Run: 2026-10-09-01M4FXNEJ9HPCQJX5PQJFYZT2C

Run Details

Duration:
15.2s
Cost:
$0.001248
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 came sideways off the Thames-bound wind and found every gap in her collar. Harlow Quinn wiped her eyes with the back of her wrist, the worn leather watch cold against her cheek, and kept her eyes on the man in the grey parka forty metres ahead. Tomás Herrera did not run like a man who had been caught. He ran like a man who had done this before, weaving between a bin lorry and a queue of taxis outside Camden Town station, cutting left where the pavement narrowed to a strip of wet paving slabs. The Saint Christopher medallion must have swung against his chest with every stride. She could almost hear it. "Herrera! Stop where you are!" The words bounced off shuttered shopfronts and came back to her thinner than she'd sent them. He glanced over his shoulder. Rain ran off his cropped curls and into his eyes, and he didn't bother to wipe it away. "You're going to get yourself killed, Detective." "Stop running and I'll decide that for myself." He laughed, short and breathless, and swung right into a gap between two shuttered market stalls. Quinn followed without slowing. Her knee complained on the wet kerb. She ignored it. Eighteen years had taught her that pain was information, and the information right now said she was closing the gap. The street fell away into a service road that smelled of diesel and wet cardboard. Halfway along, a chain-link gate hung open on one hinge. Beyond it, a set of stone steps dropped into darkness, and above the steps a sheet of corrugated hoarding had been torn back to show a tiled arch. Faded lettering still clung to the tiles. Someone had painted over the station name years ago, but the tube-map roundel above the arch was intact, its red ring bleeding into the rust. Herrera stopped at the top of the steps. He turned, chest heaving, rainwater dripping from his jaw. The scar along his left forearm showed pale against his wet skin where his sleeve had ridden up. "You know where this goes?" he asked. "A disused Tube station. Closed in the sixties, if I remember the file correctly." "Closed to the public." He tilted his head toward the dark. "The people down there don't care what the file says." Quinn drew her warrant card from her inside pocket, held it up so the rain beaded across the laminate. "Metropolitan Police. You're under arrest for the Holloway killings, and for the unlicensed treatment you've been giving people who shouldn't exist. Come up those steps with your hands where I can see them." "You don't understand what you're looking at." "Then explain it to me on the way back to the station." He shook his head slowly. Something in his face shifted. It was not fear exactly. It looked closer to pity, and she hated it immediately. "Three years ago," he said, "your partner came down those steps. Morris, wasn't it? Good man. Stubborn. He had a token in his coat. He didn't come back up." The name landed like a fist beneath her ribs. She kept her face still. Years of interview rooms had taught her that. "Don't use his name." "I'm using it because you've been using it in your head every night since. I can see it on you." He reached into the pocket of his parka. Quinn's hand went to her holster. He stopped, slow and deliberate, and drew out a small object between two fingers. It caught the sodium light from the street: a pale flat disc, yellowed and carved with a spiral of marks she could not read. Bone, she thought. Something that had been part of an animal or a person and had been polished smooth for a purpose. "This gets you through the door," he said. "Nothing else does. No warrant, no radio, no armed response. Your phone will stop working in about four steps. You know that already, don't you? You've felt it in your pocket all evening. Dead air." She had. Her handset had gone silent somewhere around Chalk Farm, the signal bars collapsing one by one as if something had reached into the network and pulled. "Morris went in without a token," Herrera said. "He thought the rules would protect him. They didn't." Quinn looked down the steps. The darkness below did not look empty. It looked like it was waiting, the way a held breath waits. Somewhere down there a sound rose and fell, a low murmur of voices, then a single bright note like a bell struck underwater. Cold air drifted up the stairwell and smelled of wet stone, incense, and something sweeter underneath that she couldn't name. Her backup was twelve minutes away, if they came at all. Her radio had already failed. She had one clip of ammunition, a torch, and a dead partner's name hanging in the air between her and the man holding the only key. "Give it to me," she said. Herrera's mouth twitched. "You're not going to arrest me with it in your hand." "I'm not going to arrest you at all, not yet. I'm going to decide whether I'm following you down there or whether I'm walking back to my car." He held out the bone token on his open palm. The rain pattered against it. He did not close his fingers. He simply waited, as if he had all the time in the world, and she understood with a cold drop in her stomach that he already knew which way she would go.
