Run: 2026-07-25-01KYCPV943P2RGJA85377RTCVE

Run Details

Duration:
49.0s
Cost:
$0.069545
Provider:
Amazon Bedrock

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 came down in sheets across Camden High Street, turning the tarmac into a black mirror that shattered under every footfall. Quinn ran through it with her coat open, her radio dead in her pocket, and the shape of Tomás Herrera thirty metres ahead of her, cutting between a bus shelter and a shuttered kebab shop. He was fast. Faster than a man carrying a courier bag had any right to be. He'd taken the corner off Kentish Town Road without slowing, and she'd lost half a second on the wet kerb, one hand slapping the wall of a Tesco Express to keep herself upright. Her watch strap had gone slick against her wrist. Her lungs burned in that specific way that reminded her she was forty-one and hadn't run the sprints since Hendon. "Herrera!" She shouted it into the rain and didn't expect it to land. "Tomás! Stop!" He looked back. That was his mistake and she filed it away, because in that half-turn she saw his face clear under the streetlight — olive skin, water streaming off his jaw, and something around his neck catching the amber glow. A medallion on a chain, bouncing against his collarbone. Saint Christopher. Patron saint of travellers. Fitting. He put his head down and went left into the mouth of an alley that Quinn knew, because she'd walked this beat for two years before she made DS, ended in a brick wall and three commercial bins. She allowed herself a breath. Something like satisfaction settled in her chest as she took the corner, one hand already going to the cuffs at the back of her belt. The alley was empty. She stopped dead. Water hammered the bin lids, a flat industrial percussion. The wall at the end was exactly where she remembered it, unhelpful and solid, tagged over with three generations of graffiti. No fire escape. No doorway. A drainpipe too narrow and too rusted to hold a grown man's weight. "No," Quinn said. She swept her torch across the ground. Puddles. A crushed can. And there, in the corner where the wall met the terrace, a rectangle of deeper black where the paving had been lifted and set aside — a service hatch, iron, propped open at forty degrees against the brick. She crouched. Cold air came up out of it, and it didn't smell like sewage. It smelled like a Tube tunnel: dust, brake iron, warm electric. And under that, something floral and rotten, incense left too long in a damp room. There were rungs. Someone had welded them in, and they weren't old. Quinn stayed on her heels and did the arithmetic she'd been trained to do. No radio signal — she'd checked twice since Chalk Farm and got nothing but static, which was its own kind of information. No backup, because she hadn't logged this as a pursuit, because she hadn't logged any of the last six weeks, because the moment she put Herrera's name in a case file next to the words *Raven's Nest* she'd be in front of a DCI explaining why a decorated detective was building a wall of red string in her spare room. Eighteen years. Commendations. A file so clean it squeaked. And a partner in the ground. Morris had gone into a basement in Deptford on a Tuesday night in November and come out on a coroner's table with a report that said *cardiac event* and photographs that said something else entirely. Frost on the inside of a warm room. Her partner's hands curled like he'd been holding on to something. Quinn had read that report eleven times and every reading was a hole in the world she couldn't stop putting her hand into. Herrera knew something. She was certain of it in the way she was certain about very little anymore. Former paramedic. Struck off by the NHS for reasons the tribunal minutes described as *administering unauthorised treatments* and then, curiously, redacted for four consecutive paragraphs. He'd been in the Nest three times in the last fortnight. He carried a bag full of things that weren't in any formulary she could find. The hatch breathed cold at her. "Right," Quinn said, to nobody, and swung her legs into the dark. The rungs were slick. She went down twelve of them with her torch clamped in her teeth and her coat catching on the frame, and dropped the last metre onto concrete that rang hollow. The rain became a distant hush above her, like a crowd in another room. She was standing on a platform. Actual platform, tiled, with the curve of a tunnel mouth at each end and a strip of ancient enamel signage still clinging to the wall in cream and blue letters half-eaten by damp. She got two of them: *SO*—something—*RN*. There were no rails. The trackbed had been floored over with pallets and boards. And there were lights. Not electric. Down the length of the platform, hung from the ceiling on wire and from stanchions on hooks, dozens of glass jars