Run: 2026-10-08-01M4DA87HP03PHRD173RZ2C4G2

Run Details

Duration:
22.2s
Cost:
$0.001778
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 Northern line had been dead for thirty years, and the platform still smelled of it: wet brick, rust, and something sweeter underneath that Harlow Quinn decided not to name yet. Her torch swept the tiles. Someone had painted a cartoon fox on the far wall, and the fox had faded to a ghost of orange, its grin eaten away by damp. "Mind the edge, ma'am," said the uniformed constable at the bottom of the stairs. He kept his eyes on his boots. "Sergeant Tolliver's already down there. Says he's got it sorted." "Has he." Quinn stepped past the cordon tape, the leather of her watch strap cold against her wrist. The station had been sealed behind a steel grille at street level, its padlock so furred with rust it looked grown rather than fitted. Nobody had cut it. Nobody had needed to. The grille had been open for less than an hour, and the dust on its bars had been disturbed only by the cutting team's gloves. Tolliver was crouched beside the body at the platform edge, the way a man crouches when he wants the camera to see him looking thoughtful. He stood as she approached, dusting his knees. "Ma'am. Male, mid-fifties, identification in the inside pocket. Gerald Pryce. Architect, according to the card. Works in Clerkenwell." "What was an architect doing under Camden at two in the morning?" "Pissed, probably." Tolliver nodded at the tracks. "Lost his footing, went over the edge. Caught his head on the rail on the way down. Sad, but it's the sort of thing that happens to people who wander into places they shouldn't." Quinn did not answer. She was looking at the body. Pryce lay on his side with one arm flung out across the gravel of the track bed. His good wool overcoat was clean, not even a scuff at the elbows. His face had a blue tinge at the lips, but there was no blood anywhere, no wound at the temple, no glimmer of the rail damage Tolliver had described. Frost had furred the hairs of his eyebrows, despite the warm August night above ground. "Head wound?" she asked. "Could be concealed by the position." "Could be." She knelt. The torch beam caught his left hand, curled tight around something. A cord, black and waxed, looped between his fingers. "What's he holding?" "Some kind of charm. Bone thing. Took it off him for the bag, but I'd bet on a bit of occult larking. There's a lot of that down here, I'm told. Kids go looking for ghosts." Quinn eased the cord from his grip. The token on the end was a sliver of pale bone, the size of a thumbnail, scored with a spiral of fine lines. Her fingers went cold where they touched it. Not the cold of the tunnel. A sharper cold, like the metal of a railing in January. "Bag it separately," she said. "Gloves on, Ben. Don't let it near your phone." "Ma'am, with respect, it's a bone and a bit of string." "Then it won't mind being labelled." She stood, her knees complaining. "Show me the stairs." They walked the length of the platform, Tolliver's torch jittering over the grime. Quinn kept her light low and angled, the way Morris had taught her years ago, back when they still shared a car and a bad coffee habit. *Shadows tell you what the light is hiding,* he had said, usually while complaining about the heating in the Hendon office. The dust along the platform was thick and grey, untouched except for a single line of prints. Heel first, deliberate, each step placed. They ran from the stairs to the platform edge, where they stopped. Then they didn't return. "He walked in," she said. "Calm. No running, no stumbling." "Pissed men don't stumble neatly, ma'am?" "Pissed men drag their feet. These are even. Someone who knows where he's putting himself." She crouched by the last print. "Look at the depth. He's standing still for a long time before he goes over." "Or he fell asleep on his feet." "Then where did he come from?" Tolliver shifted his weight. "The steps. Obviously." Quinn swept the torch up the concrete staircase. The steps were coated in the same undisturbed dust, and the grille at the top still hung whole, its lock still furred. She followed the dust to the landing, where the only marks were a few gouges from the cutting team's boots. "Nobody has come down those stairs in years," she said. "Not Pryce. Not anyone." "He could have come through the old ventilation shafts. Kids always find a way in." "Kids leave prints in the dust. Pryce left one line, and it goes one way." She turned slowly, the torch lighting the wall beside the empty lift shaft. The tiles there were cracked, and something had been pressed into the grime on the lowest tiles, a faint arc like a finger drawn through sugar. "Something came through that wall. Or he did." Her eyes returned to the compass lying where the constable had kicked it aside near the bottom step. She had missed it on the first pass. Small and brass, its casing dulled with green verdigris, the glass face etched with tight, protective marks. The needle was not still. It trembled, then swung, and settled pointing past the platform, toward the black mouth of the tunnel where the rails ran into darkness. "Ben," she said quietly, "did you find that by his body, or did it roll down here on its own?" Tolliver's torch wavered toward the compass and then away again. Quinn checked her watch. Pryce's watch, she had noticed on the body, had stopped at 2:14. The second hand on hers swept on, steady and indifferent, and she realised she had been holding her breath.
