Run: 2026-05-29-01KSSJEFWYPS6AQ547VQ8SDQ5G

Run Details

Duration:
43.9s
Cost:
$0.066250
Provider:
Anthropic

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 call had come at 4:17 a.m., which meant nothing good. Quinn took the stairs down into the abandoned Tube station two at a time, her torch beam slicing through air thick with brick dust and something sweeter underneath. Rot, maybe. Or incense. She couldn't decide which bothered her more. "Detective Quinn." A uniformed constable straightened as she reached the platform. Young. Pale around the mouth. "DS Okafor's already down with the body." "How long?" "Twenty minutes, give or take. We secured the perimeter, but—" He hesitated, eyes flicking toward the dark mouth of the tunnel. "It's strange, ma'am. You'll see." She always did. That was the job. The platform stretched out before her, tiled in the cracked cream and oxblood of a station that hadn't seen a train since the Blitz. Camden, the map said, though no Camden line ran here anymore. Someone had strung work lamps along the wall, and they threw everything into harsh relief: the graffiti, the drifts of rubbish, and the man lying spread-eagled at the platform's edge. Okafor crouched beside him, gloved and patient. He glanced up as her footsteps echoed. "Wasn't sure they'd send you," he said. "Given the hour." "They always send me." Quinn knelt opposite, the cold of the concrete seeping through her trousers. "Talk me through it." "Male, mid-forties. No ID. Found by an urban explorer who's currently being sick in the stairwell." Okafor gestured at the body with the flat of his hand, almost reverent. "Cause of death looks straightforward. Massive blood loss. See the throat?" She saw it. A clean wound, edges parted like a second mouth. But that wasn't what held her attention. "Where's the blood?" Okafor nodded as if she'd passed a test. "That's the thing. There isn't any. Not a drop on the platform, not on his clothes past the collar. Floor's dry as bone." Quinn leaned closer. The man's shirt, once white, had gone stiff and brown at the neck — but below the sternum, the cotton was pristine. A wound like that should have emptied him across the tiles. The body should have lain in a lake of its own making. "Postmortem relocation," she said, testing it. "Killed elsewhere, dumped here." "That's my read." Okafor sat back on his heels. "Someone wanted him found. Dragged him down three flights of stairs to do it." "No drag marks." She swept her torch across the dust. The floor told its own story, and it was a clean one. Two sets of footprints leading in — Okafor's and the explorer's, by the tread — and the body, lying as if it had simply appeared. No furrows. No scuffs. No heel-tracks through the grime. "If they carried him, there'd be two people minimum. Disturbed dust. Sweat marks where they set him down." "Maybe they swept up after." "And left the body?" She shook her head. "You don't tidy a crime scene and then leave the centerpiece. No. Whoever did this either didn't care, or—" She stopped. Okafor waited. He'd worked with her long enough to know the silences mattered more than the words. Quinn's torch traveled up the body again, slower this time. The man's hands. Palms up, fingers curled, and ringing each wrist a band of pale skin where something had been worn and removed. A watch, perhaps. Bracelets. She'd seen the same on her own arm where her leather strap sat. But these marks circled the whole wrist, front and back, like a cuff. "His hands were bound," she said. "Restraints, then taken off after death. See the indentation? Not rope. Something flat. Leather, maybe metal." "Could be a robbery gone wrong. They take the watch, the wallet—" "And the restraints?" She frowned. "Robbers don't unbind a corpse. There's no profit in it." She moved to the head, angling the light. The dead man's eyes were open, fixed on the curved ceiling. And around them, faint, almost lost in the grime of his skin, something had been drawn. She breathed on her glove and wiped a fingertip across his temple. Ash. Fine grey ash, arranged in lines. A pattern. "Okafor. Give me your phone light." He passed it over without question. Under the doubled beam, the marks resolved. Not random. Deliberate strokes radiating from the bridge of the nose across both cheekbones, curving up toward the hairline. A symbol. She'd seen its like once before, three years ago, in a photograph she'd never been able to explain. The case that took Morris. Her stomach tightened. "What is it?" Okafor leaned in. "Don't know yet." A half-truth. "But it was put here on purpose. Same as the body." She sat back, letting the whole tableau settle in her mind. The bloodless wound. The vanished blood. The unmarked floor. The bound and unbound wrists. The ash upon the skin. None of it fit a mugging, a hit, a body dump. The pieces refused to lie flat together. "You're seeing something I'm not," Okafor said. "I'm seeing what's missing." She rose, knees protesting. "A man dies of a cut throat. The blood goes somewhere. It doesn't evaporate. So either it was collected—" she let that hang "—or he didn't die here