Run: 2026-10-09-01M4G07BW7DDF20KCCT8523FQT

Run Details

Duration:
15.8s
Cost:
$0.001295
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 Thames and found every gap in Quinn's collar before she reached Dean Street. She didn't bother with the umbrella clipped to her belt. Water ran down her neck and into the wool of her coat, and she let it. Ahead, the green neon of the Raven's Nest bled across the wet pavement, and the figure in the grey hoodie was already past it, moving fast along the kerb with one hand jammed in a pocket. "Herrera!" Her voice cut through the traffic hiss. "Stop where you are." He didn't stop. He glanced over his shoulder, and even at forty metres she caught the flash of his face, the dark curls plastered flat, the mouth set in something close to exasperation. Then he broke left into Bateman Street and vanished between two parked vans. Quinn ran. Her left wrist caught the streetlight as she swung her arm, the worn leather strap of her watch darkening with rain. Eighteen years of training had taught her to run without wasting motion, but her knees had opinions about it now. She hit the corner and took the turn wide, skidding on a slick of oil and cardboard, and caught her balance against a shuttered florist's grille. "Don't make me chase you through Soho in this weather," she called. "You'll only get wet, and I'll only get annoyed." Tomás's voice floated back, rough at the edges, the vowels stretched by a childhood somewhere far south of here. "You always say that, Detective. Yet here you are, drowning." She rounded the next corner. He was gone again, but a metal door on the far side of the street swung shut with a bang that rang off the brickwork. Quinn crossed without looking. A cab horn blared and a driver swore at her in three languages. She didn't care. She reached the door, grabbed the handle, and found it locked from the inside. "Open it," she said. Nothing. Then the scrape of a bolt and the door cracked an inch. Tomás's face appeared in the gap, lit from below by a single bare bulb. His left forearm was pressed against the frame, and the old knife scar stood out pale and ridged in the light. "You're going to arrest me for walking home," he said. "I'm going to arrest you for whatever you've been doing with your clinic in the back of that bar. Unlicensed treatment. Unlicensed everything. Three people in Hackney have stopped breathing properly since you touched them." "They were already dying." He didn't blink. The Saint Christopher medallion swung out from his collar and caught the light. "You know that. You read the files. Some of them were dead before the ambulance came, and I was the only one who would crawl through the mess for them." "Then come out and explain it to a magistrate." Tomás laughed, short and bitter, and it sounded like it hurt him. "Explain what, Detective? That the people who come to me don't have pulses that a machine can read? That their wounds close if you put the right herbs on them and speak to them in the right way?" "Step out where I can see your hands." Instead, he glanced down the passage behind him, then back at her. "You don't understand what you're asking. If I go out this door, I'm yours. If I go down there, I'm nobody's." "Down where?" He stepped back. The door swung wide enough for her to see the passage beyond, a narrow corridor of wet brick sloping away into darkness. Cold air rolled up from it, smelling of diesel, old stone, and something sweeter underneath, like lilies left too long in a vase. At the bottom, faint and blue, a light flickered where a rusted iron grate sealed off the way forward. Quinn stepped into the doorway and her boot found a metal step. The stairs went down, dropping steep and narrow past a sign so old its paint had flaked to nothing. Some lettering survived at the edge of the stonework: a broken ring, and beneath it, a single word that had been carved, not painted. *Camden.* The Tube was long dead here. She knew that. The line had been closed for decades, the platforms bricked up and the tunnels sealed after a collapse that never made the papers. Her files had mentioned it once, in a dry paragraph about structural hazards, and a second time in a note from DS Morris three years ago, scribbled in the margin of a report he never finished. Below, the grate rattled. Tomás had reached it. Through the bars she saw the blue light shift, and a shape moved across it, a hand lifting something small and pale. A bone, she thought, and then the grate began to rise with a grinding groan, slow as a sigh, and the cold air poured up the stairwell into her face. "You don't have a token, Detective," Tomás called from somewhere beyond the bars. His voice was gentler now, almost pitying. "Nobody goes past that gate without one. Not even you." Quinn stood on the top step with the rain at her back and the darkness below. Her watch ticked against her wrist, loud in the quiet between gusts. Behind her, the Raven's Nest's green sign buzzed and flickered. Ahead, the grate lifted another foot and stopped. She put one hand on the cold iron railing and looked at the gap beneath the bars, wide enough for a man, perhaps not for a woman built like her. Her fingers tightened on the rail. "Tell me what's down there, Herrera," she said.
