Run: 2026-10-08-01M4DA54DJVF26ZZWZ8EV7BKB3

Run Details

Duration:
13.5s
Cost:
$0.001154
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 came sideways off the canal, slapping against Harlow Quinn's face as she cut past the shuttered stalls of Camden Lock. Her watch read twenty past eleven. The leather strap had gone dark with water, and the face was fogged at the edges. Ahead, a dark coat bolted between two parked vans, and the hem flared behind him like a wing. "Metropolitan Police. Stop where you are." He did not stop. Tomás Herrera had never once stopped for anyone in the three months she had been watching him, and he was not about to start now. He vaulted a low railing, landed badly on the slick cobbles, and kept his left arm tucked tight against his ribs. The sleeve had ridden up. Even in the sodium glow she caught the pale ridge of the scar running from wrist to elbow. Quinn went over the railing faster than she should have. Her knee complained. She ignored it. They spilled onto Chalk Farm Road, where the traffic hissed through standing water and the neon of a kebab shop bled red across the pavement. A cab swerved, horn bellowing. Herrera shoulder-checked a woman carrying a bag of shopping, muttered an apology in Spanish that sounded almost sincere, and kept running. Quinn shoved past the woman, who swore at her in a language Quinn didn't speak, and kept her eyes on the coat. "You're making this harder on yourself, Tomás," she called out. Her breath came short and hot. "Whatever you're carrying, put it down." He glanced back. The medallion around his neck swung free of his collar and caught the light, a small silver saint carrying a child across a river. "You think I'm carrying something?" His voice had the bruised roughness of a man who had been awake for two days. "I'm carrying a lot of things, Detective. None of them are yours." He veered left onto a side street, and Quinn lost sight of him for three full seconds before she heard the scrape of a shoe against brick. She followed the sound. The street narrowed into a service alley, bins stacked high, a single bulb buzzing overhead. At the far end, Herrera was crouched beside a rusted grate, prying at it with his good hand. Quinn stopped ten feet away and raised her warrant card. The plastic was wet and the photograph had blurred, but the badge still caught the light. "Step away from the grate. Hands where I can see them." He lifted his hands. Something small and pale dangled from his fingers. Quinn caught the gleam of it and felt her stomach tighten. It looked like a carved piece of bone, threaded on a length of black cord. "You know what this is?" he asked. "I know what it's going to be if you use it." Herrera laughed, a short, humourless sound. "Then you know more than most of your colleagues." He nodded at the grate. Beneath it, a flight of iron steps descended into darkness, and a breath of cold air rose up through the bars. It carried the smell of wet stone, old tallow and something sweeter underneath, like burnt sugar and copper. "The Tube station closed in 1958. Did you know that? Nobody's used it for seventy years. Except for the people who never left." "Camden," Quinn said. "The abandoned platform." "The Veil Market. Tonight it's underneath Camden. Next month, who knows?" He slid the bone token onto his thumb and rolled it between his fingers. "Come down with me, and you'll see things your superiors don't believe exist. Stay up here, and you'll go back to your desk, file a report, and wonder for the rest of your life why Daniel Morris never came home." The name hit her like a cold slap. Quinn kept her face still. Years of interview rooms had taught her that much. But her grip tightened on the warrant card until the edges bit into her palm. "Don't you say his name." "He came down here three years ago," Herrera said quietly. "He asked the same questions you're asking. He chased somebody too." "Did you take him?" Herrera said nothing. Water dripped from the fire escape above and struck the lid of a bin with a hollow, patient rhythm. Quinn looked at the grate, then at the iron steps. The darkness below did not seem empty. It seemed to be waiting, the way a held breath waits. Her watch ticked against her wrist. Radio backup was twelve minutes out, if the dispatcher was right, and the dispatcher had been wrong about the last two calls. She took one step toward the grate. The metal of the bars looked black with age, flecked with something pale that might have been rust and might not. "Last chance, Quinn," Herrera said. He stood, the bone token swinging from his fingers, the saint on his chest rising and falling with each breath. "Are you coming down, or are you going home?"