at all, and yet there's no way to bring him here without leaving a trace. Both can't be true. But they are." "So one of them's a lie." "Or both are, and the truth's something neither of us has a box for." She thought of the dust again, perfectly undisturbed around the corpse. As if he'd been set down by hands that left no weight. "Who reported this station? It's not on any active register." Okafor checked his notebook. "Sealed in 1947. Officially doesn't exist." "And yet someone knew it was here. Knew to bring him." She crouched one last time, studying the ash sigil, committing every line to memory. There was a researcher she knew of — a friend of someone she'd been watching, a woman at the British Museum who dealt in the kind of history that didn't make the textbooks. Eva Kowalski. The name had crossed her desk more than once. "Photograph everything," Quinn said. "The face especially. Before forensics arrive." "Why before?" She wiped her glove clean on her trouser leg, the ash smearing grey. "Because I've a feeling," she said, "that by the time they get here, that mark won't be the kind of thing that shows up on film." Okafor stared at her. "Quinn, that's—" "Just photograph it." She stood, and the work lamps flickered, all of them at once, plunging the platform into a half-second of dark before steadying. In that black moment, she'd have sworn the dead man's eyes had moved. She didn't say so. She simply raised her torch and looked again — and the body lay exactly as before, staring up at nothing, wearing a symbol that meant something she wasn't ready to name.
created_at"2026-05-29T09:53:32.761Z" 5/29/2026, 9:53:32 AM
model"anthropic/claude-4.8-opus-20260528"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency1056
moderation_latency(null)
generation_time43607
tokens_prompt1149
tokens_completion1722
native_tokens_prompt1595
native_tokens_completion2331
native_tokens_completion_images(null)
native_tokens_reasoning0
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"
usage0.06625
router(null)
provider_responses
0
endpoint_id"b0d3beaa-5ff7-4666-a749-b1bb2b14c916"
id"msg_01BRUJfhTqjTUw4arBcF7Du7"
is_byokfalse
latency1056
model_permaslug"anthropic/claude-4.8-opus-20260528"
provider_name"Anthropic"
status200
user_agent"langchainjs-openai/1.0.0 ((node/v24.16.0; linux; x64))"
http_referer(null)
request_id"req-1780048412-enqp05h7VeuwLpw7AquH"
session_id(null)
api_type"completions"
id"gen-1780048412-sWiB1nYfxRE5VCFcr928"
upstream_id"msg_01BRUJfhTqjTUw4arBcF7Du7"
total_cost0.06625
cache_discount(null)
upstream_inference_cost0
provider_name"Anthropic"
response_cache_source_id(null)

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags23
adverbTagCount2
adverbTags
0"Okafor sat back [back]"
1"She sat back [back]"
dialogueSentences45
tagDensity0.511
leniency1
rawRatio0.087
effectiveRatio0.087
95.63% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1143
totalAiIsmAdverbs1
found
0
adverb"perfectly"
count1
highlights
0"perfectly"
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)
69.38% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1143
totalAiIsms7
found
0
word"footsteps"
count1
1
word"echoed"
count1
2
word"pristine"
count1
3
word"resolved"
count1
4
word"stomach"
count1
5
word"weight"
count1
6
word"flickered"
count1
highlights
0"footsteps"
1"echoed"
2"pristine"
3"resolved"
4"stomach"
5"weight"
6"flickered"
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
narrationSentences91
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount0
hedgeCount0
narrationSentences91
filterMatches(empty)
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences112
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen51
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1147
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions12
unquotedAttributions0
matches(empty)
66.67% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions24
wordCount797
uniqueNames10
maxNameDensity1.25
worstName"Okafor"
maxWindowNameDensity3
worstWindowName"Okafor"
discoveredNames
Tube1
Young1
Blitz1
Camden2
Quinn5
Okafor10
Morris1
British1
Museum1
Kowalski1
persons
0"Quinn"
1"Okafor"
2"Morris"
3"Kowalski"
places
0"British"
globalScore0.873
windowScore0.667
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences49
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1147
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount1
totalSentences112
matches
0"let that hang"
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs42
mean27.31
std22.17
cv0.812
sampleLengths
050
123
22
326
47
565
614
710
820
940
1019
113
1231
1348
1410
1523
1674
175
1829
1917
2063
2122
2212
2362
249
256
2657
273
286
2964
307
3158
326
3347
3410
3569
3610
372
3839
396
4038
4135
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount1
totalSentences91
matches
0"been drawn"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs143
matches(empty)
15.31% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount6
semicolonCount0
flaggedSentences5
totalSentences112
ratio0.045
matches
0"The man's shirt, once white, had gone stiff and brown at the neck — but below the sternum, the cotton was pristine."