created_at"2026-10-08T08:32:05.695Z" 10/8/2026, 8:32:05 AM
model"anthropic/claude-haiku-5.5-20261007"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency9479
moderation_latency(null)
generation_time22192
tokens_prompt1112
tokens_completion1379
native_tokens_prompt1597
native_tokens_completion3236
native_tokens_completion_images(null)
native_tokens_reasoning1344
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"
usage0.0017777
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.21.0; linux; x64))"
http_referer(null)
request_id"req-1791448325-wWZwe4qScEIrMQ4FaVJ5"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1791448325-XXLG5Znyw7XkDSygHp2o"
upstream_id"msg_011CfpTbUjtGA9CXCwUPZHdB"
provider_responses
0
endpoint_id"b6cdf493-3a61-441f-a134-e7944fddb980"
id"msg_011CfpTbUjtGA9CXCwUPZHdB"
is_byokfalse
latency702
model_permaslug"anthropic/claude-haiku-5.5-20261007"
provider_name"Claude Platform on AWS"
status200
total_cost0.0017777
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
70.97% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags10
adverbTagCount2
adverbTags
0"She turned slowly [slowly]"
1"she said quietly [quietly]"
dialogueSentences31
tagDensity0.323
leniency0.645
rawRatio0.2
effectiveRatio0.129
94.86% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount973
totalAiIsmAdverbs1
found
0
adverb"slowly"
count1
highlights
0"slowly"
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)
69.17% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount973
totalAiIsms6
found
0
word"tinge"
count1
1
word"charm"
count1
2
word"weight"
count1
3
word"etched"
count1
4
word"trembled"
count1
5
word"wavered"
count1
highlights
0"tinge"
1"charm"
2"weight"
3"etched"
4"trembled"
5"wavered"
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
narrationSentences56
matches(empty)
66.33% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount3
hedgeCount0
narrationSentences56
filterMatches
0"watch"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences76
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen36
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans1
markdownWords8
totalWords973
ratio0.008
matches
0"Shadows tell you what the light is hiding,"
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions7
unquotedAttributions0
matches(empty)
98.68% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions19
wordCount682
uniqueNames8
maxNameDensity1.03
worstName"Quinn"
maxWindowNameDensity1.5
worstWindowName"Quinn"
discoveredNames
Northern1
Harlow1
Quinn7
Tolliver6
August1
January1
Morris1
Hendon1
persons
0"Harlow"
1"Quinn"
2"Tolliver"
3"Morris"
places
0"January"
1"Hendon"
globalScore0.987
windowScore1
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences40
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount973
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences76
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs34
mean28.62
std22.42
cv0.783
sampleLengths
062
131
22
373
433
518
612
741
810
974
104
116
1227
1336
1455
1514
1611
1715
1861
1939
2010
216
2236
237
246
257
2650
2714
2815
2962
3071
3120
3210
3335
73.93% Passive voice overuse
Target: ≤2% passive sentences
passiveCount5
totalSentences56
matches
0"been sealed"
1"been open"
2"been disturbed"
3"was crouched"
4"were coated"
5"been pressed"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount1
totalVerbs103
matches
0"was looking"
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences76
ratio0
matches(empty)
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount682
adjectiveStacks0
stackExamples(empty)
adverbCount21
adverbRatio0.030791788856304986
lyAdverbCount5
lyAdverbRatio0.007331378299120235
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences76
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences76
mean12.8
std8.48
cv0.663
sampleLengths
031
15
226
314
47
510
62
716
824
94
104
1125
1225
138
1418
1512
167
1734
184
196
2017
2113
2229
2315
244
256
264
2711
289
293
3036
317
3223
338
346
3511
365
379
3811
3911
404
4113
4227
4321
4417
456
4612
474
485
495
78.07% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats4
diversityRatio0.5
totalSentences76
uniqueOpeners38
65.36% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount1
totalSentences51
matches
0"Then they didn't return."
ratio0.02
86.67% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount17
totalSentences51
matches
0"Her torch swept the tiles."
1"He kept his eyes on"
2"He stood as she approached,"
3"She was looking at the"
4"His good wool overcoat was"
5"His face had a blue"
6"Her fingers went cold where"
7"She stood, her knees complaining"
8"They walked the length of"
9"They ran from the stairs"
10"She crouched by the last"
11"She followed the dust to"
12"She turned slowly, the torch"
13"Her eyes returned to the"
14"She had missed it on"
15"It trembled, then swung, and"
16"she said quietly"
ratio0.333
0.00% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount47
totalSentences51
matches
0"The Northern line had been"
1"Her torch swept the tiles."
2"Someone had painted a cartoon"
3"He kept his eyes on"
4"Quinn stepped past the cordon"
5"The station had been sealed"
6"Nobody had cut it."
7"Nobody had needed to."
8"The grille had been open"
9"Tolliver was crouched beside the"
10"He stood as she approached,"
11"Tolliver nodded at the tracks"
12"Quinn did not answer."
13"She was looking at the"
14"Pryce lay on his side"
15"His good wool overcoat was"
16"His face had a blue"
17"Frost had furred the hairs"
18"The torch beam caught his"
19"A cord, black and waxed,"
ratio0.922
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences51
matches(empty)
ratio0
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences27
technicalSentenceCount0
matches(empty)
75.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags10
uselessAdditionCount1
matches
0"She turned slowly, the torch lighting the wall beside the empty lift shaft"
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags5
fancyCount0
fancyTags(empty)
dialogueSentences31
tagDensity0.161
leniency0.323
rawRatio0
effectiveRatio0
85.9678%