Run: 2026-10-08-01M4DW9ECG77NNGD390VN83T7E

Run Details

Duration:
15.1s
Cost:
$0.001266
Provider:
Claude Platform on AWS

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 had been falling since Chalk Farm, thin and mean, and by the time Harlow Quinn reached the canal bridge at Camden Lock it had soaked through her coat collar and found the gap between her shirt buttons. Her watch face fogged on the inside. She wiped the glass with her thumb and kept moving. Ahead, Tomás Herrera vaulted the low railing at the end of the towpath. He moved like a man who knew exactly where his feet would land, which was the first thing that had bothered her about him three weeks ago, when he'd stitched a gash on a bouncer's hand in a Soho back room without asking a single question about how it got there. "Herrera! Stop right there!" He glanced over his shoulder. Rain ran off the short curls plastered to his forehead, and under the sodium lamps she caught the pale line of the scar on his left forearm where his sleeve had ridden up. He didn't stop. He laughed, short and breathless, and kept running. Quinn's shoes hit the wet cobbles of Inverness Street. Market stalls stood shuttered and sagging under tarpaulins, water pooling in the dips of their canvas roofs. Neon from a kebab shop bled red across the puddles. A bottle smashed somewhere behind her and a drunk swore at nobody. "You're making this difficult for yourself, Tomás," she called. Her breath came hard now. Eighteen years of service had given her a decent engine, but the cold had got into her knees. "I'm making it difficult?" His voice bounced off the brickwork. "You came to my flat with a warrant for a man who's been dead for four days." "Then you should have answered the door." "I did answer it. You didn't like the answer." He cut left through a gap between two derelict units, and she lost sight of him for three full seconds. Her heart kicked. She remembered the last time she'd lost sight of someone in the dark, the way DS Morris had turned a corner on Hanbury Street and never turned back out of it. Morris had walked into something that the coroner's report described with words like *unexplained* and *indeterminate*. Quinn had stood over the empty alley afterwards and found nothing but rainwater and a smell like struck matches. She had not slept properly since. She pushed through the gap. Herrera stood at the far end of a service yard, one hand on a rusted gate, staring down at the ground. "Don't," he said. "Just don't come any closer." Quinn stopped ten feet from him. Her hand drifted towards her hip and stayed there. "Step away from the gate." "Look at the stairs, Detective." She looked. Beyond the gate, a flight of iron steps spiralled down into a darkness so complete it seemed to have texture. Someone had painted a faded sigil at the top of the railing: a ring of thin lines, like a skull threaded with wire. Below it, a sign hung crooked on one chain. The lettering had weathered almost away, but she could read the old Underground roundel and, beneath it, two words painted by hand in a careful, unhurried script: *Bone first.* The air rising from below carried damp stone and something sweeter underneath, like incense left too long in a closed room. Somewhere far down, a voice laughed, and then music started, a single warped violin note that stretched and stopped. "That's the Veil Market," Herrera said. "It's under the old Camden Town platforms. It moves every full moon, so tonight it's here, and tomorrow it won't be." He turned, and rain dripped off his chin. "I'm not running from you because I did something wrong. I'm running because the people who ask me to patch them up don't come to the front door of anywhere. And the people who pay me don't like cops asking questions in their building." "Then tell me who's paying you." "I'm telling you there's a bone token in my pocket, and it's the only thing that gets me through that gate. It won't get you through. Not without one of their tokens, and you haven't got one." Quinn stared at the stairs. Her training screamed at her to radio for backup, to wait at the surface with a perimeter and a sergeant. But the radio on her shoulder crackled with nothing but static. The signal had died the moment she'd crossed the lock. Her phone showed one bar, then none. She thought of Morris's last transmission, a half-sentence that had cut off mid-word. She thought of her own name scratched into the report beside the words *no witnesses*. "You know what happened to him," she said. Herrera's jaw tightened. For a second, the easy defiance drained from his face and left something tired and frightened behind. "Yes," he said quietly. "And if you go down there without a token, you'll find out too." Quinn unbuttoned her coat, pulled it aside so the rain couldn't reach her holster, and took a long breath of the damp, sweet air rising from the dark. Then she stepped through the gate and set her foot on the first cold iron stair.
created_at"2026-10-08T13:47:19.839Z" 10/8/2026, 1:47:19 PM
model"anthropic/claude-haiku-5.5-20261007"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency15027
moderation_latency(null)
generation_time15053
tokens_prompt1104
tokens_completion1454
native_tokens_prompt1576
native_tokens_completion2217
native_tokens_completion_images(null)
native_tokens_reasoning597
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"end_turn"
service_tier"default"
usage0.0012661
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.21.0; linux; x64))"
http_referer(null)
request_id"req-1791467239-0fhi3kyIob4Xobue4bii"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1791467239-nUqKcgdnU9U8lZgvdzmg"
upstream_id"msg_011Cfpsdj4hXkaZYBJPDxrRy"
provider_responses
0
endpoint_id"b6cdf493-3a61-441f-a134-e7944fddb980"
id"msg_011Cfpsdj4hXkaZYBJPDxrRy"
is_byokfalse
latency779
model_permaslug"anthropic/claude-haiku-5.5-20261007"
provider_name"Claude Platform on AWS"
status200
total_cost0.0012661
cache_discount(null)
upstream_inference_cost0
provider_name"Claude Platform on AWS"
response_cache_source_id(null)
data_region"global"
workspace_id"97e315e5-d303-487d-83c1-83180e8a13d4"

