Run: 2026-04-24-01KQ0GB19KMCX4P922745BWMJ7

Run Details

Duration:
32.8s
Cost:
$0.067820
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 hammered the pavement in sheets, turning Dean Street into a slick black mirror. Detective Harlow Quinn ran flat-out, boots slapping through standing water, her coat pasted to her shoulders. Ahead of her, Tomás Herrera cut left down a service alley, his jacket flaring behind him like a torn wing. "Herrera! Stop! Police!" He didn't stop. He never did. She'd known he wouldn't the moment he clocked her at the end of the bar, the moment his hand had twitched towards the Saint Christopher medallion at his throat like a man saying a quick prayer before sprinting for his life. She hit the alley. A wheelie bin crashed over in front of her — his work — and she vaulted it without breaking stride, landing in a puddle deep enough to soak her to the shin. Her radio crackled against her collarbone. She slapped it off. No units. Not tonight. Tonight was hers. "Tommy!" She kept her voice level, conversational. "I just want to talk!" He laughed, high and breathless, already fifteen metres ahead. "You're a terrible liar, Detective." A good sign. A running man who talked back was a running man who'd slip. She pushed harder, her lungs working, her leather watch ticking cold against her wrist. Eighteen years on the force and she could still run any of the DCs at the station into the floor. That was the trick of grief — it made a body very efficient. He broke out onto the main road. A black cab blared at him, swerved, sent a wall of water sideways. He kept going, weaving between a startled couple under one umbrella, and swung left towards Camden Road. Camden. That was the second sign, and a worse one. Quinn filed it away and ran. They went under the railway bridge, where the sound of the rain turned metallic and the sodium lights painted Herrera's soaked curls a dirty gold. He glanced over his shoulder. His face, for half a second, was nothing like the easy-charm paramedic she'd been quietly building a file on for six months. It was the face of a man who had seen things she hadn't. The scar on his left forearm caught the light as he shoved off a railing and dropped down a set of stone steps she hadn't known were there. She followed. The steps were slick with moss, old, older than the street above them. At the bottom, a boarded hoarding that said CLOSED — TUBE WORKS. A panel in it had been kicked loose at the hinge. Herrera's shape slid through it like smoke. Quinn pulled up, one hand braced on the hoarding, rain sluicing off her cropped hair and running cold between her shoulder blades. She drew her torch and flicked it on. The beam cut into a passage of tiled walls — the old cream-and-maroon of a pre-war Tube station — and at the edge of the light, movement. A back, a flash of pale hand, gone. She listened. No traffic, this far down. The rain was muffled, a low static. Underneath it: voices. Plural. Somewhere below and ahead, a hum of commerce, of people, of bargaining in a register she couldn't place. Someone was playing a reedy instrument. She could smell woodsmoke, and under that something sweeter and more chemical, like burnt sugar laid over petrol. Three years. Three years, almost to the week, since DS Morris had walked into a warehouse in Rotherhithe and walked out in three plastic bags, with a coroner's report that read like a shrug. Unexplained. No suspect charged. Case cold and getting colder. Three years of Quinn building quiet files on the people who'd been in that warehouse and the people who knew those people, a careful pyramid of names with Tomás Herrera three rows up and the bloke from the Raven's Nest near the top. Three years of knowing, with the marrow of her, that what had killed Morris wasn't in any of the manuals they'd handed her at Hendon. She looked at the gap in the hoarding. Protocol said call it in. Protocol said wait for backup, for an entry team, for somebody in a high-vis to survey the structural integrity of an abandoned Tube station while Herrera disappeared into whatever warren lay past that tiled passage. By the time she'd finished the paperwork, he'd be in Calais. He'd be nowhere. He'd be one more name that slipped. Her torch trembled. She steadied it against her palm. "Sod it," she muttered, and ducked through. The passage sloped down. Her boots echoed. She killed the torch — it was a lighthouse in here, announcing her — and let her eyes adjust to the greenish glow bleeding up from the bend ahead. Not fluorescent. Something older. Something that breathed. She moved along the tiles with her back half-turned to the wall, her hand loose near the baton at her hip. Her sidearm stayed holstered. Firing a Glock in a tiled tunnel was a way to deafen yourself and get no one. The bend opened. What she saw made her stop, and in the stopping she understood, clean and cold, that she'd crossed a line she would not be uncrossing tonight. The platform of the old station had been stripped of its benches and signage and rebuilt into a market. Stalls ran along both tracks, cobbled together from crates and scaffolding and what looked, in one case, like the ribcage of something she couldn't name. The light came from lanterns — real lanterns, with real flames that burned green and didn't flicker. A woman in a butcher's apron was weighing something wet and grey on a brass scale. A child with too many teeth was selling folded paper birds that opened and closed their beaks. At the far end, a man in a three-piece suit was examining a jar of eyes. Quinn's hand found the tiled wall and held on. The crowd was thick. Cloaks, yes, actual cloaks, and office coats, and one woman in full leathers with a helmet under her arm. Nobody looked at her. That was almost worse than being stared at. It meant she wasn't unusual enough to be noticed. At the edge of the platform, moving fast between a stall of bottled smoke and a table piled with bones the size of dinner plates, was Tomás Herrera. He'd slowed. He thought he was safe. He was reaching into his jacket for something — a token, she saw, pale and carved, held out to a figure in a hooded robe at what she slowly understood was a checkpoint. Past the checkpoint, more tunnels. Deeper. Quinn's radio wouldn't work down here. She knew that the way she knew her own pulse. No one on the surface would hear her. No one on the surface would even know where to start. She thought about Morris. About the bags. About the shrug. She pulled her warrant card from her inside pocket, looked at it for a moment — the photo of a younger woman with more hope in her jaw — and tucked it, very carefully, into the lining of her coat where no one could see it. Then Detective Harlow Quinn stepped down onto the platform of the Veil Market and started walking.