created_at"2026-10-08T08:30:24.186Z" 10/8/2026, 8:30:24 AM
model"anthropic/claude-haiku-5.5-20261007"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency2420
moderation_latency(null)
generation_time13505
tokens_prompt1104
tokens_completion1370
native_tokens_prompt1576
native_tokens_completion1993
native_tokens_completion_images(null)
native_tokens_reasoning425
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"
usage0.0011541
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.21.0; linux; x64))"
http_referer(null)
request_id"req-1791448224-AuQ6lXKHJeiXyQ6MnWUQ"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1791448224-S4wnptjLM8uafi33aNCH"
upstream_id"msg_011CfpTTzwMZbxLTnwBrLX9n"
provider_responses
0
endpoint_id"b6cdf493-3a61-441f-a134-e7944fddb980"
id"msg_011CfpTTzwMZbxLTnwBrLX9n"
is_byokfalse
latency833
model_permaslug"anthropic/claude-haiku-5.5-20261007"
provider_name"Claude Platform on AWS"
status200
total_cost0.0011541
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
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags8
adverbTagCount1
adverbTags
0"Herrera said quietly [quietly]"
dialogueSentences20
tagDensity0.4
leniency0.8
rawRatio0.125
effectiveRatio0.1
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount829
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)
93.97% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount829
totalAiIsms1
found
0
word"stomach"
count1
highlights
0"stomach"
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
narrationSentences54
matches(empty)
63.49% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount2
hedgeCount1
narrationSentences54
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)
analyzedSentences66
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen40
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords829
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions8
unquotedAttributions0
matches(empty)
71.88% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions24
wordCount640
uniqueNames9
maxNameDensity1.56
worstName"Quinn"
maxWindowNameDensity2.5
worstWindowName"Quinn"
discoveredNames
Harlow1
Quinn10
Camden1
Lock1
Herrera7
Chalk1
Farm1
Road1
Spanish1
persons
0"Harlow"
1"Quinn"
2"Herrera"
places
0"Chalk"
1"Farm"
2"Road"
3"Spanish"
globalScore0.719
windowScore0.833
84.21% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences38
glossingSentenceCount1
matches
0"looked like a carved piece of bone, threa"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount829
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences66
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs23
mean36.04
std25.09
cv0.696
sampleLengths
062
16
273
316
473
522
660
764
837
938
107
1111
1282
136
1465
1537
165
1721
184
1922
2056
2128
2234
92.27% Passive voice overuse
Target: ≤2% passive sentences
passiveCount2
totalSentences54
matches
0"was fogged"
1"was crouched"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs108
matches(empty)
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences66
ratio0
matches(empty)
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount641
adjectiveStacks0
stackExamples(empty)
adverbCount9
adverbRatio0.014040561622464899
lyAdverbCount2
lyAdverbRatio0.0031201248049922
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences66
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences66
mean12.56
std7.92
cv0.63
sampleLengths
022
16
216
318
46
54
625
721
85
918
1010
113
123
1325
145
1521
1622
1710
186
196
203
2124
2221
2312
2427
254
2615
2718
2810
2916
3011
314
328
3311
3415
357
3611
376
3814
3921
4018
4123
423
433
4425
4540
468
475
489
4915
75.25% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats2
diversityRatio0.4696969696969697
totalSentences66
uniqueOpeners31
0.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount0
totalSentences51
matches(empty)
ratio0
55.29% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount21
totalSentences51
matches
0"Her watch read twenty past"
1"He did not stop."
2"He vaulted a low railing,"
3"Her knee complained."
4"She ignored it."
5"They spilled onto Chalk Farm"
6"she called out"
7"Her breath came short and"
8"He glanced back."
9"His voice had the bruised"
10"He veered left onto a"
11"She followed the sound."
12"He lifted his hands."
13"It looked like a carved"
14"He nodded at the grate"
15"It carried the smell of"
16"He slid the bone token"
17"It seemed to be waiting,"
18"Her watch ticked against her"
19"She took one step toward"
ratio0.412
9.02% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount46
totalSentences51
matches
0"The rain came sideways off"
1"Her watch read twenty past"
2"The leather strap had gone"
3"He did not stop."
4"Tomás Herrera had never once"
5"He vaulted a low railing,"
6"The sleeve had ridden up."
7"Quinn went over the railing"
8"Her knee complained."
9"She ignored it."
10"They spilled onto Chalk Farm"
11"A cab swerved, horn bellowing."
12"Herrera shoulder-checked a woman carrying"
13"Quinn shoved past the woman,"
14"she called out"
15"Her breath came short and"
16"He glanced back."
17"The medallion around his neck"
18"His voice had the bruised"
19"He veered left onto a"
ratio0.902
98.04% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount1
totalSentences51
matches
0"Even in the sodium glow"
ratio0.02
89.95% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences27
technicalSentenceCount2
matches
0"Herrera shoulder-checked a woman carrying a bag of shopping, muttered an apology in Spanish that sounded almost sincere, and kept running."
1"He stood, the bone token swinging from his fingers, the saint on his chest rising and falling with each breath."
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags8
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags4
fancyCount0
fancyTags(empty)
dialogueSentences20
tagDensity0.2
leniency0.4
rawRatio0
effectiveRatio0
87.7789%