Run: 2026-10-08-01M4DA3ZK5JGDCHFZMXTAJQQCP

Run Details

Duration:
22.4s
Cost:
$0.002134
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 green neon above the Raven's Nest buzzed like a trapped insect, bleeding colour across the wet pavement of Dean Street. Harlow Quinn stood in a doorway opposite, rain running off the peak of her cap and down the back of her collar. The leather strap of her watch had soaked through, and the cold worked its way into the joints of her wrist. Three hours she had waited. Three hours of drunks, delivery bikes and a fox that seemed to have business of its own. Then the door opened, and Tomás Herrera stepped out with his collar up and a canvas holdall clamped against his ribs. She knew the walk before she saw the face. Hands buried in his pockets, shoulders hunched, eyes sweeping the street the way a man checks for a bus he already knows is late. When he turned under the streetlamp, the scar along his left forearm showed pale and ropy, and the silver medallion swung out from his shirt and caught the light. Quinn pushed off the doorframe and let him get twenty metres clear before she followed. He didn't hail a cab. He didn't drop into the Tube at Tottenham Court Road. He walked north through Soho's narrow arteries, past shuttered doors and steaming extractor vents, and she shadowed him along the opposite pavement, keeping the parked vans between them. Rain drummed on the roofs of the cars. Somewhere a bass line thudded through a basement wall and cut out mid-beat. She tried the radio at Oxford Street. The handset spat static, then nothing. She swore under her breath and shoved it back into her coat. By the time he crossed the Euston Road, she had decided where he was going. By the time he reached the canal, she was sure of it. Camden at this hour belonged to the wrong sort of people. Light and noise spilled from the pub on the corner, but Herrera ducked past it and cut down a side street where half the lamps were dead and the buildings leaned in close, as if eavesdropping. Water pooled in the potholes and threw the orange glow back in long, shivering smears. He stopped at a chain-link gate set into a brick arch. Beyond it, a stairwell dropped into blackness, and a tiled sign half-buried under graffiti announced a station name Quinn had not thought about in years. She stopped at the mouth of the side street and pressed her back to the wall. Herrera turned, and for one bad second she thought he had seen her. He hadn't. He reached inside his coat and drew out something pale and round. A disc, carved with lines she couldn't read from here, glowing faintly like old ivory. A figure peeled itself from the shadows beside the gate. Tall and narrow, wrapped in a coat that didn't stir in the wind. Beneath the hood, the face was a smooth, unmarked oval. "Token," it said. The voice seemed to come from somewhere below its ribs. "I'm expected," Herrera said. He held up the disc between two fingers. The figure took it, turned it over with long, pale fingers, and tucked it away somewhere inside its coat. The gate unlatched with a sound like a knuckle cracking. Herrera slipped through without looking back. Quinn's hand found her warrant card in the inside pocket of her coat. She ran her thumb over the worn edge. Her ID would mean nothing down there, she suspected. Nothing about the last three years had meant anything in the way the institution wanted it to. She kept her hand where it was and stepped out from the wall. The hooded head turned toward her, unhurried, the way a compass needle settles on north. "You're not on the list," it said. "No," Quinn said. "I'm not." "Then you cannot go down." She looked past it into the stairwell. Warm air rose up the stone steps, thick with cloves, wet brick and something sharper underneath, like old pennies. From far below came a murmur of voices, a laugh, the chime of glass against glass. Herrera's footsteps were already fading into it. Three years ago she had stood at the edge of a dark place just like this one, watching a man she trusted walk into it ahead of her. She had hesitated. Morris had gone through alone, and she had spent every day since working out whether that hesitation had saved her or cost him everything. The figure waited. Rain dripped from the gate's rusted hinges, one drop at a time. Quinn pulled her watch straight on her wrist, rolled her shoulders, and set her boot on the top step.
