Run: 2026-02-19-01KHV72HMN279177R4VS2T3YBH

Run Details

Duration:
40.8s
Cost:
$0.024213
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="4417" name="Tomás Herrera" aliases="Tommy, Tomás, Herrera" pronouns="he/him" species="Human" storyRole="Support"> <eyeColor>warm brown</eyeColor> <hair>short curly dark brown</hair> <height>5'10"</height> <age>29</age> <skinTone>olive skin</skinTone> <scar>scar running along his left forearm from a knife attack</scar> <medallion>Saint Christopher medallion around his neck</medallion> <birthplace>Seville, Spain</birthplace> <description>A former paramedic who provides off-the-books medical care for the clique.</description> <backstory>Born in Seville, Spain. He moved to London to work for the NHS but lost his license after administering unauthorized treatments to supernatural patients.</backstory> </character> <location id="854" name="The Raven's Nest" aliases="the Nest, Raven, Silas' bar" realm="Earth"> <signColor>distinctive green neon sign above the entrance</signColor> <secretRoom>hidden back room accessible through a bookshelf, used for clandestine meetings</secretRoom> <description>A dimly lit bar in Soho, London. The walls are covered with old maps and black-and-white photographs.</description> </location> <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> </codex> Continue the story using the following instructions: <instructions> Write a fully fleshed out scene of at least 1000 words in the thriller genre. A detective is pursuing a suspect through rain-soaked city streets at night. The chase takes them from the street level down into an underground market. The detective must decide whether to follow the suspect into unfamiliar and potentially dangerous territory. 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 rain came sideways off the Thames, carrying with it the smell of diesel and wet stone. Quinn turned her collar up against it and kept moving. She'd been watching the Raven's Nest for forty minutes from the doorway of a closed newsagent across the street, its green neon sign bleeding colour into the puddles below. Her leather watch pressed cold against her wrist. Twenty past eleven. She'd told herself she'd give it until midnight, but then the side door had swung open and the man she'd been looking for slipped out into the rain at a pace that wasn't quite running but wanted to be. Tomás Herrera. Twenty-nine. Former paramedic. Lost his licence three years back under circumstances that her superintendent had described as irregular and Quinn had decided meant something else entirely. She'd been building a file on him for six weeks. Blurry CCTV stills. A mobile number that went to a burner. Witness statements from people who described a man matching his description arriving at addresses where, an hour later, someone would be dead or gone or inexplicably recovered from injuries that should have killed them. She pushed off the doorframe and crossed the street. Herrera moved north through Soho, ducking under scaffolding, cutting through a narrow alley that smelled of bins and old fat from the kitchen extraction fans overhead. Quinn kept thirty metres between them. He hadn't looked back yet. His dark curly hair was plastered flat by the rain and the Saint Christopher medallion at his throat caught the amber of a streetlamp as he turned. He looked back. Their eyes met for half a second. He ran. Quinn was already moving. She took the alley at full stride, her boots finding the least waterlogged parts of the cobblestones by instinct, years of night foot-chases in this city written into her muscle memory. Herrera was quick for someone who hadn't expected to be running. He vaulted a fallen wheelie bin without breaking stride, cut right onto a broader street, and made for the Tube station entrance on the corner. She reached the top of the stairs just as his head disappeared below street level. The station was closed. Had been for thirty years, judging by the state of the hoarding she'd clocked earlier that week when she'd done a preliminary walk of the area. Camden decommission. The entrance had been boarded with corrugated sheeting but somebody had worked one panel loose at the bottom, folding it back just enough for a person to drop through. There was a fresh scuff in the rust where Herrera's boot had caught it. Quinn stopped at the top of the stairs and looked at it. The rain hammered the back of her neck. Down in the dark, she heard his footsteps receding on the old tile. Going deeper. She was off-duty. No backup. She'd called in a favour to access the surveillance records that had led her here tonight, which meant this wasn't logged anywhere. She pressed her hand against her side and felt the reassuring mass of her Glock in its holster. She'd pulled the board and dropped through before she'd