Run: 2026-04-24-01KQ0GGQ8XPC5NSY0J3N670HXK

Run Details

Duration:
30.7s
Cost:
$0.062325
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="4414" name="Eva Kowalski" aliases="Eva, Evie" pronouns="she/her" species="Human" storyRole="Best Friend"> <eyeColor>green</eyeColor> <hair>curly red</hair> <height>5'4"</height> <age>26</age> <glasses>round glasses</glasses> <satchel>worn leather satchel full of books</satchel> <freckles>freckled complexion</freckles> <nervousHabit>tucking hair behind her left ear</nervousHabit> <description>Aurora's childhood friend and an occult researcher.</description> <backstory>Moved to London two years before Aurora and works as a research assistant at the British Museum's restricted archives. She holds a master's degree in Ancient History from Oxford.</backstory> </character> <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> <item id="2004" name="Veil Compass" aliases="the Compass, shadow compass" type="Tool" origin="The Veil Market"> <casingMaterial>small brass compass</casingMaterial> <faceMarkings>face etched with protective sigils</faceMarkings> <needle>points toward the nearest supernatural rift or portal</needle> <patina>casing has a patina of verdigris</patina> <creator>crafted by a Shade artisan</creator> <description>A compass attuned to supernatural energy.</description> </item> </codex> Continue the story using the following instructions: <instructions> Write a fully fleshed out scene of at least 1000 words in the mystery genre. A detective arrives at a crime scene in an unusual location. Something is wrong — the evidence doesn't add up. A colleague is present, offering a different interpretation. Through careful observation and deduction, the detective begins to see what others have missed. 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 had stopped an hour ago, but the platform still smelled of it — wet concrete, wet iron, something mineral and old underneath. Quinn ducked beneath the tape and descended the final flight of stairs into Aldwych Station, her torch beam sliding across tiles the colour of nicotine. "Bit far from the beat, guv." DC Patel was leaning against a pillar near the body, notepad open, biro clicking in his free hand. He was young enough to still find decommissioned Tube stations exciting. Quinn hadn't been young for a long time. "Who found him?" "Urbex kid. Came down through the lift shaft on a dare. Puked on the southbound tracks, then rang 999." Patel nodded toward the corpse laid out near the tiled wall. "White male, late thirties. No ID. Uniform's running prints." Quinn crouched. The dead man lay on his back, one arm flung wide, the other folded across his chest as though he'd been trying to hold something in. No blood pooled beneath him. His eyes were open and dry, the whites gone the colour of parchment. "Cause of death?" "SOCO's guessing cardiac. No visible trauma, no ligature marks, no defensive injuries. Wallet still in his pocket, sixty quid cash. Watch on his wrist, not cheap." Patel clicked the biro. "Looks like he came down here for a laugh and his heart packed it in." "Does it." She ran her torch across the tiles behind him. The paint had gone to chalk decades ago, and the walls wore a grey fur of dust wherever the damp hadn't stripped them. Except for a ring, roughly the diameter of a dinner plate, at chest height on the wall above the body. Dust wiped clean. A single smudge of something darker at its centre. "Patel. What do you make of that?" He followed her beam. "Where?" "The wall. Eight inches above his head." He squinted. "Could be anything. Rats." "Rats don't polish." Quinn straightened and stepped closer, careful of where she put her boots. The mark at the centre was a fingerprint — a thumb, she thought, pressed flat, the whorl set into a residue that glittered faintly when the torch caught it at an angle. Not blood. Not oil. Something in between. "You been up close?" "Gave it the usual walkthrough, guv." "Gloves on." She pulled her own from her coat pocket and crouched again, bringing her face within a foot of the dead man's. The parchment in his eyes wasn't a trick of the light; the sclera had taken on the grain of dried paper. His pupils were blown wide and stayed wide, as if stuck open. She touched the back of her hand to his cheek. Cold, obviously, but more than cold — dry in a way skin shouldn't be. Like driftwood. "How long's he been down here?" "Kid found him two hours ago. Pathologist reckons between six and nine." "Six and nine hours and he's already leathered up." She sat back on her heels. "That's not right." "Damp air down here might—" "Damp air does the opposite, Patel." She swept the torch down the body. The trouser cuffs were filthy from the tiles, but the shoes — brown brogues, expensive — were clean on the soles. Almost spotless. She turned one gently with a gloved finger. A thin crust of pale grey mud clung to the welt, but the leather underneath hadn't been walked on in any real sense. No scuff on the heel, no grit pressed into the rubber. "He didn't walk in." Patel looked up from his pad. "Sorry?" "His shoes. He didn't walk down those stairs. He didn't walk the platform. Whoever put him here carried him, or—" She stopped. "Carried him." "Guv, the lift shaft's welded shut. Stairs are the only way in, and the stairs are filthy. If someone dragged him, we'd see it." "We'd see something." Quinn stood and turned slowly on the spot. The platform stretched away on either side, a long grey mouth. Her torch beam found an old tiled sign — TO TRAINS — and