created_at"2026-04-24T19:44:17.719Z" 4/24/2026, 7:44:17 PM
model"anthropic/claude-4.7-opus-20260416"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency1877
moderation_latency(null)
generation_time32784
tokens_prompt1140
tokens_completion1801
native_tokens_prompt1579
native_tokens_completion2397
native_tokens_completion_images(null)
native_tokens_reasoning60
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"
usage0.06782
router(null)
provider_responses
0
endpoint_id"0fa65117-00d9-4835-808d-9b68041d9ce4"
id"3cc6e22d-228a-41be-b78b-5f18e5d0e47e"
is_byokfalse
latency948
model_permaslug"anthropic/claude-4.7-opus-20260416"
provider_name"Amazon Bedrock"
status200
user_agent"langchainjs-openai/1.0.0 ((node/v24.14.1; linux; x64))"
http_referer(null)
request_id"req-1777059857-HT6wP5vFEgmkDgRmudxo"
session_id(null)
api_type"completions"
id"gen-1777059857-hTuQoxE3OST0LtkTlOiJ"
upstream_id"3cc6e22d-228a-41be-b78b-5f18e5d0e47e"
total_cost0.06782
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provider_name"Amazon Bedrock"
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Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags2
adverbTagCount0
adverbTags(empty)
dialogueSentences5
tagDensity0.4
leniency0.8
rawRatio0
effectiveRatio0
83.32% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1199
totalAiIsmAdverbs4
found
0
adverb"very"
count2
1
adverb"slowly"
count1
2
adverb"carefully"
count1
highlights
0"very"
1"slowly"
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)
66.64% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1199
totalAiIsms8
found
0
word"efficient"
count1
1
word"charm"
count1
2
word"flicked"
count1
3
word"charged"
count1
4
word"trembled"
count1
5
word"echoed"
count1
6
word"flicker"
count1
7
word"pulse"
count1
highlights
0"efficient"
1"charm"
2"flicked"
3"charged"
4"trembled"
5"echoed"
6"flicker"
7"pulse"
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
narrationSentences102
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount0
narrationSentences102
filterMatches
0"watch"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences105
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen44
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1211
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions1
unquotedAttributions0
matches(empty)
100.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions44
wordCount1195
uniqueNames22
maxNameDensity0.59
worstName"Quinn"
maxWindowNameDensity2
worstWindowName"Three"
discoveredNames
Dean1
Street1
Harlow2
Quinn7
Tomás3
Herrera6
Saint1
Christopher1
Camden2
Road1
Tube2
Morris3
Rotherhithe1
Raven1
Nest1
Hendon1
Calais1
Glock1
Detective2
Veil1
Market1
Three4
persons
0"Harlow"
1"Quinn"
2"Tomás"
3"Herrera"
4"Saint"
5"Christopher"
6"Morris"
places
0"Dean"
1"Street"
2"Camden"
3"Road"
4"Rotherhithe"
5"Raven"
6"Hendon"
7"Calais"
8"Market"
9"Three"
globalScore1
windowScore1
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences63
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1211
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount1
totalSentences105
matches
0"knew that the"
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs34
mean35.62
std27.39
cv0.769
sampleLengths
050
13
247
353
412
514
662
737
810
96
1093
1145
1265
132
1458
1543
1668
178
1861
199
207
2143
2242
233
2426
25110
269
2744
2868
296
3035
3110
3246
3316
91.50% Passive voice overuse
Target: ≤2% passive sentences
passiveCount4
totalSentences102
matches
0"been kicked"
1"was muffled"
2"been stripped"
3"being stared"
59.65% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount4
totalVerbs190
matches
0"was playing"
1"was weighing"
2"was selling"
3"was examining"
0.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount12
semicolonCount0
flaggedSentences8
totalSentences105
ratio0.076
matches
0"A wheelie bin crashed over in front of her — his work — and she vaulted it without breaking stride, landing in a puddle deep enough to soak her to the shin."