finished thinking about it. The air changed immediately. Cooler. Damp in a different way than the street, the moisture clinging rather than striking. The old station smelled of mould and iron and something she couldn't place, something almost organic, like soil turned over in a forest after dark. The tiled walls were intact, the paint peeling in long strips that curled down toward a floor thick with old leaf debris and grit. Emergency lighting that should not have been functioning cast a thin orange wash across the passage, the fixtures far too new for an abandoned station. Someone maintained this. She moved fast down the corridor, hand on the Glock but not drawing. Herrera's footsteps ahead, closer than she'd expected. He'd slowed. The passage opened out. Quinn stopped in the archway and stared. The old station platform had been entirely transformed. The space ran perhaps sixty metres, the vaulted ceiling hung with lanterns that gave off a yellow-green light too steady to be flame and too warm to be electric. Stalls lined both edges of the platform, constructed from reclaimed wood and iron, draped with canvas. Behind them stood people — and things that were not quite people — selling from arrangements that Quinn's brain kept trying to rationalise and kept failing to. Glass bottles containing liquids in colours she had no names for. Bundles of dried material that moved despite the still air. Cages of something small and dark. Documents, stacked and bound, some with covers that appeared to be writing in no alphabet she recognised. The crowd between the stalls was perhaps forty strong. Mixed. Some in ordinary clothes, some in things that weren't. Conversations in low voices and at least three languages she couldn't identify. Nobody shouted, nobody pushed. The whole thing had the specific atmosphere of a place where everyone present understood that drawing attention was its own kind of danger. Three people near the edge of the platform had already noticed her. They weren't alarmed. They were watching, the way you watch something that you're deciding what to do about. Herrera stood ten metres ahead on the platform, turned to face her, chest still heaving from the run. His left forearm was crossed over his body, thumb hooked in the strap of his bag. The scar along the forearm caught the lantern light, pale against his olive skin. "Detective." He'd steadied his breathing faster than she expected. His warm brown eyes moved from her face to her gun hand and back. "You shouldn't be down here." Quinn scanned the room in three clean sweeps. Two exits she could see. One she couldn't locate but suspected existed somewhere past the furthest stalls. The people watching her hadn't moved, but the quality of their stillness had changed. Anticipatory, rather than merely curious. "Tomás Herrera." Her voice carried the same flat authority it always did, regardless of what her body was doing. "I've got questions." "I know." He didn't step back. "That's not the problem." He glanced over her shoulder toward the archway she'd come through, a quick but deliberate movement. She didn't turn.
created_at"2026-02-19T15:07:41.365Z" 2/19/2026, 3:07:41 PM
model"anthropic/claude-4.6-sonnet-20260217"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency1564
moderation_latency(null)
generation_time40392
tokens_prompt1140
tokens_completion1593
native_tokens_prompt1126
native_tokens_completion1389
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)
origin"https://ncbench.com/"
is_byokfalse
finish_reason"stop"
native_finish_reason"stop"
usage0.024213
router(null)
provider_responses
0
endpoint_id"6d408764-7dd7-4626-bb87-a6cc1589bc86"
id"msg_01EmsxDjNFfVYwCp5ZSSiFhW"
is_byokfalse
latency1552
model_permaslug"anthropic/claude-4.6-sonnet-20260217"
provider_name"Anthropic"
status200
api_type"completions"
id"gen-1771513661-FGfw0suCOIQ2t42aPNde"
upstream_id"msg_01EmsxDjNFfVYwCp5ZSSiFhW"
total_cost0.024213
cache_discount(null)
upstream_inference_cost0
provider_name"Anthropic"

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags3
adverbTagCount0
adverbTags(empty)
dialogueSentences6
tagDensity0.5
leniency1
rawRatio0
effectiveRatio0
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1042
totalAiIsmAdverbs0
found(empty)
highlights(empty)
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)
76.01% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1042
totalAiIsms5
found
0
word"footsteps"
count2
1
word"electric"
count1
2
word"constructed"
count1
3
word"scanned"
count1
highlights
0"footsteps"
1"electric"
2"constructed"
3"scanned"
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
narrationSentences84
matches(empty)
91.84% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount2
hedgeCount1
narrationSentences84
filterMatches
0"watch"
hedgeMatches
0"appeared to"