beneath it, the scuff and shuffle of modern footprints where SOCO had come through. Beyond that zone the dust lay undisturbed as a snowfield. She walked the other way, past the body, past the pillar where Patel had been leaning. The dust there was clean too. No drag marks. No second set of prints. "He came from nowhere," she said aloud. "Urbex kid's trainers are all over the south end. He could've—" "The kid found him, Patel. He didn't carry a fourteen-stone corpse down six flights and lay him out like a church brass." "Then what's your theory, guv?" She didn't answer yet. She came back to the ring on the wall and lifted the torch until the beam raked across the tiles at a shallow angle. The dust there wasn't just wiped. It was pushed outward, radially, as though something had punched through and displaced the air. A fine pattern of it lay on the platform below, a crescent of grey powder that matched the mud crusted on the dead man's shoes. She thought about the mud. Pale grey, almost chalky. The tiles here were white; the dust here was white. This grey was something else. Somewhere else. "Patel." "Guv." "Call it in as suspicious. I want the scene sealed for another twenty-four hours, and I want the pathologist to check his lungs for anything that isn't London air. Specifically, I want a soil sample off those brogues." "You think he was killed elsewhere and dumped." "I think he was killed elsewhere." She paused. "I'm not sure dumped is the word." Patel gave her the look he reserved for her worse hunches — polite, patient, quietly unconvinced. "What else would you call it?" Quinn let the torch beam settle again on the ring of cleaned tile. The fingerprint at its centre caught the light and, for half a breath, seemed to sit slightly proud of the wall, as though pressed from the inside. "Delivered," she said. Her watch ticked against her wrist. She rolled the cuff down over it and took out her phone. "Get me Eva Kowalski's number. British Museum. Restricted archives." Patel frowned. "Guv?" "Just get it."
created_at"2026-04-24T19:47:24.065Z" 4/24/2026, 7:47:24 PM
model"anthropic/claude-4.7-opus-20260416"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency2297
moderation_latency(null)
generation_time30228
tokens_prompt1149
tokens_completion1599
native_tokens_prompt1600
native_tokens_completion2173
native_tokens_completion_images(null)
native_tokens_reasoning58
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"
usage0.062325
router(null)
provider_responses
0
endpoint_id"0fa65117-00d9-4835-808d-9b68041d9ce4"
id"27f4a86b-9dad-4681-9bfc-713922551608"
is_byokfalse
latency1810
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-1777060044-eOvYCpv54N0Q40EGlmKT"
session_id(null)
api_type"completions"
id"gen-1777060044-iGQErUDD5SRVX6HyQP6h"
upstream_id"27f4a86b-9dad-4681-9bfc-713922551608"
total_cost0.062325
cache_discount(null)
upstream_inference_cost0
provider_name"Amazon Bedrock"
response_cache_source_id(null)

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags7
adverbTagCount2
adverbTags
0"She sat back [back]"
1"she said aloud [aloud]"
dialogueSentences43
tagDensity0.163
leniency0.326
rawRatio0.286
effectiveRatio0.093
85.44% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1030
totalAiIsmAdverbs3
found
0
adverb"gently"
count1
1
adverb"slowly"
count1
2
adverb"slightly"
count1
highlights
0"gently"
1"slowly"
2"slightly"
80.00% AI-ism character names
Target: 0 AI-default names (17 tracked, −20% each)
codexExemptions(empty)
found
0"Patel"
100.00% AI-ism location names
Target: 0 AI-default location names (33 tracked, −20% each)
codexExemptions(empty)
found(empty)
95.15% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1030
totalAiIsms1
found
0
word"blown wide"
count1
highlights
0"blown wide"
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
narrationSentences65
matches(empty)
98.90% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount1
narrationSentences65
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)
analyzedSentences101
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen39
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1038
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions6
unquotedAttributions0
matches(empty)
100.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions16
wordCount703
uniqueNames5
maxNameDensity1
worstName"Patel"
maxWindowNameDensity2
worstWindowName"Quinn"
discoveredNames
Aldwych1
Station1
Patel7
Tube1
Quinn6
persons
0"Patel"
1"Quinn"
places
0"Aldwych"
globalScore1
windowScore1
90.48% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences42
glossingSentenceCount1
matches
0"Cold, obviously, but more than cold"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1038
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences101
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs50
mean20.76
std23.11
cv1.113
sampleLengths
049
16
237
33
439
546
63
745
82
964
107
115
127
136
143
1551
164
176
182
1980
206
2112
2218
235
246
2572
264
277
2824
2924
303
3186
327
3311
3422
355
3674
3726
381
391
4038
418
4215
4322
4440
453
4618
479
483
493
89.07% Passive voice overuse
Target: ≤2% passive sentences
passiveCount3
totalSentences65
matches
0"were blown"
1"been walked"
2"was pushed"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs111
matches(empty)
0.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount8
semicolonCount2
flaggedSentences8
totalSentences101
ratio0.079
matches
0"The rain had stopped an hour ago, but the platform still smelled of it — wet concrete, wet iron, something mineral and old underneath."