created_at"2026-10-09T08:49:50.672Z" 10/9/2026, 8:49:50 AM
model"anthropic/claude-haiku-5.5-20261007"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency2574
moderation_latency(null)
generation_time15154
tokens_prompt1104
tokens_completion1406
native_tokens_prompt1576
native_tokens_completion2180
native_tokens_completion_images(null)
native_tokens_reasoning486
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"
usage0.0012476
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.21.0; linux; x64))"
http_referer(null)
request_id"req-1791535790-o6joeyKFVo9FfQLiP7QX"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1791535790-YCJ85boirE8zaBuEmZjK"
upstream_id"msg_011CfrNkuCEBN2427RzePj2C"
provider_responses
0
endpoint_id"b6cdf493-3a61-441f-a134-e7944fddb980"
id"msg_011CfrNkuCEBN2427RzePj2C"
is_byokfalse
latency775
model_permaslug"anthropic/claude-haiku-5.5-20261007"
provider_name"Claude Platform on AWS"
status200
total_cost0.0012476
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
totalTags7
adverbTagCount0
adverbTags(empty)
dialogueSentences20
tagDensity0.35
leniency0.7
rawRatio0
effectiveRatio0
94.62% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount929
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)
94.62% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount929
totalAiIsms1
found
0
word"stomach"
count1
highlights
0"stomach"
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
narrationSentences57
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount0
narrationSentences57
filterMatches
0"watch"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences70
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen37
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords929
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions7
unquotedAttributions0
matches(empty)
100.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions16
wordCount674
uniqueNames9
maxNameDensity0.74
worstName"Quinn"
maxWindowNameDensity1.5
worstWindowName"Quinn"
discoveredNames
Thames-bound1
Quinn5
Herrera4
Camden1
Town1
Saint1
Christopher1
Chalk1
Farm1
persons
0"Quinn"
1"Herrera"
2"Saint"
3"Christopher"
places
0"Camden"
1"Town"
2"Chalk"
3"Farm"
globalScore1
windowScore1
84.21% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences38
glossingSentenceCount1
matches
0"looked like it was waiting, the way a hel"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount929
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences70
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs28
mean33.18
std24.01
cv0.724
sampleLengths
048
167
25
339
47
58
650
785
835
97
1014
1121
1252
137
1412
1525
1629
1726
1894
1943
2028
2117
2267
2342
246
2514
2628
2753
86.80% Passive voice overuse
Target: ≤2% passive sentences
passiveCount3
totalSentences57
matches
0"been caught"
1"been torn"
2"been polished"
78.79% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount2
totalVerbs110
matches
0"was closing"
1"was waiting"
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences70
ratio0
matches(empty)
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount677
adjectiveStacks0
stackExamples(empty)
adverbCount25
adverbRatio0.03692762186115214
lyAdverbCount5
lyAdverbRatio0.007385524372230428
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences70
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences70
mean13.27
std9.19
cv0.692
sampleLengths
015
133
212
337
413
55
65
716
85
918
107
118
1216
134
147
153
1620
1715
1810
1928
207
2125
228
239
2418
257
2614
2711
2810
2919
3033
317
3212
335
345
355
3610
3729
389
395
408
414
4228
436
4414
4524
463
4719
488
4935
74.29% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats3
diversityRatio0.4714285714285714
totalSentences70
uniqueOpeners33
65.36% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount1
totalSentences51
matches
0"Somewhere down there a sound"
ratio0.02
39.61% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount23
totalSentences51
matches
0"He ran like a man"
1"She could almost hear it."
2"He glanced over his shoulder."
3"He laughed, short and breathless,"
4"Her knee complained on the"
5"She ignored it."
6"He turned, chest heaving, rainwater"
7"He tilted his head toward"
8"He shook his head slowly."
9"It was not fear exactly."
10"It looked closer to pity,"
11"She kept her face still."
12"He reached into the pocket"
13"He stopped, slow and deliberate,"
14"It caught the sodium light"
15"Her handset had gone silent"
16"It looked like it was"
17"Her backup was twelve minutes"
18"Her radio had already failed."
19"She had one clip of"
ratio0.451
18.82% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount45
totalSentences51
matches
0"The rain came sideways off"
1"Harlow Quinn wiped her eyes"
2"Tomás Herrera did not run"
3"He ran like a man"
4"The Saint Christopher medallion must"
5"She could almost hear it."
6"The words bounced off shuttered"
7"He glanced over his shoulder."
8"Rain ran off his cropped"
9"He laughed, short and breathless,"
10"Quinn followed without slowing."
11"Her knee complained on the"
12"She ignored it."
13"The street fell away into"
14"Halfway along, a chain-link gate"
15"Someone had painted over the"
16"Herrera stopped at the top"
17"He turned, chest heaving, rainwater"
18"The scar along his left"
19"He tilted his head toward"
ratio0.882
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences51
matches(empty)
ratio0
63.49% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences27
technicalSentenceCount3
matches
0"He ran like a man who had done this before, weaving between a bin lorry and a queue of taxis outside Camden Town station, cutting left where the pavement narrow…"
1"Her handset had gone silent somewhere around Chalk Farm, the signal bars collapsing one by one as if something had reached into the network and pulled."
2"She had one clip of ammunition, a torch, and a dead partner's name hanging in the air between her and the man holding the only key."
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags7
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags5
fancyCount0
fancyTags(empty)
dialogueSentences20
tagDensity0.25
leniency0.5
rawRatio0
effectiveRatio0
86.6866%