Run: 2026-10-08-01M4DANAF4KSAKS1G7H108S0W5

Run Details

Duration:
17.6s
Cost:
$0.001425
Provider:
Claude Platform on AWS

Model input

System
You are an expert novelist with a gift for vivid, immersive prose. You write in tight third-person limited point of view with a strong narrative voice. Your prose is clean, precise, and engaging — you favor strong verbs, concrete details, and natural-sounding dialogue. You will be given a story bible (codex) containing canonical details about characters, locations, items, and lore. Use these details to ground your writing in the established world. Stay consistent with the codex. Write only the prose of the scene. Do not include titles, chapter headings, markdown formatting, or any commentary before or after the scene.
User/Human
<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> 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.

Model response

AI
The platform smelled of wet brick and something older underneath, like coins kept too long in a pocket. Harlow Quinn stood at the bottom of the stairs with her hands in her coat and let the place settle around her before she moved. Camden Town station had closed to passengers in 1992. The tiles still carried the ghost of a tube map, faded to the color of weak tea, and the advertisements on the far wall had peeled into strips that hung like old bandages. "Ma'am." Detective Inspector Tom Pardoe came down the platform toward her, collar up, a torch in one hand. He had the look of a man who had already decided what he was going to say and wanted to say it before anyone argued. "White male, mid-forties. Found by a council inspector at half five. We think he came in through the old ventilation shaft off Hawley Street." "We think?" "Gate's rusted shut. Someone's been cutting through the mesh, but not recently, if you ask me." He shone the torch down the platform. "Looks like he got high, wandered in, and took a bad fall from the edge. There's a drop onto the rails. Probably caught his head on the lip of the platform on the way down." Quinn walked toward the body without answering. The man lay on his back on the concrete, arms loose at his sides, eyes open. His coat was dry. The tunnel behind him dripped steadily from a dozen cracks in the ceiling, and the floor for ten metres in every direction was slick with condensation, yet his shoes, a pair of good brown brogues, had no water on them at all. She crouched beside him. No blood on the concrete beneath his head. No mark on his scalp when she tilted it gently with a gloved hand. No smell of alcohol, no powder residue at the nostrils, no needle marks she could find. "Fall," Pardoe said behind her. "Concussion. Happens." "Does it?" Quinn studied the man's left hand. It was curled, and when she eased the fingers open, a small, pale object rolled into her palm. Bone, polished smooth and carved with a thin spiral. A token. She had seen one before, in an evidence locker three years ago, and had spent four months trying to forget the tag number attached to it. She set it on the concrete and did not look at Pardoe. Instead she looked at the wrist. His watch had stopped at eleven twelve. The face was cracked, the second hand frozen mid-sweep. But his phone, in the inside pocket of his coat, read 2:41 when she woke the screen, and she did not need a forensics team to tell her that a man who fell at eleven twelve did not lie on a dry coat for three hours in a flooded tunnel. "Someone set that watch," she said. "Or someone wanted us to think they did." "Or the damp got in it." "Pardoe, look at the floor." He did, with the reluctant patience of a man who had been waiting for her to finish. Quinn pointed with her pen to the far end of the platform, where the tiles gleamed under the torchlight. Faint prints ran across the wet surface, long and narrow, the heels deep and the toes barely marked. They came from the stairwell and walked straight toward the far wall, where a tiled panel bore an old ad for a brand of tea that had been out of business since the seventies. They stopped at the wall. There was nothing beyond it but more wall. "Could be the man himself," Pardoe said. "Wandering." "Then he walked into a solid surface and kept walking?" She stood, knees cracking, and moved to the wall. The tiles there were clean. Too clean, in a place where grime had gathered on everything else for thirty years. She ran her fingers along the grout. It was newer than the rest, pale and smooth, as if someone had repaired a seam recently and very carefully. The compass was lying in the dust by the man's boot. She had not noticed it until her eyes passed over the spot a second time. Small, brass, its casing gone green at the edges with verdigris. She crouched and lifted it with two fingers. Its face was etched around the rim with sigils, tight and precise, and she knew at least three of them. They had been in the margins of DS Morris's last notebook, the one she had been given in a plastic bag with his effects, the one she had read every night for a year and still could not explain. The needle was not resting. It turned slowly, trembling, and then swung with a small, decisive click until it pointed at the clean tiles of the far wall. "Ma'am?" Pardoe said. "What's that?" "A compass." Her voice came out level, which pleased her. "It's pointing at something." "At the wall." "At whatever's behind the wall." He laughed, not unkindly. "You can't seriously think there's a room behind it." Quinn did not answer. She was looking at the wet prints again, at the way the heels pressed deep into the tile, the way they stopped dead at the seam in the grout, and she was thinking about the bone token in its evidence bag, and about a man whose watch had stopped at the exact minute someone had decided he should die. Morris had found a seam like this, once, in a building in Holborn. He had described it to her in the car, laughing at himself, and then he had gone back alone and never come out. She slid the compass into her coat pocket, where it sat warm against her ribs, its needle still straining toward the wall. "Get a team to take the grout samples," she said. "Tell them to be careful with the tiles. And Pardoe?" "Ma'am?" "Don't let anyone touch that token but me."