1"The mark at the centre was a fingerprint — a thumb, she thought, pressed flat, the whorl set into a residue that glittered faintly when the torch caught it at an angle."
2"The parchment in his eyes wasn't a trick of the light; the sclera had taken on the grain of dried paper."
3"Cold, obviously, but more than cold — dry in a way skin shouldn't be."
4"The trouser cuffs were filthy from the tiles, but the shoes — brown brogues, expensive — were clean on the soles."
5"Her torch beam found an old tiled sign — TO TRAINS — and beneath it, the scuff and shuffle of modern footprints where SOCO had come through."
6"The tiles here were white; the dust here was white."
7"Patel gave her the look he reserved for her worse hunches — polite, patient, quietly unconvinced."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount695
adjectiveStacks0
stackExamples(empty)
adverbCount23
adverbRatio0.033093525179856115
lyAdverbCount8
lyAdverbRatio0.011510791366906475
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
mean10.28
std8.6
cv0.836
sampleLengths
024
125
26
318
411
58
63
730
89
92
1026
115
1213
133
1430
1515
162
179
1823
1920
203
219
227
234
241
257
262
274
283
2912
3032
312
322
333
344
356
362
3721
3821
3912
4010
4114
422
436
4412
4515
463
475
486
497
80.86% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats5
diversityRatio0.5148514851485149
totalSentences101
uniqueOpeners52
61.73% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount1
totalSentences54
matches
0"Pale grey, almost chalky."
ratio0.019
79.26% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount19
totalSentences54
matches
0"He was young enough to"
1"His eyes were open and"
2"She ran her torch across"
3"He followed her beam."
4"She pulled her own from"
5"His pupils were blown wide"
6"She touched the back of"
7"She sat back on her"
8"She swept the torch down"
9"She turned one gently with"
10"Her torch beam found an"
11"She walked the other way,"
12"she said aloud"
13"She didn't answer yet."
14"She came back to the"
15"It was pushed outward, radially,"
16"She thought about the mud."
17"Her watch ticked against her"
18"She rolled the cuff down"
ratio0.352
34.07% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount46
totalSentences54
matches
0"The rain had stopped an"
1"Quinn ducked beneath the tape"
2"DC Patel was leaning against"
3"He was young enough to"
4"Quinn hadn't been young for"
5"Patel nodded toward the corpse"
6"The dead man lay on"
7"His eyes were open and"
8"Patel clicked the biro"
9"She ran her torch across"
10"The paint had gone to"
11"Dust wiped clean."
12"A single smudge of something"
13"He followed her beam."
14"Quinn straightened and stepped closer,"
15"The mark at the centre"
16"Something in between."
17"She pulled her own from"
18"The parchment in his eyes"
19"His pupils were blown wide"
ratio0.852
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences54
matches(empty)
ratio0
71.43% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences30
technicalSentenceCount3
matches
0"The dead man lay on his back, one arm flung wide, the other folded across his chest as though he'd been trying to hold something in."
1"The mark at the centre was a fingerprint — a thumb, she thought, pressed flat, the whorl set into a residue that glittered faintly when the torch caught it at a…"
2"A fine pattern of it lay on the platform below, a crescent of grey powder that matched the mud crusted on the dead man's shoes."
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags7
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags2
fancyCount0
fancyTags(empty)
dialogueSentences43
tagDensity0.047
leniency0.093
rawRatio0
effectiveRatio0
85.5459%