glowed a low fungal green, the colour of the neon above Silas' door, the colour of nothing that grew in England. They lit stalls. Trestle tables. Tarpaulins strung as awnings. A tin sign hand-painted with a crescent moon. Somewhere down there a man was laughing, and a woman was singing something with too many syllables in it, and a hundred quiet voices layered into the murmur of a market that should not have existed forty feet under Camden. Quinn switched off her torch. It felt suddenly like walking into a room and turning on the lights during someone's funeral. She could see Herrera. He'd stopped at the top of the stairs at the far end, hands on his knees, chest heaving, and now he straightened up and looked back along the platform at her. Two hundred metres. Between them, a market full of people who turned, one at a time, to see what he was looking at. A boy at the nearest stall put down a mortar and pestle. He was maybe nineteen, and his eyes had no whites at all. Quinn's hand went to her hip and found nothing there worth finding — a warrant card, a phone with no signal, cuffs. She'd left her stab vest in the car in a fit of confidence she was already revising. "You shouldn't be here." Herrera's voice carried, and it carried strangely, arriving thinner than it should have. "Detective. *Detective.* Turn around." "Come here and say it to my face." "I'm saying it from here so you live." He wiped rain off his mouth with the back of his wrist. "You don't have a token. You know what that means? No, you don't. That's the whole problem with you people, you come down without knowing—" A woman stepped out from behind the tarpaulin nearest Quinn. Tall, in a butcher's apron, holding a curved knife she wasn't using on any meat Quinn could see. She said something. Not in English. Not in any language Quinn had heard on the High Street, and Quinn had heard most of them. "She's asking if you're bringing an offering or if you're the offering," Herrera called. "I would answer carefully." Quinn stood on the tiles with rainwater running out of her hair and down the back of her collar, and behind her the rungs went up into an alley with brick walls and bins and a beat she understood. She thought about Morris' hands. Curled. Holding on. "Tell her," Quinn said, and got her warrant card out and held it up so the green light caught the crest, "that I'm buying." The butcher looked at the card. Then she laughed — a wet, delighted sound — and stepped aside, and the market opened up in front of Quinn like a throat. Herrera swore in Spanish and started walking back towards her.
created_at"2026-07-25T13:18:47.435Z" 7/25/2026, 1:18:47 PM
model"anthropic/claude-opus-5-20260723"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency2170
moderation_latency(null)
generation_time48940
tokens_prompt1104
tokens_completion1861
native_tokens_prompt1574
native_tokens_completion2467
native_tokens_completion_images(null)
native_tokens_reasoning0
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"
usage0.069545
router(null)
provider_responses
0
endpoint_id"76cb4608-f48c-483d-8da8-9957fb44244e"
id"msg_011CdNqnpZpfEGQdP2ZnVo6z"
is_byokfalse
latency2170
model_permaslug"anthropic/claude-opus-5-20260723"
provider_name"Amazon Bedrock"
status200
user_agent"langchainjs-openai/1.0.0 ((node/v24.18.0; linux; x64))"
http_referer(null)
request_id"req-1784985527-SZxPgZbEUq7nisVOMRXp"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1784985527-EGqayRppIbTduwwJS5EZ"
upstream_id"msg_011CdNqnpZpfEGQdP2ZnVo6z"
total_cost0.069545
cache_discount(null)
upstream_inference_cost0
provider_name"Amazon Bedrock"
response_cache_source_id(null)
data_region"global"

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags9
adverbTagCount0
adverbTags(empty)
dialogueSentences12
tagDensity0.75
leniency1
rawRatio0
effectiveRatio0
88.57% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1312
totalAiIsmAdverbs3
found
0
adverb"very"
count1
1
adverb"suddenly"
count1
2
adverb"carefully"
count1
highlights
0"very"
1"suddenly"
2"carefully"
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)
77.13% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1312
totalAiIsms6
found
0
word"shattered"
count1
1
word"footfall"
count1
2
word"streaming"
count1
3
word"weight"
count1
4
word"electric"
count2
highlights
0"shattered"
1"footfall"
2"streaming"
3"weight"
4"electric"
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
narrationSentences96
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount0
narrationSentences96
filterMatches
0"watch"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences101
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen60
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans6
markdownWords10
totalWords1318
ratio0.008
matches
0"Raven's Nest"
1"cardiac event"
2"administering unauthorised treatments"
3"SO"
4"RN"
5"Detective."