1"That was the trick of grief — it made a body very efficient."
2"At the bottom, a boarded hoarding that said CLOSED — TUBE WORKS."
3"The beam cut into a passage of tiled walls — the old cream-and-maroon of a pre-war Tube station — and at the edge of the light, movement."
4"She killed the torch — it was a lighthouse in here, announcing her — and let her eyes adjust to the greenish glow bleeding up from the bend ahead."
5"The light came from lanterns — real lanterns, with real flames that burned green and didn't flicker."
6"He was reaching into his jacket for something — a token, she saw, pale and carved, held out to a figure in a hooded robe at what she slowly understood was a checkpoint."
7"She pulled her warrant card from her inside pocket, looked at it for a moment — the photo of a younger woman with more hope in her jaw — and tucked it, very carefully, into the lining of her coat where no one could see it."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount1190
adjectiveStacks0
stackExamples(empty)
adverbCount20
adverbRatio0.01680672268907563
lyAdverbCount3
lyAdverbRatio0.0025210084033613447
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences105
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences105
mean11.53
std10.19
cv0.883
sampleLengths
014
116
220
33
43
53
641
74
832
96
104
112
122
133
147
155
169
175
183
1912
2014
2120
2213
237
2413
2517
261
279
286
2925
305
3122
3213
3328
342
3513
3612
3711
387
3922
408
4127
428
432
445
457
463
471
4818
496
55.87% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats13
diversityRatio0.4095238095238095
totalSentences105
uniqueOpeners43
74.07% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount2
totalSentences90
matches
0"Somewhere below and ahead, a"
1"Then Detective Harlow Quinn stepped"
ratio0.022
73.33% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount33
totalSentences90
matches
0"He didn't stop."
1"He never did."
2"She'd known he wouldn't the"
3"She hit the alley."
4"Her radio crackled against her"
5"She slapped it off."
6"She kept her voice level,"
7"He laughed, high and breathless,"
8"She pushed harder, her lungs"
9"He broke out onto the"
10"He kept going, weaving between"
11"They went under the railway"
12"He glanced over his shoulder."
13"His face, for half a"
14"It was the face of"
15"She drew her torch and"
16"She could smell woodsmoke, and"
17"She looked at the gap"
18"He'd be nowhere."
19"He'd be one more name"
ratio0.367
82.22% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount68
totalSentences90
matches
0"Detective Harlow Quinn ran flat-out,"
1"He didn't stop."
2"He never did."
3"She'd known he wouldn't the"
4"She hit the alley."
5"A wheelie bin crashed over"
6"Her radio crackled against her"
7"She slapped it off."
8"Tonight was hers."
9"She kept her voice level,"
10"He laughed, high and breathless,"
11"A good sign."
12"A running man who talked"
13"She pushed harder, her lungs"
14"That was the trick of"
15"He broke out onto the"
16"A black cab blared at"
17"He kept going, weaving between"
18"That was the second sign,"
19"Quinn filed it away and"
ratio0.756
55.56% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount1
totalSentences90
matches
0"By the time she'd finished"
ratio0.011
94.16% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences44
technicalSentenceCount3
matches
0"Three years, almost to the week, since DS Morris had walked into a warehouse in Rotherhithe and walked out in three plastic bags, with a coroner's report that r…"
1"Three years of Quinn building quiet files on the people who'd been in that warehouse and the people who knew those people, a careful pyramid of names with Tomás…"
2"Protocol said wait for backup, for an entry team, for somebody in a high-vis to survey the structural integrity of an abandoned Tube station while Herrera disap…"
0.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags2
uselessAdditionCount1
matches
0"She kept, conversational"
0.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags1
fancyCount1
fancyTags
0"she muttered (mutter)"
dialogueSentences5
tagDensity0.2
leniency0.4
rawRatio1
effectiveRatio0.4
81.2108%