Run: 2026-10-08-01M4DA2NMJJ60HWWCZE4Q2ZA0T

Run Details

Duration:
14.9s
Cost:
$0.001246
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="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 had soaked through Quinn's collar within the first hundred yards, and now it ran in cold threads down the back of her neck. Ahead, Tomás Herrera vaulted a bollard on Chalk Farm Road without breaking stride, his dark coat flaring behind him like a torn sail. The green neon of a kebab shop sign stuttered across the wet tarmac and caught the silver medallion swinging at his throat. She had him on the corner of Camden High Street, close enough to hear his breath. Then a bus pulled out between them and the gap opened to twenty yards. Quinn pushed harder. Her left wrist ached where the leather watch strap had worn a groove into the skin, and she ignored it. Eighteen years on the force had taught her to run in a straight line and to never, ever chase a man into a place she could not see the walls of. "Herrera!" Her voice bounced off the shuttered shopfronts. "Stop running and I'll stop shouting." He glanced back. Even in the sodium light she caught the flash of his face, the sharp cut of his cheekbones, and the thin white scar that ran from wrist to elbow on his left arm. He didn't answer. He turned left, into a service lane between a closed record shop and a row of bins, and vanished. Quinn reached the mouth of the lane and stopped. Water pooled in the cracked concrete, reflecting the orange glow of a single lamp. At the far end, a steel hoarding fence sagged on its posts, and beyond it lay the dark throat of the canal towpath. A gap in the metal, no wider than a man's shoulders, had been peeled back and then carelessly pushed into place again. She stepped into the lane. Her shoes slapped on the wet surface, too loud, and she made herself slow down. Halfway along, a shape detached itself from the shadow of a skip. Young, hood up, a hand already held out in front of him, palm up. "Ticket, Auntie?" "Police," Quinn said, and held up her warrant card. The boy's eyes flicked to the card, then to her face, then past her shoulder. He grinned without warmth. "Then you'll want a bone token, Detective, because the lads on the other side don't read ID." "Where did he go?" "Who?" Quinn took two steps closer and stopped with her toes an inch from his trainers. She did not raise her voice. "Thirty seconds ago, a man with a cut on his arm ran into this lane. I want to know where he went, and I want to know now, before I start counting the things you've been selling out of that skip." The boy's grin slipped. He glanced at the gap in the hoarding, and something in his shoulders eased, as if a debt had been paid. "Through the fence and down. Market's under the old station. Everyone goes down when the rain comes in. Your mate's got a token, though. You don't." "Then I'll manage." "Won't manage nothing." He stepped aside. "Nobody comes back up the same person they went down as. Not the ones who don't know the way." Quinn looked at the gap. The steel edges were bent outward, fresh scrapes gleaming bright against the rust. Herrera had squeezed through here in a hurry, and he had not hesitated. She thought about the Nest, the locked back room with its bookshelf door, and the three nights she'd spent watching Silas's regulars file in and out with that same look of people who knew something she didn't. She thought about DS Morris, and the report she'd written that said *unexplained* because she had not been able to write anything else. Rain drummed on the skip lid. Somewhere to the north a train rattled over the bridge, and the sound faded into a low hum she felt in her teeth. Her wrist throbbed under the watch. She set her jaw and checked the cuffs on her belt, a habit older than the watch itself. "Who runs the place?" she asked. The boy shrugged. "Nobody runs it. It moves, every full moon. Tonight it's here." He nodded at the fence. "Tomorrow it could be under Euston. Depends who's selling what and who's buying." "And what's Herrera buying?" The boy's eyes narrowed. For the first time, he looked afraid. "Not my business, Detective. And I'd say it's not yours, neither." Quinn stepped forward and took hold of the twisted steel. It was cold and slick, and it bit into her palm when she pulled. The gap gave another inch. Beyond it, a flight of stairs dropped into blackness, and from somewhere far below came the faint, metallic scent of old rain and something sweeter, like burnt sugar and iron. She could call it in. Wait at the top, radio for backup that would take twenty minutes to find a way through a fence no map had ever marked. Or she could follow a man she had been watching for a month into a place with no records, no cameras, and no rules she recognised. Quinn turned her wrist so the watch faced her. Then she ducked her head, pressed her shoulders through the gap, and felt the cold concrete of the staircase rise to meet her boots.