created_at"2026-10-08T08:29:46.478Z" 10/8/2026, 8:29:46 AM
model"anthropic/claude-haiku-5.5-20261007"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency22378
moderation_latency(null)
generation_time22378
tokens_prompt1104
tokens_completion1092
native_tokens_prompt1576
native_tokens_completion3953
native_tokens_completion_images(null)
native_tokens_reasoning2487
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"
usage0.0021341
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.21.0; linux; x64))"
http_referer(null)
request_id"req-1791448186-wIKrUjS5bumruSvDyG97"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1791448186-Q96ECf4kN86aOnH5Gcu8"
upstream_id"msg_011CfpTRDpfmwjSd5Q6F1auG"
provider_responses
0
endpoint_id"b6cdf493-3a61-441f-a134-e7944fddb980"
id"msg_011CfpTRDpfmwjSd5Q6F1auG"
is_byokfalse
latency820
model_permaslug"anthropic/claude-haiku-5.5-20261007"
provider_name"Claude Platform on AWS"
status200
total_cost0.0021341
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
totalTags4
adverbTagCount0
adverbTags(empty)
dialogueSentences6
tagDensity0.667
leniency1
rawRatio0
effectiveRatio0
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount779
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)
93.58% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount779
totalAiIsms1
found
0
word"footsteps"
count1
highlights
0"footsteps"
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
narrationSentences58
matches(empty)
44.33% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount2
hedgeCount2
narrationSentences58
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)
analyzedSentences60
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
totalWords779
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions4
unquotedAttributions0
matches(empty)
100.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions29
wordCount763
uniqueNames15
maxNameDensity0.79
worstName"Quinn"
maxWindowNameDensity1.5
worstWindowName"Quinn"
discoveredNames
Raven1
Nest1
Dean1
Street2
Quinn6
Tomás1
Herrera6
Tube1
Tottenham1
Court1
Road2
Soho1
Oxford1
Euston1
Three3
persons
0"Raven"
1"Nest"
2"Quinn"
3"Tomás"
4"Herrera"
places
0"Dean"
1"Street"
2"Tube"
3"Tottenham"
4"Court"
5"Road"
6"Soho"
7"Oxford"
8"Euston"
globalScore1
windowScore1
47.96% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences49
glossingSentenceCount2
matches
0"fox that seemed to have business of its own"
1"as if eavesdropping"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount779
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences60
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs23
mean33.87
std25.67
cv0.758
sampleLengths
086
121
262
315
464
525
627
798
816
942
1033
1113
1212
1335
1460
1515
167
175
185
1949
2055
2115
2219
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount0
totalSentences58
matches(empty)
98.22% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount2
totalVerbs131
matches
0"was going"
1"were already fading"
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences60
ratio0
matches(empty)
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount766
adjectiveStacks0
stackExamples(empty)
adverbCount13
adverbRatio0.016971279373368148
lyAdverbCount1
lyAdverbRatio0.0013054830287206266
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences60
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences60
mean12.98
std7.52
cv0.579
sampleLengths
021
122
221
35
417
521
69
724
829
915
105
1110
1228
138
1413
157
166
1712
1815
1912
2011
2136
2215
2311
2425
2516
2613
272
2812
2915
3010
3113
3210
333
3410
354
368
3719
3810
396
4013
418
429
4317
4413
4515
467
473
482
495
68.89% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats7
diversityRatio0.48333333333333334
totalSentences60
uniqueOpeners29
100.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount2
totalSentences53
matches
0"Then the door opened, and"
1"Somewhere a bass line thudded"
ratio0.038
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount15
totalSentences53
matches
0"She knew the walk before"
1"He didn't hail a cab."
2"He didn't drop into the"
3"He walked north through Soho's"
4"She tried the radio at"
5"She swore under her breath"
6"He stopped at a chain-link"
7"She stopped at the mouth"
8"He reached inside his coat"
9"He held up the disc"
10"She ran her thumb over"
11"Her ID would mean nothing"
12"She kept her hand where"
13"She looked past it into"
14"She had hesitated."
ratio0.283
92.08% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount39
totalSentences53
matches
0"The green neon above the"
1"Harlow Quinn stood in a"
2"The leather strap of her"
3"She knew the walk before"
4"Hands buried in his pockets,"
5"Quinn pushed off the doorframe"
6"He didn't hail a cab."
7"He didn't drop into the"
8"He walked north through Soho's"
9"Rain drummed on the roofs"
10"She tried the radio at"
11"The handset spat static, then"
12"She swore under her breath"
13"Camden at this hour belonged"
14"Water pooled in the potholes"
15"He stopped at a chain-link"
16"She stopped at the mouth"
17"Herrera turned, and for one"
18"He reached inside his coat"
19"A disc, carved with lines"
ratio0.736
100.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount2
totalSentences53
matches
0"By the time he crossed"
1"By the time he reached"
ratio0.038
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences39
technicalSentenceCount2
matches
0"Three hours of drunks, delivery bikes and a fox that seemed to have business of its own."
1"Light and noise spilled from the pub on the corner, but Herrera ducked past it and cut down a side street where half the lamps were dead and the buildings leane…"
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags4
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags4
fancyCount0
fancyTags(empty)
dialogueSentences6
tagDensity0.667
leniency1
rawRatio0
effectiveRatio0
94.8353%