%