Evaluation details

Result Evaluator Details Meta Data
88.89% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags7
adverbTagCount1
adverbTags
0"he said quietly [quietly]"
dialogueSentences18
tagDensity0.389
leniency0.778
rawRatio0.143
effectiveRatio0.111
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount865
totalAiIsmAdverbs0
found(empty)
highlights(empty)
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)
100.00% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount865
totalAiIsms0
found(empty)
highlights(empty)
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
narrationSentences50
matches(empty)
85.71% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount1
narrationSentences50
filterMatches
0"watch"
hedgeMatches
0"seemed to"
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences61
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen51
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans4
markdownWords6
totalWords865
ratio0.007
matches
0"unexplained"
1"indeterminate"
2"Bone first."
3"no witnesses"
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions12
unquotedAttributions0
matches(empty)
100.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions25
wordCount669
uniqueNames14
maxNameDensity0.9
worstName"Quinn"
maxWindowNameDensity1
worstWindowName"Quinn"
discoveredNames
Chalk1
Farm1
Harlow1
Quinn6
Camden1
Lock1
Tomás1
Herrera4
Soho1
Inverness1
Street2
Morris3
Hanbury1
Underground1
persons
0"Harlow"
1"Quinn"
2"Tomás"
3"Herrera"
4"Morris"
places
0"Chalk"
1"Farm"
2"Camden"
3"Soho"
4"Inverness"
5"Street"
6"Hanbury"
globalScore1
windowScore1
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences37
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount865
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences61
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs25
mean34.6
std25.7
cv0.743
sampleLengths
056
164
24
349
448
532
627
77
89
995
1026
118
1220
135
1483
1540
1679
176
1837
1953
2028
218
2220
2317
2444
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount0
totalSentences50
matches(empty)
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs115
matches(empty)
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences61
ratio0
matches(empty)
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount671
adjectiveStacks0
stackExamples(empty)
adverbCount17
adverbRatio0.02533532041728763
lyAdverbCount3
lyAdverbRatio0.004470938897168405
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences61
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences61
mean14.18
std10.85
cv0.765
sampleLengths
039
17
210
313
451
54
65
733
83
98
109
1117
1210
1312
149
155
1618
1710
1817
197
209
2120
223
2331
2416
2519
266
275
2821
293
305
316
329
335
345
352
3620
3723
389
3929
4021
4119
426
4329
4444
456
4637
475
4820
4911
75.41% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats4
diversityRatio0.4918032786885246
totalSentences61
uniqueOpeners30
100.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount2
totalSentences45
matches
0"Somewhere far down, a voice"
1"Then she stepped through the"
ratio0.044
42.22% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount20
totalSentences45
matches
0"Her watch face fogged on"
1"She wiped the glass with"
2"He moved like a man"
3"He glanced over his shoulder."
4"He didn't stop."
5"He laughed, short and breathless,"
6"Her breath came hard now."
7"His voice bounced off the"
8"He cut left through a"
9"Her heart kicked."
10"She remembered the last time"
11"She had not slept properly"
12"She pushed through the gap."
13"Her hand drifted towards her"
14"He turned, and rain dripped"
15"Her training screamed at her"
16"Her phone showed one bar,"
17"She thought of Morris's last"
18"She thought of her own"
19"he said quietly"
ratio0.444
60.00% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount36
totalSentences45
matches
0"The rain had been falling"
1"Her watch face fogged on"
2"She wiped the glass with"
3"He moved like a man"
4"He glanced over his shoulder."
5"Rain ran off the short"
6"He didn't stop."
7"He laughed, short and breathless,"
8"Quinn's shoes hit the wet"
9"Neon from a kebab shop"
10"A bottle smashed somewhere behind"
11"Her breath came hard now."
12"His voice bounced off the"
13"He cut left through a"
14"Her heart kicked."
15"She remembered the last time"
16"Morris had walked into something"
17"Quinn had stood over the"
18"She had not slept properly"
19"She pushed through the gap."
ratio0.8
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences45
matches(empty)
ratio0
89.95% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences27
technicalSentenceCount2
matches
0"Somewhere far down, a voice laughed, and then music started, a single warped violin note that stretched and stopped."
1"She thought of Morris's last transmission, a half-sentence that had cut off mid-word."
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags7
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags5
fancyCount0
fancyTags(empty)
dialogueSentences18
tagDensity0.278
leniency0.556
rawRatio0
effectiveRatio0
91.4061%