Run: 2026-10-09-01M4FYY16CJ3BQAESBK7TPZ8EC

Run Details

Duration:
16.0s
Cost:
$0.001372
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="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 Camden Town platform had been dead for sixty years, and it smelled like it. Harlow Quinn stepped off the last rung of the service ladder into a fug of wet brick, old cigarette smoke, and something sweeter underneath that she couldn't name. Above her, the lamps strung along the tunnel mouth flickered in a rhythm that matched no electrical fault she had ever seen. "Ma'am." Detective Constable Pete Lassiter came down the platform toward her, his torch sweeping the tiles in short, nervous arcs. "You'll want to see this before the lads from forensics start treading all over it." "Who found him?" "Urban explorer. Two lads with a drone and a death wish. They rang it in at six." Quinn pulled on fresh gloves and followed the beam. The body lay at the foot of the stairwell that once carried commuters up to the street, arms flung wide, a man in his thirties in a charcoal wool coat that had cost more than her boots. His eyes were open. Frost had feathered the edges of his lashes. Frost. Underground, in August, with the air thick enough to chew. "Your DI's already got a theory," Lassiter said. "Has he." Detective Inspector Graham Sowerby emerged from the shadows by the ticket hall, thumbs hooked into his stab vest. He had the look of a man who had already written the report in his head and was only waiting for the coroner to agree with him. "Harlow. Good. Saves me ringing you. Drugs, clear as day. Look at the kit." He nodded toward a scatter of items on the tiles: a syringe, a blackened spoon, a glass vial no bigger than a fingertip, its cork stopper missing. "Overdose," Sowerby said. "Fell down the stairs off his face. Happens every other week in this city." "Does it?" Quinn crouched beside the body. "Then tell me why his shoes are dry." Sowerby opened his mouth and closed it again. She angled her torch across the platform. The floor glistened everywhere, black water seeping from cracks in the concrete, pooling in the gutters where the rails had long since been pulled. Every footprint she could see was a ghost of wet grey sole pressed into dust. The man's Oxford brogues were polished and bone dry, not a single speck of grime on the welt. "He walked here from somewhere that wasn't wet," she said. "Which means he didn't come down the tunnel. Which means he came in another way." "Or the lads who found him had a poke around and wiped things," Sowerby said. "Lassiter, did you touch the body?" "Only to check for a pulse, ma'am. Cold as a fridge." "Good lad." She turned back to the corpse. "Look at his left wrist." Lassiter knelt beside her, shining the torch where she pointed. A thin gold watch sat on the dead man's arm, its face cracked straight across. The hands had stopped at twenty past three. "Battery?" Lassiter offered. "Mechanical. Expensive. Those don't stop on their own, and they certainly don't crack like that from a stair fall without the strap tearing." She leaned closer. The crystal had fractured outward from the centre in a neat star, the way ice does on a pond when someone drops a stone onto it from above. "Something hit it from the inside." Sowerby snorted. "You're reading tea leaves." "Am I?" She stood and walked the length of the platform, her own watch ticking against her wrist, the scarred leather strap creaking as she flexed it. Halfway along, a circle had been scraped into the grime on the tiles, roughly two metres across. Inside it, someone had drawn lines with what looked like chalk or powdered bone, and the lines formed a pattern of interlocking marks she didn't recognise. Not runes. Not any alphabet in the reference books she'd studied in training. Some of the marks had been smudged by a heel, the rest were intact. At the edge of the circle sat a small brass object, green-stained at the rim where time had worked on it. Quinn crouched and didn't touch it. It was a compass. The glass was cracked, but the face had been etched with tiny symbols running around the rim, the same shapes she could see on the floor. The needle was not still. It trembled in a slow, insistent arc, swinging toward the far end of the platform where the tunnel wall was bricked over, then snapping back toward the stairs, then swinging again, as though something beyond the wall kept calling it. "Ma'am, what is that?" Lassiter asked from behind her, uneasy now. "Evidence," she said. "Bag it separately. Don't let anyone else near it, and for God's sake don't let anyone open it." "Sowerby's going to have a fit." "Sowerby is going to have a fit regardless." She straightened, rolling the stiffness out of her shoulders. "Tell me something. Did you see the ticket hall on the way in?" "Yes, ma'am. Padlocked, boarded up." "Padlocked from which side?" Lassiter frowned, working it through. "The outside. Why?" "Because the stairs lead up to a street that's been closed for years. Nobody comes down here by the front door." She looked at the frost on the dead man's lashes, at the dry shoes, at the stopped watch, at the mark on the floor that had been drawn with care by someone who knew exactly what they were doing. "He didn't fall down those stairs, Pete. He came up them, and whatever he came up for wasn't finished with him yet." Across the platform, the needle swung again toward the bricked-up wall, and the lamps overhead dimmed in unison.
