Run: 2026-10-08-01M4E17Z5YQBR4MSNCH66P9W4R

Run Details

Duration:
19.2s
Cost:
$0.001504
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 disused platform smelled of wet brick and something sweeter underneath, like lilies left too long in a vase. Harlow Quinn ducked beneath the blue tape at the foot of the escalator shaft and let her torch find the tiles. Someone had painted the old station name over with a sheet of cream enamel, and that paint had blistered in a ring the size of a dinner plate, right where the body lay. "Watch your feet, ma'am," said the constable at the barrier. "Forensics has marked the route but they're still arguing about the lights." "Who found him?" "Two lads from the Camden Lock lot. Came down to sleep rough and found him sitting up against the wall like he'd nodded off." Quinn nodded and kept walking. Her boots found the centre of the line of yellow markers without her looking for them. DI Tom Varley was already crouched beside the body, his coat collar turned up against a draught that Quinn could not feel. He had a flask in one hand and a face that suggested the flask had been a poor decision. "Harlow. Thought you'd be here sooner. Did they tell you it's a bit grim?" "They told me a man died in a Tube station that closed in 1987." She stopped at the edge of the enamel ring. "Who put the tape up?" "I did. Once I saw him." Varley stood, knees cracking. "Look, it's simple enough. Bloke's maybe forty, in his coat, no ID. Liver's probably shot from the look of his face. He came down here to get out of the rain, drank himself stupid, and the stairs or the cold did the rest. Bit of a mess on the wall, but squatters have been doing God knows what down here for years." Quinn said nothing. She crouched at the body's side and took in the details the way her old sergeant had taught her, one at a time, without hurrying. The man's trousers were soaked to the thigh. His boots were dry, the laces tied in a neat double knot. His coat had a clean lapel and a tear at the left elbow that had not yet frayed. No bottles. No cigarette ends. Nothing in his pockets but a wallet with cash and an expired bus pass. Around his neck hung a cord of waxed black thread, and at the end of it, a small piece of carved bone, yellowed and polished smooth by a thumb. "Did you bag that?" she asked. "Not yet. Forensics wants to photograph everything in situ first." "Then tell them to hurry. That's a bone token. You don't buy one at a corner shop." Varley let out a short laugh. "Harlow, come on. It's a bit of carved trinket. Lots of people wear those. Ex-army types, hippies, whatever." "Are you going to tell me he was a hippy with wet trousers and dry boots?" "I'm going to tell you he sat in a puddle." Quinn leaned closer. The man's right hand was curled against his chest, fingers locked around something small. She did not touch it. She shone the torch over his knuckles, where the skin had split and crusted over, and she saw the faint green bloom along the brass edge of an object clutched within them. "What's he holding?" Varley sighed and crouched beside her again. "Compass, looks like. Old thing. Those are common enough at antique fairs." "Look at the face." Quinn angled the light. Fine lines had been cut into the brass dial, rings within rings, and the markings were not any sort of compass rose she recognised. Verdigris clung to the casing like frost. "Right, so he's a bit of a nerd with an old compass. Still doesn't mean anything." "Does it still point north?" "What?" "Look at the needle, Tom." Varley squinted. The needle lay quivering against the glass, trembling as though a current ran through it, and it swung slowly toward the far end of the platform, toward the black mouth of the tunnel where the rails disappeared. "It's probably just the damp," Varley said. "Then why does it keep turning toward the wall?" Quinn stood and walked the length of the platform with the torch sweeping low. The boot prints in the grime were all heading one way, from the stairs toward the tiled wall at the far end, and not one of them came back. She stopped in front of the wall. The tiles there had been scorched in a pattern of overlapping arcs, faint and sooty, the sort of marks left by a candle burning down in a single spot for hours. Someone had drawn a chalk circle on the floor in front of them. The chalk had smeared, but it had not been scuffed by a shoe. Something had been stepped over it instead, carefully, and then the line had been left alone. "Harlow," Varley called from behind her. "You're doing the face." "I'm counting." "Counting what?" "Footprints." She knelt and aimed the light at the one clean print in the dust just beyond the circle. It was narrow, a woman's boot, the heel worn down on the outside. "Three sets going in. Only the dead man's coming out, and he's not walking, he's dragged. The ones that went through the wall never came back the same way." Varley came up beside her and breathed out slowly. "That's not possible." "No," Quinn said. She straightened, and her left wrist caught the torchlight as she shifted her weight. The leather strap of her watch had worn pale where her pulse sat. "It isn't. So either somebody was very careful with a very good story, or the man walked into the wall on his own and somebody came down afterwards to clean up what he left behind." She looked at the compass in the dead man's hand, its needle still pulling toward the tiles like a dog straining at a lead. "Now," she said quietly. "Who taught him how to find the way in?"