1"Two sets of footprints leading in — Okafor's and the explorer's, by the tread — and the body, lying as if it had simply appeared."
2"\"A man dies of a cut throat. The blood goes somewhere. It doesn't evaporate. So either it was collected—\" she let that hang \"—or he didn't die here at all, and yet there's no way to bring him here without leaving a trace. Both can't be true. But they are.\""
3"There was a researcher she knew of — a friend of someone she'd been watching, a woman at the British Museum who dealt in the kind of history that didn't make the textbooks."
4"She simply raised her torch and looked again — and the body lay exactly as before, staring up at nothing, wearing a symbol that meant something she wasn't ready to name."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount684
adjectiveStacks0
stackExamples(empty)
adverbCount19
adverbRatio0.027777777777777776
lyAdverbCount3
lyAdverbRatio0.0043859649122807015
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences112
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences112
mean10.24
std8.73
cv0.852
sampleLengths
011
128
22
32
47
511
61
74
87
92
1021
115
123
134
1424
1511
1630
177
187
197
203
2116
224
2329
2411
253
269
277
283
298
3023
313
3222
3311
3412
356
364
379
3814
3910
4012
4125
422
432
445
4518
465
478
4821
492
84.52% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats7
diversityRatio0.5446428571428571
totalSentences112
uniqueOpeners61
0.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount0
totalSentences71
matches(empty)
ratio0
84.79% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount24
totalSentences71
matches
0"She couldn't decide which bothered"
1"He hesitated, eyes flicking toward"
2"She always did."
3"He glanced up as her"
4"She saw it."
5"she said, testing it"
6"She swept her torch across"
7"She shook her head"
8"He'd worked with her long"
9"She'd seen the same on"
10"She moved to the head,"
11"She breathed on her glove"
12"He passed it over without"
13"She'd seen its like once"
14"Her stomach tightened."
15"She sat back, letting the"
16"She rose, knees protesting"
17"she let that hang \"—or"
18"She thought of the dust"
19"She crouched one last time,"
ratio0.338
44.51% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount59
totalSentences71
matches
0"The call had come at"
1"Quinn took the stairs down"
2"She couldn't decide which bothered"
3"A uniformed constable straightened as"
4"He hesitated, eyes flicking toward"
5"She always did."
6"That was the job."
7"The platform stretched out before"
8"Camden, the map said, though"
9"Someone had strung work lamps"
10"Okafor crouched beside him, gloved"
11"He glanced up as her"
12"Quinn knelt opposite, the cold"
13"Okafor gestured at the body"
14"She saw it."
15"A clean wound, edges parted"
16"Okafor nodded as if she'd"
17"Quinn leaned closer."
18"The man's shirt, once white,"
19"A wound like that should"
ratio0.831
70.42% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount1
totalSentences71
matches
0"As if he'd been set"
ratio0.014
60.44% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences26
technicalSentenceCount3
matches
0"Two sets of footprints leading in — Okafor's and the explorer's, by the tread — and the body, lying as if it had simply appeared."
1"There was a researcher she knew of — a friend of someone she'd been watching, a woman at the British Museum who dealt in the kind of history that didn't make th…"
2"She simply raised her torch and looked again — and the body lay exactly as before, staring up at nothing, wearing a symbol that meant something she wasn't ready…"
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags23
uselessAdditionCount1
matches
0"He hesitated, eyes flicking toward the dark mouth of the tunnel"
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags7
fancyCount1
fancyTags
0"She rose knees protesting (protest)"
dialogueSentences45
tagDensity0.156
leniency0.311
rawRatio0.143
effectiveRatio0.044
86.3886%