created_at"2026-10-08T08:29:03.515Z" 10/8/2026, 8:29:03 AM
model"anthropic/claude-haiku-5.5-20261007"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency2693
moderation_latency(null)
generation_time14909
tokens_prompt1104
tokens_completion1432
native_tokens_prompt1576
native_tokens_completion2176
native_tokens_completion_images(null)
native_tokens_reasoning507
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"
usage0.0012456
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.21.0; linux; x64))"
http_referer(null)
request_id"req-1791448143-70GAhxojxP5BMFcYLHYa"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1791448143-TqAwz54H5xXHdWaB21OV"
upstream_id"msg_011CfpTN3jcwJvvuvpnhyZ42"
provider_responses
0
endpoint_id"b6cdf493-3a61-441f-a134-e7944fddb980"
id"msg_011CfpTN3jcwJvvuvpnhyZ42"
is_byokfalse
latency741
model_permaslug"anthropic/claude-haiku-5.5-20261007"
provider_name"Claude Platform on AWS"
status200
total_cost0.0012456
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
82.35% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags5
adverbTagCount1
adverbTags
0"He stepped aside [aside]"
dialogueSentences17
tagDensity0.294
leniency0.588
rawRatio0.2
effectiveRatio0.118
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount888
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)
77.48% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount888
totalAiIsms4
found
0
word"flicked"
count1
1
word"warmth"
count1
2
word"gleaming"
count1
3
word"throbbed"
count1
highlights
0"flicked"
1"warmth"
2"gleaming"
3"throbbed"
100.00% Cliché density
Target: ≤1 cliche(s) per 800-word window
totalCliches1
maxInWindow1
found
0
label"eyes widened/narrowed"
count1
highlights
0"eyes narrowed"
100.00% Emotion telling (show vs. tell)
Target: ≤3% sentences with emotion telling
emotionTells1
narrationSentences52
matches
0"looked afraid"
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount0
narrationSentences52
filterMatches
0"watch"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences64
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen41
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans1
markdownWords1
totalWords888
ratio0.001
matches
0"unexplained"
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions6
unquotedAttributions0
matches(empty)
94.52% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions20
wordCount721
uniqueNames12
maxNameDensity1.11
worstName"Quinn"
maxWindowNameDensity2
worstWindowName"Quinn"
discoveredNames
Quinn8
Tomás1
Herrera2
Chalk1
Farm1
Road1
Camden1
High1
Street1
Nest1
Silas1
Morris1
persons
0"Quinn"
1"Tomás"
2"Herrera"
3"Silas"
4"Morris"
places
0"Chalk"
1"Farm"
2"Road"
3"Camden"
4"High"
5"Street"
globalScore0.945
windowScore1
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences38
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount888
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences64
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs26
mean34.15
std24.82
cv0.727
sampleLengths
070
130
254
314
458
568
646
72
89
936
104
111
1262
1351
143
1525
1691
1729
1824
196
2032
214
2222
2359
2455
2533
91.77% Passive voice overuse
Target: ≤2% passive sentences
passiveCount2
totalSentences52
matches
0"been peeled"
1"been paid"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs111
matches(empty)
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences64
ratio0
matches(empty)
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount721
adjectiveStacks0
stackExamples(empty)
adverbCount20
adverbRatio0.027739251040221916
lyAdverbCount1
lyAdverbRatio0.0013869625520110957
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences64
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences64
mean13.88
std9.45
cv0.681
sampleLengths
025
123
222
316
414
53
620
731
88
96
103
1133
123
1319
149
1514
1623
1722
185
1915
2012
2114
222
239
2415
254
2617
274
281
2915
306
3141
324
3321
3426
353
366
3719
385
3913
4013
4137
4223
436
4423
456
4618
476
483
4916
85.42% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats2
diversityRatio0.53125
totalSentences64
uniqueOpeners34
100.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount3
totalSentences51
matches
0"Then a bus pulled out"
1"Somewhere to the north a"
2"Then she ducked her head,"
ratio0.059
70.98% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount19
totalSentences51
matches
0"She had him on the"
1"Her left wrist ached where"
2"Her voice bounced off the"
3"He glanced back."
4"He didn't answer."
5"He turned left, into a"
6"She stepped into the lane."
7"Her shoes slapped on the"
8"He grinned without warmth."
9"She did not raise her"
10"He glanced at the gap"
11"He stepped aside"
12"She thought about the Nest,"
13"She thought about DS Morris,"
14"Her wrist throbbed under the"
15"She set her jaw and"
16"He nodded at the fence"
17"It was cold and slick,"
18"She could call it in."
ratio0.373
77.65% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount39
totalSentences51
matches
0"The rain had soaked through"
1"The green neon of a"
2"She had him on the"
3"Quinn pushed harder."
4"Her left wrist ached where"
5"Her voice bounced off the"
6"He glanced back."
7"He didn't answer."
8"He turned left, into a"
9"Quinn reached the mouth of"
10"Water pooled in the cracked"
11"A gap in the metal,"
12"She stepped into the lane."
13"Her shoes slapped on the"
14"Halfway along, a shape detached"
15"Quinn said, and held up"
16"The boy's eyes flicked to"
17"He grinned without warmth."
18"Quinn took two steps closer"
19"She did not raise her"
ratio0.765
98.04% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount1
totalSentences51
matches
0"Even in the sodium light"
ratio0.02
95.24% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences30
technicalSentenceCount2
matches
0"Even in the sodium light she caught the flash of his face, the sharp cut of his cheekbones, and the thin white scar that ran from wrist to elbow on his left arm…"
1"She thought about the Nest, the locked back room with its bookshelf door, and the three nights she'd spent watching Silas's regulars file in and out with that s…"
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags5
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags2
fancyCount0
fancyTags(empty)
dialogueSentences17
tagDensity0.118
leniency0.235
rawRatio0
effectiveRatio0
95.7814%