created_at"2026-10-08T15:13:54.404Z" 10/8/2026, 3:13:54 PM
model"anthropic/claude-haiku-5.5-20261007"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency3507
moderation_latency(null)
generation_time19140
tokens_prompt1112
tokens_completion1768
native_tokens_prompt1597
native_tokens_completion2689
native_tokens_completion_images(null)
native_tokens_reasoning818
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"
usage0.0015042
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.21.0; linux; x64))"
http_referer(null)
request_id"req-1791472434-vJBlXkPsQ0XRAGDfdPVK"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1791472434-rVB3V8eYIIyrZP2uoGj8"
upstream_id"msg_011CfpzEe5z31iTh4P6GTBSU"
provider_responses
0
endpoint_id"b6cdf493-3a61-441f-a134-e7944fddb980"
id"msg_011CfpzEe5z31iTh4P6GTBSU"
is_byokfalse
latency1344
model_permaslug"anthropic/claude-haiku-5.5-20261007"
provider_name"Claude Platform on AWS"
status200
total_cost0.0015042
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
totalTags9
adverbTagCount1
adverbTags
0"she said quietly [quietly]"
dialogueSentences35
tagDensity0.257
leniency0.514
rawRatio0.111
effectiveRatio0.057
75.10% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1004
totalAiIsmAdverbs5
found
0
adverb"slowly"
count2
1
adverb"carefully"
count1
2
adverb"very"
count2
highlights
0"slowly"
1"carefully"
2"very"
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)
90.04% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1004
totalAiIsms2
found
0
word"weight"
count1
1
word"pulse"
count1
highlights
0"weight"
1"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
narrationSentences48
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount0
narrationSentences48
filterMatches
0"watch"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences73
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen62
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1004
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions12
unquotedAttributions0
matches(empty)
87.21% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions18
wordCount637
uniqueNames4
maxNameDensity1.26
worstName"Quinn"
maxWindowNameDensity2
worstWindowName"Quinn"
discoveredNames
Quinn8
Tom1
Varley8
Fine1
persons
0"Quinn"
1"Tom"
2"Varley"
3"Fine"
places(empty)
globalScore0.872
windowScore1
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences34
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1004
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences73
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs38
mean26.42
std25.76
cv0.975
sampleLengths
073
122
23
324
421
541
614
728
872
928
1057
1129
126
1310
1417
1524
1616
1710
1854
193
2019
2139
2216
235
241
255
2639
277
289
29123
3010
312
322
3361
3412
3565
3624
3713
68.71% Passive voice overuse
Target: ≤2% passive sentences
passiveCount5
totalSentences48
matches
0"were soaked"
1"was curled"
2"been scorched"
3"been scuffed"
4"been stepped"
5"been left"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs96
matches(empty)
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences73
ratio0
matches(empty)
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount637
adjectiveStacks0
stackExamples(empty)
adverbCount18
adverbRatio0.0282574568288854
lyAdverbCount4
lyAdverbRatio0.006279434850863423
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences73
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences73
mean13.75
std10.78
cv0.784
sampleLengths
019
121
233
310
412
53
624
75
816
922
1019
1114
1223
135
1410
1562
163
1725
188
1912
2018
212
223
2314
2429
256
2610
2717
286
2918
3016
3110
323
3314
345
3532
363
377
3812
398
4024
417
4216
435
441
455
462
4737
487
499
82.65% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats3
diversityRatio0.5205479452054794
totalSentences73
uniqueOpeners38
0.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount0
totalSentences43
matches(empty)
ratio0
89.77% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount14
totalSentences43
matches
0"Her boots found the centre"
1"He had a flask in"
2"She stopped at the edge"
3"She crouched at the body's"
4"His boots were dry, the"
5"His coat had a clean"
6"She did not touch it."
7"She shone the torch over"
8"She stopped in front of"
9"She knelt and aimed the"
10"It was narrow, a woman's"
11"She straightened, and her left"
12"She looked at the compass"
13"she said quietly"
ratio0.326
18.14% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount38
totalSentences43
matches
0"The disused platform smelled of"
1"Harlow Quinn ducked beneath the"
2"Someone had painted the old"
3"Quinn nodded and kept walking."
4"Her boots found the centre"
5"He had a flask in"
6"She stopped at the edge"
7"Varley stood, knees cracking"
8"Quinn said nothing."
9"She crouched at the body's"
10"The man's trousers were soaked"
11"His boots were dry, the"
12"His coat had a clean"
13"Nothing in his pockets but"
14"Varley let out a short"
15"Quinn leaned closer."
16"The man's right hand was"
17"She did not touch it."
18"She shone the torch over"
19"Varley sighed and crouched beside"
ratio0.884
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences43
matches(empty)
ratio0
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences25
technicalSentenceCount1
matches
0"The needle lay quivering against the glass, trembling as though a current ran through it, and it swung slowly toward the far end of the platform, toward the bla…"
69.44% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags9
uselessAdditionCount1
matches
0"Varley stood, knees cracking"
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags5
fancyCount0
fancyTags(empty)
dialogueSentences35
tagDensity0.143
leniency0.286
rawRatio0
effectiveRatio0
86.0353%