Run: 2026-10-09-01M4FXMKRYRQA3T5PCJBFB4D89

Run Details

Duration:
15.6s
Cost:
$0.001332
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 platform smelled of wet brick and something sweeter underneath, like lilies left too long in a vase. Harlow Quinn stopped at the bottom of the maintenance stairs and let her eyes adjust to the lamp-light that the forensic team had strung along the tunnel wall. Someone had painted a faded ring of white chalk around the body, and the chalk had already been scuffed by a boot. "You're late, Quinn." Detective Inspector Tom Ashby stood near the rusted turnstile with his hands in his coat pockets. He had the flushed look of a man who had been awake since four and expected to be awake until Christmas. "Thought they'd sent the wrong lot down here." "Traffic on the Euston Road." She pulled on a pair of blue nitrile gloves and flexed her fingers. "Who found him?" "Night cleaner at the flats above the old ticket hall. Heard someone shouting down the ventilation shaft around two." Ashby nodded at the body. "Young lad, twenty-two or so. Dealer, by the look of him. Went down the stairs at speed, hit the landing, and then whatever he'd taken got the better of him. Cut powder, probably. We've had three of these in Camden since spring." Quinn crouched at the edge of the chalk ring. The victim lay on his back with his arms flung out, one palm turned up toward the ceiling. His face had gone the grey-violet of a bruise that had stopped growing. His denim jacket was torn at the left shoulder, and the sleeve was dark with dried blood. "Stairs are forty feet from here," she said. "Look at the dust." Ashby sighed. "It's a tunnel, Harlow. It's dust." "It's a layer about an inch thick that hasn't been walked on for years, and it's untouched across the whole platform except for this." She traced the air above a faint line in the grey powder that ran from the foot of the stairs to the body. It was too straight for a fall. It was too straight for a man who had run. "He didn't roll down. Somebody dragged him from the stairs and laid him out like that. Then they walked back up without leaving a single print." "Or he crawled and his mates tidied up after." "His mates didn't tie his laces." She nodded at the boots. The left lace was pulled into a neat double knot, the loops even, the ends trimmed square. "Nobody sprints down a staircase in the dark and stops to do that." Ashby shifted his weight. "Your point being?" "Someone wanted him found exactly like this." Quinn pulled her torch from her belt and played the beam across the victim's open palm. In the creases of his skin, half-buried in grey dust that had collected there like flour, lay a faint impression. It was narrow and curved, a smooth ridge with a notch at one end, the kind of mark a hard object leaves when it is pressed tight for a long time. "What was in his hand?" "Nothing. Bag of wraps, maybe. We've bagged what was in his pockets." "Then bag the dust in his palm before the photographers stomp on it." She stood, knees cracking, and her left wrist caught the light. The leather strap of her watch had worn pale where it sat against the bone. The second hand ticked on. Its hour and minute hands read ten past seven, though the platform clock had been dead for decades. She glanced at the wall above the turnstile, where a row of old ceramic tiles had been stripped back to bare brick. Fresh scrapes ran through the black soot. "And what's that?" Ashby followed her gaze. "Vandals. Half this station's covered in them." "Vandals don't gouge brick at the height of a man's chest in a neat line." She stepped closer, careful of the chalk. A small brass object lay wedged in the crack beneath the scraped bricks, the casing furred with green verdigris. Quinn didn't touch it. Instead she tilted her head and read the faint etchings on its face, a ring of spiky marks she couldn't name and had seen once before in a case file she was not supposed to have photographed. She breathed in through her nose. The lily smell was stronger here, sharp at the back of her throat. "Ashby. Who had the call on the ventilation shaft?" "Duty sergeant. Why?" "Because I want to know what the cleaner heard shouting down that shaft." She looked from the scraped wall to the body and back again, and the pieces slid together with the cold clarity she had learned to trust over eighteen years on the job. The dust had been disturbed once and only once, by someone who knew precisely where to step. The compass, if that was what it was, pointed at the brick. "Because I don't think he fell into this tunnel. I think somebody brought him through the wall."