created_at"2026-10-09T09:34:34.893Z" 10/9/2026, 9:34:34 AM
model"anthropic/claude-haiku-5.5-20261007"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency2570
moderation_latency(null)
generation_time15747
tokens_prompt1104
tokens_completion1417
native_tokens_prompt1576
native_tokens_completion2274
native_tokens_completion_images(null)
native_tokens_reasoning526
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"
usage0.0012946
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.21.0; linux; x64))"
http_referer(null)
request_id"req-1791538474-buI1Rpm5oVY5QTd8giC3"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1791538474-1lXNmyiOQZdF53A3N9M4"
upstream_id"msg_011CfrSAm9Z7B7qeFgVWVnkf"
provider_responses
0
endpoint_id"b6cdf493-3a61-441f-a134-e7944fddb980"
id"msg_011CfrSAm9Z7B7qeFgVWVnkf"
is_byokfalse
latency871
model_permaslug"anthropic/claude-haiku-5.5-20261007"
provider_name"Claude Platform on AWS"
status200
total_cost0.0012946
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
totalTags6
adverbTagCount0
adverbTags(empty)
dialogueSentences18
tagDensity0.333
leniency0.667
rawRatio0
effectiveRatio0
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount942
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)
89.38% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount942
totalAiIsms2
found
0
word"flickered"
count2
highlights
0"flickered"
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
narrationSentences55
matches(empty)
64.94% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount2
hedgeCount1
narrationSentences55
filterMatches
0"watch"
hedgeMatches
0"began 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
maxSentenceWordsSeen38
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans1
markdownWords1
totalWords942
ratio0.001
matches
0"Camden."
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions10
unquotedAttributions0
matches(empty)
100.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions23
wordCount729
uniqueNames12
maxNameDensity0.69
worstName"Quinn"
maxWindowNameDensity1.5
worstWindowName"Tomás"
discoveredNames
Thames1
Quinn5
Dean1
Street2
Raven2
Nest2
Bateman1
Tomás5
Saint1
Christopher1
Tube1
Morris1
persons
0"Quinn"
1"Raven"
2"Nest"
3"Tomás"
4"Saint"
5"Christopher"
6"Morris"
places
0"Thames"
1"Dean"
2"Street"
3"Bateman"
globalScore1
windowScore1
21.79% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences39
glossingSentenceCount2
matches
0"something close to exasperation"
1"sounded like it hurt him"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount942
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
totalParagraphs25
mean37.68
std23.3
cv0.618
sampleLengths
081
112
246
369
421
529
664
74
848
910
1035
1150
129
1350
148
1533
162
1767
1856
1968
2060
2130
2246
2336
248
86.12% Passive voice overuse
Target: ≤2% passive sentences
passiveCount3
totalSentences55
matches
0"was gone"
1"been carved"
2"been closed"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs113
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
wordCount729
adjectiveStacks0
stackExamples(empty)
adverbCount20
adverbRatio0.027434842249657063
lyAdverbCount0
lyAdverbRatio0
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
mean14.27
std9.67
cv0.677
sampleLengths
019
110
216
336
48
54
63
730
813
92
1021
1120
1226
1312
149
1519
1610
175
1825
194
2013
213
2214
234
241
2512
2614
2721
2810
2935
307
3113
3230
339
3412
3538
368
3712
3821
392
403
4122
4223
4319
4412
4519
4624
471
486
493
80.30% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats2
diversityRatio0.5
totalSentences66
uniqueOpeners33
100.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount3
totalSentences48
matches
0"Then he broke left into"
1"Then the scrape of a"
2"Instead, he glanced down the"
ratio0.063
61.67% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount19
totalSentences48
matches
0"She didn't bother with the"
1"Her voice cut through the"
2"He didn't stop."
3"He glanced over his shoulder,"
4"Her left wrist caught the"
5"She hit the corner and"
6"She rounded the next corner."
7"He was gone again, but"
8"She didn't care."
9"She reached the door, grabbed"
10"His left forearm was pressed"
11"He didn't blink"
12"He stepped back."
13"She knew that."
14"Her files had mentioned it"
15"His voice was gentler now,"
16"Her watch ticked against her"
17"She put one hand on"
18"Her fingers tightened on the"
ratio0.396
74.58% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount37
totalSentences48
matches
0"The rain came sideways off"
1"She didn't bother with the"
2"Water ran down her neck"
3"Her voice cut through the"
4"He didn't stop."
5"He glanced over his shoulder,"
6"Her left wrist caught the"
7"She hit the corner and"
8"Tomás's voice floated back, rough"
9"She rounded the next corner."
10"He was gone again, but"
11"Quinn crossed without looking."
12"A cab horn blared and"
13"She didn't care."
14"She reached the door, grabbed"
15"Tomás's face appeared in the"
16"His left forearm was pressed"
17"He didn't blink"
18"The Saint Christopher medallion swung"
19"Tomás laughed, short and bitter,"
ratio0.771
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences48
matches(empty)
ratio0
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences33
technicalSentenceCount1
matches
0"Some lettering survived at the edge of the stonework: a broken ring, and beneath it, a single word that had been carved, not painted."
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags6
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
89.2931%