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions10
unquotedAttributions0
matches(empty)
50.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions47
wordCount1231
uniqueNames23
maxNameDensity1.22
worstName"Quinn"
maxWindowNameDensity3.5
worstWindowName"Quinn"
discoveredNames
Camden2
High2
Street2
Tomás1
Herrera7
Kentish1
Town1
Road1
Tesco1
Express1
Hendon1
Christopher1
Quinn15
Tube1
Chalk1
Farm1
Deptford1
Tuesday1
November1
Nest2
English1
Curled1
Spanish1
persons
0"Tomás"
1"Herrera"
2"Christopher"
3"Quinn"
places
0"Camden"
1"High"
2"Street"
3"Kentish"
4"Town"
5"Road"
6"Chalk"
7"Farm"
8"Deptford"
9"November"
10"Nest"
11"English"
12"Spanish"
globalScore0.891
windowScore0.5
68.03% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences61
glossingSentenceCount2
matches
0"Something like satisfaction settled in her c"
1"smelled like a Tube tunnel: dust, brake ir"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1318
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount1
totalSentences101
matches
0"read that report"
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs39
mean33.79
std26.04
cv0.771
sampleLengths
056
178
215
356
41
538
630
74
851
93
1049
1141
1212
1396
149
156
1677
1769
186
1912
2048
2159
224
23101
2421
2535
2623
2724
2839
2921
308
3145
3252
3318
3439
358
3624
3730
3810
94.30% Passive voice overuse
Target: ≤2% passive sentences
passiveCount3
totalSentences96
matches
0"been lifted"
1"been trained"
2"been floored"
0.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount7
totalVerbs186
matches
0"was building"
1"was standing"
2"was laughing"
3"was singing"
4"was looking"
5"was already revising"
6"wasn't using"
0.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount8
semicolonCount0
flaggedSentences6
totalSentences101
ratio0.059
matches
0"That was his mistake and she filed it away, because in that half-turn she saw his face clear under the streetlight — olive skin, water streaming off his jaw, and something around his neck catching the amber glow."
1"And there, in the corner where the wall met the terrace, a rectangle of deeper black where the paving had been lifted and set aside — a service hatch, iron, propped open at forty degrees against the brick."
2"No radio signal — she'd checked twice since Chalk Farm and got nothing but static, which was its own kind of information."
3"She got two of them: *SO*—something—*RN*."
4"Quinn's hand went to her hip and found nothing there worth finding — a warrant card, a phone with no signal, cuffs."
5"Then she laughed — a wet, delighted sound — and stepped aside, and the market opened up in front of Quinn like a throat."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount901
adjectiveStacks0
stackExamples(empty)
adverbCount20
adverbRatio0.022197558268590455
lyAdverbCount3
lyAdverbRatio0.003329633740288568
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences101
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences101
mean13.05
std11.89
cv0.911
sampleLengths
021
135
23
313
433
59
620
713
82
93
1038
119
122
134
141
1538
165
1725
184
193
209
2121
223
232
2413
253
267
271
283
2938
302
3113
3211
3315
343
359
3614
3722
3860
392
401
416
426
4335
448
4511
4623
473
4815
492
74.26% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats5
diversityRatio0.4752475247524752
totalSentences101
uniqueOpeners48
81.30% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount2
totalSentences82
matches
0"Somewhere down there a man"
1"Then she laughed — a"
ratio0.024
88.29% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount27
totalSentences82
matches
0"He was fast."
1"He'd taken the corner off"
2"Her watch strap had gone"
3"Her lungs burned in that"
4"She shouted it into the"
5"He looked back."
6"He put his head down"
7"She allowed herself a breath."
8"She stopped dead."
9"She swept her torch across"
10"It smelled like a Tube"
11"Her partner's hands curled like"
12"She was certain of it"
13"He'd been in the Nest"
14"He carried a bag full"
15"She went down twelve of"
16"She was standing on a"
17"She got two of them:"
18"They lit stalls."
19"It felt suddenly like walking"
ratio0.329
94.15% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount60
totalSentences82
matches
0"Rain came down in sheets"
1"Quinn ran through it with"
2"He was fast."
3"He'd taken the corner off"
4"Her watch strap had gone"
5"Her lungs burned in that"
6"She shouted it into the"
7"He looked back."
8"That was his mistake and"
9"A medallion on a chain,"
10"Patron saint of travellers."
11"He put his head down"
12"She allowed herself a breath."
13"Something like satisfaction settled in"
14"The alley was empty."
15"She stopped dead."
16"Water hammered the bin lids,"
17"The wall at the end"
18"A drainpipe too narrow and"
19"She swept her torch across"
ratio0.732
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences82
matches(empty)
ratio0
40.82% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences42
technicalSentenceCount6
matches
0"Rain came down in sheets across Camden High Street, turning the tarmac into a black mirror that shattered under every footfall."
1"That was his mistake and she filed it away, because in that half-turn she saw his face clear under the streetlight — olive skin, water streaming off his jaw, an…"
2"No radio signal — she'd checked twice since Chalk Farm and got nothing but static, which was its own kind of information."
3"Morris had gone into a basement in Deptford on a Tuesday night in November and come out on a coroner's table with a report that said *cardiac event* and photogr…"
4"Somewhere down there a man was laughing, and a woman was singing something with too many syllables in it, and a hundred quiet voices layered into the murmur of …"
5"Tall, in a butcher's apron, holding a curved knife she wasn't using on any meat Quinn could see."
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags9
uselessAdditionCount0
matches(empty)
66.67% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags5
fancyCount1
fancyTags
0"She shouted (shout)"
dialogueSentences12
tagDensity0.417
leniency0.833
rawRatio0.2
effectiveRatio0.167
80.7838%