created_at"2026-10-08T08:39:14.668Z" 10/8/2026, 8:39:14 AM
model"anthropic/claude-haiku-5.5-20261007"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency17614
moderation_latency(null)
generation_time17614
tokens_prompt896
tokens_completion1360
native_tokens_prompt1287
native_tokens_completion2593
native_tokens_completion_images(null)
native_tokens_reasoning787
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"
usage0.0014252
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.21.0; linux; x64))"
http_referer(null)
request_id"req-1791448754-BbdNCO2qF24TEg18ponx"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1791448754-dZA2yB4zMGT5oZlqPJAI"
upstream_id"msg_011CfpU96pAarS5iEJSFrosT"
provider_responses
0
endpoint_id"b6cdf493-3a61-441f-a134-e7944fddb980"
id"msg_011CfpU96pAarS5iEJSFrosT"
is_byokfalse
latency794
model_permaslug"anthropic/claude-haiku-5.5-20261007"
provider_name"Claude Platform on AWS"
status200
total_cost0.0014252
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
79.98% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount999
totalAiIsmAdverbs4
found
0
adverb"gently"
count1
1
adverb"very"
count1
2
adverb"carefully"
count1
3
adverb"slowly"
count1
highlights
0"gently"
1"very"
2"carefully"
3"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)
94.99% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount999
totalAiIsms1
found
0
word"etched"
count1
highlights
0"etched"
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)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
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)
analyzedSentences72
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen59
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords999
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions9
unquotedAttributions0
matches(empty)
100.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions16
wordCount824
uniqueNames7
maxNameDensity0.61
worstName"Quinn"
maxWindowNameDensity1
worstWindowName"Quinn"
discoveredNames
Quinn5
Town1
Inspector1
Tom1
Pardoe5
Morris2
Holborn1
persons
0"Quinn"
1"Inspector"
2"Tom"
3"Pardoe"
4"Morris"
places
0"Town"
1"Holborn"
globalScore1
windowScore1
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences43
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount999
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences72
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs28
mean35.68
std34.02
cv0.953
sampleLengths
085
167
22
358
469
542
67
763
884
914
106
115
1288
1313
148
1566
16104
1728
185
1914
203
215
2213
2399
2422
2520
261
278
80.20% Passive voice overuse
Target: ≤2% passive sentences
passiveCount4
totalSentences56
matches
0"was curled"
1"was cracked"
2"was etched"
3"been given"
42.52% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount3
totalVerbs127
matches
0"was lying"
1"was looking"
2"was thinking"
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences72
ratio0
matches(empty)
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount825
adjectiveStacks0
stackExamples(empty)
adverbCount26
adverbRatio0.03151515151515152
lyAdverbCount7
lyAdverbRatio0.008484848484848486
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences72
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences72
mean13.88
std11.69
cv0.843
sampleLengths
018
125
29
333
418
525
624
72
823
935
107
1116
124
1342
144
158
1614
1716
185
192
208
2118
229
232
2426
2512
266
277
289
2950
306
318
326
335
3417
3519
3618
3734
385
398
407
411
4219
435
4415
457
4620
4711
4815
4911
84.26% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats6
diversityRatio0.5555555555555556
totalSentences72
uniqueOpeners40
100.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount2
totalSentences51
matches
0"Instead she looked at the"
1"Too clean, in a place"
ratio0.039
31.76% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount24
totalSentences51
matches
0"He had the look of"
1"He shone the torch down"
2"His coat was dry."
3"She crouched beside him."
4"It was curled, and when"
5"She had seen one before,"
6"She set it on the"
7"His watch had stopped at"
8"He did, with the reluctant"
9"They came from the stairwell"
10"They stopped at the wall."
11"She stood, knees cracking, and"
12"She ran her fingers along"
13"It was newer than the"
14"She had not noticed it"
15"She crouched and lifted it"
16"Its face was etched around"
17"They had been in the"
18"It turned slowly, trembling, and"
19"Her voice came out level,"
ratio0.471
58.04% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount41
totalSentences51
matches
0"The platform smelled of wet"
1"Harlow Quinn stood at the"
2"Camden Town station had closed"
3"The tiles still carried the"
4"Detective Inspector Tom Pardoe came"
5"He had the look of"
6"He shone the torch down"
7"Quinn walked toward the body"
8"The man lay on his"
9"His coat was dry."
10"The tunnel behind him dripped"
11"She crouched beside him."
12"Pardoe said behind her"
13"Quinn studied the man's left"
14"It was curled, and when"
15"She had seen one before,"
16"She set it on the"
17"His watch had stopped at"
18"The face was cracked, the"
19"He did, with the reluctant"
ratio0.804
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences51
matches(empty)
ratio0
68.97% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences29
technicalSentenceCount3
matches
0"The tiles still carried the ghost of a tube map, faded to the color of weak tea, and the advertisements on the far wall had peeled into strips that hung like ol…"
1"They came from the stairwell and walked straight toward the far wall, where a tiled panel bore an old ad for a brand of tea that had been out of business since …"
2"It was newer than the rest, pale and smooth, as if someone had repaired a seam recently and very carefully."
75.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags10
uselessAdditionCount1
matches
0"She stood, knees cracking, and moved to the wall"
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags5
fancyCount0
fancyTags(empty)
dialogueSentences26
tagDensity0.192
leniency0.385
rawRatio0
effectiveRatio0
87.1908%