created_at"2026-10-09T08:49:23.236Z" 10/9/2026, 8:49:23 AM
model"anthropic/claude-haiku-5.5-20261007"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency2907
moderation_latency(null)
generation_time15543
tokens_prompt1112
tokens_completion1349
native_tokens_prompt1597
native_tokens_completion2344
native_tokens_completion_images(null)
native_tokens_reasoning784
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"
usage0.0013317
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.21.0; linux; x64))"
http_referer(null)
request_id"req-1791535763-6WL9TjqTRy5yqhR9Fma8"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1791535763-VsCPNWIeOPZMZIo7ziUC"
upstream_id"msg_011CfrNiscfgdRYsyTXfE7tK"
provider_responses
0
endpoint_id"b6cdf493-3a61-441f-a134-e7944fddb980"
id"msg_011CfrNiscfgdRYsyTXfE7tK"
is_byokfalse
latency686
model_permaslug"anthropic/claude-haiku-5.5-20261007"
provider_name"Claude Platform on AWS"
status200
total_cost0.0013317
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
totalTags10
adverbTagCount0
adverbTags(empty)
dialogueSentences26
tagDensity0.385
leniency0.769
rawRatio0
effectiveRatio0
93.96% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount828
totalAiIsmAdverbs1
found
0
adverb"precisely"
count1
highlights
0"precisely"
80.00% AI-ism character names
Target: 0 AI-default names (17 tracked, −20% each)
codexExemptions(empty)
found
0"Lily"
100.00% AI-ism location names
Target: 0 AI-default location names (33 tracked, −20% each)
codexExemptions(empty)
found(empty)
87.92% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount828
totalAiIsms2
found
0
word"traced"
count1
1
word"weight"
count1
highlights
0"traced"
1"weight"
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
narrationSentences38
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount0
narrationSentences38
filterMatches
0"watch"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences54
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen47
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords828
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions3
unquotedAttributions0
matches(empty)
100.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions13
wordCount547
uniqueNames6
maxNameDensity0.91
worstName"Ashby"
maxWindowNameDensity2
worstWindowName"Ashby"
discoveredNames
Camden1
Quinn4
Inspector1
Tom1
Ashby5
Christmas1
persons
0"Quinn"
1"Inspector"
2"Tom"
3"Ashby"
places(empty)
globalScore1
windowScore1
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences30
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount828
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences54
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs20
mean41.4
std32.98
cv0.797
sampleLengths
069
148
221
366
457
512
68
790
89
941
107
1179
1212
1394
1411
1582
1619
179
183
1991
49.86% Passive voice overuse
Target: ≤2% passive sentences
passiveCount6
totalSentences38
matches
0"been scuffed"
1"was torn"
2"was pulled"
3"been stripped"
4"been disturbed"
5"was, pointed"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs83
matches(empty)
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences54
ratio0
matches(empty)
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount550
adjectiveStacks0
stackExamples(empty)
adverbCount12
adverbRatio0.02181818181818182
lyAdverbCount3
lyAdverbRatio0.005454545454545455
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences54
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences54
mean15.33
std10.77
cv0.702
sampleLengths
019
128
222
319
421
58
618
73
824
942
109
1118
1213
1317
148
154
162
176
1847
197
2010
2126
229
2311
2417
2513
264
273
2823
2920
3031
315
3212
3324
3415
355
3618
3722
387
393
404
417
4222
4319
444
4537
466
4713
489
493
85.80% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats7
diversityRatio0.5925925925925926
totalSentences54
uniqueOpeners32
92.59% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount1
totalSentences36
matches
0"Instead she tilted her head"
ratio0.028
53.33% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount15
totalSentences36
matches
0"He had the flushed look"
1"She pulled on a pair"
2"His face had gone the"
3"His denim jacket was torn"
4"She traced the air above"
5"It was too straight for"
6"It was too straight for"
7"She nodded at the boots"
8"It was narrow and curved,"
9"She stood, knees cracking, and"
10"Its hour and minute hands"
11"She glanced at the wall"
12"She stepped closer, careful of"
13"She breathed in through her"
14"She looked from the scraped"
ratio0.417
1.67% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount33
totalSentences36
matches
0"The Camden platform smelled of"
1"Harlow Quinn stopped at the"
2"Someone had painted a faded"
3"Detective Inspector Tom Ashby stood"
4"He had the flushed look"
5"She pulled on a pair"
6"Ashby nodded at the body"
7"Quinn crouched at the edge"
8"The victim lay on his"
9"His face had gone the"
10"His denim jacket was torn"
11"She traced the air above"
12"It was too straight for"
13"It was too straight for"
14"She nodded at the boots"
15"The left lace was pulled"
16"Ashby shifted his weight."
17"Quinn pulled her torch from"
18"It was narrow and curved,"
19"She stood, knees cracking, and"
ratio0.917
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences36
matches(empty)
ratio0
67.67% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences19
technicalSentenceCount2
matches
0"His face had gone the grey-violet of a bruise that had stopped growing."
1"In the creases of his skin, half-buried in grey dust that had collected there like flour, lay a faint impression."
25.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags10
uselessAdditionCount2
matches
0"She stood, knees cracking, and her left wrist caught the light"
1"She looked, and the pieces slid together with the cold clarity she had learned to trust over eighteen years on the job"
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags1
fancyCount0
fancyTags(empty)
dialogueSentences26
tagDensity0.038
leniency0.077
rawRatio0
effectiveRatio0
84.5937%