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences87
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
maxSentenceWordsSeen39
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1040
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions2
unquotedAttributions0
matches(empty)
100.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions23
wordCount1023
uniqueNames10
maxNameDensity0.78
worstName"Quinn"
maxWindowNameDensity1.5
worstWindowName"Quinn"
discoveredNames
Thames1
Raven1
Nest1
Herrera6
Quinn8
Soho1
Saint1
Christopher1
Tube1
Glock2
persons
0"Raven"
1"Herrera"
2"Quinn"
3"Saint"
4"Christopher"
places
0"Thames"
1"Soho"
globalScore1
windowScore1
63.79% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences58
glossingSentenceCount2
matches
0"quite running but wanted to be"
1"not quite people — selling from arrangements that Quinn's brain kept trying to rationalise and kept failing to"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1040
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount1
totalSentences87
matches
0"understood that drawing"
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs29
mean35.86
std31.83
cv0.887
sampleLengths
027
179
283
39
464
53
67
72
871
915
1075
1112
1223
1345
1413
1593
163
1722
184
197
20124
2158
2230
2348
2428
2544
2622
2710
2819
92.73% Passive voice overuse
Target: ≤2% passive sentences
passiveCount3
totalSentences84
matches
0"was plastered"
1"been boarded"
2"was crossed"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount2
totalVerbs180
matches
0"were watching"
1"was doing"
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount2
semicolonCount0
flaggedSentences1
totalSentences87
ratio0.011
matches
0"Behind them stood people — and things that were not quite people — selling from arrangements that Quinn's brain kept trying to rationalise and kept failing to."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount1025
adjectiveStacks0
stackExamples(empty)
adverbCount27
adverbRatio0.026341463414634145
lyAdverbCount6
lyAdverbRatio0.005853658536585366
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences87
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences87
mean11.95
std9.06
cv0.758
sampleLengths
017
110
229
38
43
539
62
71
82
923
1010
113
128
1334
149
1526
166
175
1827
193
207
212
224
2331
2411
2525
2615
274
2826
292
3029
3114
3212
338
3413
352
363
372
3822
3918
4013
414
421
4314
4425
4524
4625
473
4813
497
77.39% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats6
diversityRatio0.5057471264367817
totalSentences87
uniqueOpeners44
0.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount0
totalSentences74
matches(empty)
ratio0
79.46% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount26
totalSentences74
matches
0"She'd been watching the Raven's"
1"Her leather watch pressed cold"
2"She'd told herself she'd give"
3"She'd been building a file"
4"She pushed off the doorframe"
5"He hadn't looked back yet."
6"His dark curly hair was"
7"He looked back."
8"Their eyes met for half"
9"She took the alley at"
10"He vaulted a fallen wheelie"
11"She reached the top of"
12"She was off-duty."
13"She'd called in a favour"
14"She pressed her hand against"
15"She'd pulled the board and"
16"She moved fast down the"
17"They weren't alarmed."
18"They were watching, the way"
19"His left forearm was crossed"
ratio0.351
54.59% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount60
totalSentences74
matches
0"The rain came sideways off"
1"Quinn turned her collar up"
2"She'd been watching the Raven's"
3"Her leather watch pressed cold"
4"She'd told herself she'd give"
5"She'd been building a file"
6"Blurry CCTV stills."
7"A mobile number that went"
8"Witness statements from people who"
9"She pushed off the doorframe"
10"Herrera moved north through Soho,"
11"Quinn kept thirty metres between"
12"He hadn't looked back yet."
13"His dark curly hair was"
14"He looked back."
15"Their eyes met for half"
16"Quinn was already moving."
17"She took the alley at"
18"Herrera was quick for someone"
19"He vaulted a fallen wheelie"
ratio0.811
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences74
matches(empty)
ratio0
94.16% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences44
technicalSentenceCount3
matches
0"Witness statements from people who described a man matching his description arriving at addresses where, an hour later, someone would be dead or gone or inexpli…"
1"Herrera moved north through Soho, ducking under scaffolding, cutting through a narrow alley that smelled of bins and old fat from the kitchen extraction fans ov…"
2"Behind them stood people — and things that were not quite people — selling from arrangements that Quinn's brain kept trying to rationalise and kept failing to."
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags3
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags0
87.6658%