created_at"2026-10-09T09:12:00.468Z" 10/9/2026, 9:12:00 AM
model"anthropic/claude-haiku-5.5-20261007"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency3022
moderation_latency(null)
generation_time15987
tokens_prompt1112
tokens_completion1588
native_tokens_prompt1597
native_tokens_completion2424
native_tokens_completion_images(null)
native_tokens_reasoning544
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"
usage0.0013717
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.21.0; linux; x64))"
http_referer(null)
request_id"req-1791537120-53QZ8mV6G7ezU3xzOJ8z"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1791537120-rsJuea9g0Wvi7E6wlsED"
upstream_id"msg_011CfrQSvScxVBkHk3GmWcvr"
provider_responses
0
endpoint_id"b6cdf493-3a61-441f-a134-e7944fddb980"
id"msg_011CfrQSvScxVBkHk3GmWcvr"
is_byokfalse
latency744
model_permaslug"anthropic/claude-haiku-5.5-20261007"
provider_name"Claude Platform on AWS"
status200
total_cost0.0013717
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
totalTags13
adverbTagCount1
adverbTags
0"She turned back [back]"
dialogueSentences34
tagDensity0.382
leniency0.765
rawRatio0.077
effectiveRatio0.059
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount945
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)
62.96% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount945
totalAiIsms7
found
0
word"flickered"
count1
1
word"pulse"
count1
2
word"mechanical"
count1
3
word"crystal"
count1
4
word"fractured"
count1
5
word"etched"
count1
6
word"trembled"
count1
highlights
0"flickered"
1"pulse"
2"mechanical"
3"crystal"
4"fractured"
5"etched"
6"trembled"
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
narrationSentences49
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount0
hedgeCount0
narrationSentences49
filterMatches(empty)
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences70
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen60
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords945
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions8
unquotedAttributions0
matches(empty)
100.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions25
wordCount661
uniqueNames12
maxNameDensity0.91
worstName"Lassiter"
maxWindowNameDensity2
worstWindowName"Sowerby"
discoveredNames
Camden1
Town1
Quinn4
Constable1
Pete1
Lassiter6
August1
Detective2
Inspector1
Graham1
Sowerby5
Oxford1
persons
0"Quinn"
1"Constable"
2"Pete"
3"Lassiter"
4"Inspector"
5"Graham"
6"Sowerby"
places
0"Camden"
1"Town"
2"August"
3"Oxford"
globalScore1
windowScore1
2.94% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences34
glossingSentenceCount2
matches
0"smelled like it"
1"looked like chalk or powdered bone, and t"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount945
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences70
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs36
mean26.25
std25.45
cv0.97
sampleLengths
065
135
23
317
458
511
68
72
859
927
1017
1115
128
1364
1425
1515
166
1711
1813
1933
203
2160
226
232
2495
2527
2675
2711
2821
296
3030
315
324
338
3482
3518
62.30% Passive voice overuse
Target: ≤2% passive sentences
passiveCount6
totalSentences49
matches
0"been pulled"
1"been scraped"
2"been smudged"
3"been etched"
4"was bricked"
5"been drawn"
76.54% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount2
totalVerbs108
matches
0"was only waiting"
1"were doing"
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences70
ratio0
matches(empty)
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount663
adjectiveStacks0
stackExamples(empty)
adverbCount20
adverbRatio0.030165912518853696
lyAdverbCount3
lyAdverbRatio0.004524886877828055
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences70
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences70
mean13.5
std10.52
cv0.779
sampleLengths
015
128
222
320
415
53
617
79
837
94
108
111
1210
138
142
1518
1627
1714
1827
193
2014
217
228
238
247
2524
2615
2718
2810
2915
3015
316
3211
338
345
3510
3615
378
383
3926
4028
416
422
434
442
4525
4617
4726
482
4911
94.29% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats4
diversityRatio0.6571428571428571
totalSentences70
uniqueOpeners46
0.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount0
totalSentences40
matches(empty)
ratio0
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount11
totalSentences40
matches
0"His eyes were open."
1"He had the look of"
2"He nodded toward a scatter"
3"She angled her torch across"
4"She turned back to the"
5"She leaned closer"
6"She stood and walked the"
7"It was a compass."
8"It trembled in a slow,"
9"She straightened, rolling the stiffness"
10"She looked at the frost"
ratio0.275
35.00% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount34
totalSentences40
matches
0"The Camden Town platform had"
1"Harlow Quinn stepped off the"
2"Detective Constable Pete Lassiter came"
3"Quinn pulled on fresh gloves"
4"The body lay at the"
5"His eyes were open."
6"Frost had feathered the edges"
7"Detective Inspector Graham Sowerby emerged"
8"He had the look of"
9"He nodded toward a scatter"
10"Quinn crouched beside the body"
11"Sowerby opened his mouth and"
12"She angled her torch across"
13"The floor glistened everywhere, black"
14"Every footprint she could see"
15"The man's Oxford brogues were"
16"She turned back to the"
17"Lassiter knelt beside her, shining"
18"A thin gold watch sat"
19"The hands had stopped at"
ratio0.85
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences40
matches(empty)
ratio0
80.75% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences23
technicalSentenceCount2
matches
0"Above her, the lamps strung along the tunnel mouth flickered in a rhythm that matched no electrical fault she had ever seen."
1"It trembled in a slow, insistent arc, swinging toward the far end of the platform where the tunnel wall was bricked over, then snapping back toward the stairs, …"
86.54% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags13
uselessAdditionCount1
matches
0"Detective Constable Pete Lassiter came, his torch sweeping the tiles in short, nervous arcs"
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags6
fancyCount0
fancyTags(empty)
dialogueSentences34
tagDensity0.176
leniency0.353
rawRatio0
effectiveRatio0
83.3772%