Run: 2026-07-25-01KYD5EH5B0EJV9PE0TM7167KC

Run Details

Duration:
13.1s
Cost:
$0.007675
Provider:
Meta

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 hammered Soho. It turned the pavement black and slick and threw the green neon of The Raven's Nest across the wet cobbles in a long, bleeding smear. Harlow Quinn stood under the awning with her collar up and her hands in the pockets of her coat and watched the door. She had been there three hours. Her left wrist itched under the worn leather watch. She checked it. 23:14. Her brown eyes never left the entrance. The door opened. A man slipped out. Short curly dark brown hair plastered to his skull by the rain. Olive skin gone pale under the streetlamp. Saint Christopher medallion catching the light for half a second before he tucked it under his shirt. Scar along the left forearm, white against the dark. Tomás Herrera. "You lost your license, not your habits," Quinn muttered. Herrera looked left, right, then moved. Quick steps, head down, not running. That was worse than running. Quinn pushed off the wall. The rain hit her face in cold needles. Her boots slapped water. She kept five metres, then ten, then five again, using doorways, using the crowd spilling from late pubs. Her salt-and-pepper hair darkened as it soaked. Sharp jaw set. Herrera cut down Greek Street. He didn't glance back. He picked up pace. Quinn picked up hers. He reached the end of the street and turned hard into a service alley stacked with bins. The stink of rot and old grease rose even through rain. Quinn rounded the corner and her hand went to her radio, then stopped. No backup. Not for this. "Tomás! Metropolitan Police! Stop!" He ran. His shoes splashed through puddles. He vaulted a low crate. Quinn vaulted it. Her coat snagged, tore. She ignored it. Her breath burned. He burst out onto Charing Cross Road. Traffic hissed past. Buses threw sheets of water over the curb. Herrera wove between cars, palm slapping a taxi's bonnet as he crossed. Horns screamed. Quinn raised a hand at the traffic and ran straight through. A driver slammed brakes. The car skidded inches from her knee. She kept going. "You think this ends well if you run?" Herrera didn't answer. He sprinted north, towards Camden. Rain streaked his face. He cut through a pedestrian cut and knocked over a stack of flyers. Paper stuck to wet ground. Quinn shortened the distance. Ten years of pursuit drills lived in her legs. Eighteen years on the force lived in her chest and told her this man knew where he headed. This was not panic. This was a line to a place. Camden High Street flashed, closed shutters rattling under rain. The canal smelled of diesel and wet metal. Herrera reached the mouth of the abandoned Tube station on Camden Road. Chain-link fence, council signs, padlocked gates. Condemned after the fire in '09. He didn't slow. He slipped through a gap in the fence where someone had peeled the links back. Quinn reached the fence two seconds later. Her fingers gripped cold wire. Rust flaked under her nails. Beyond, Herrera lifted a loose slab of concrete near the shuttered ticket office. Under it, darkness. A set of stone steps descending where no steps should have been. Warm air rose from below, contradictory to the night, carrying scents of incense, iron, burnt sugar. He looked back once. Warm brown eyes met hers through rain and fence. "Don't." His voice cracked. "Do not come down here. You don't know what this is." Quinn stared at the opening. Her watch ticked against her skin. Water ran off her nose, her chin. "Then tell me what it is, Tomás. Tell me what you sold at The Raven's Nest. Tell me why Silas lets you use the back room behind the bookshelf when nobody else gets past the maps and photographs. Tell me why DS Morris died three years ago outside a place like this and everyone filed it as an overdose." Herrera flinched. The name hit him physical. "You think you want answers. You don't. Not like this." "You were a paramedic. You swore an oath. Now you patch up things that don't file reports. Things with teeth. That makes you an accessory or a witness. Pick." He shook his head, rain flying off his curls. He held something in his palm. Small, yellowed, carved. A token of bone. He turned it over and the air around the steps shivered. "Last chance. Walk away, Detective." Footsteps echoed up from the dark below. Not one pair. Many. A low murmur of voices, haggling, laughing. Light flickered from beneath, amber and unsteady, not electric. The Veil Market. Quinn knew the rumours. The Market moved every full moon. No fixed entrance. Bone token to enter. She had three dead informants who spoke of it before they stopped speaking at all. She had Morris's last notebook in her desk drawer with two words underlined: BONE TOKEN. And here it was, in a Spanish ex-paramedic's bleeding hand. Herrera stepped down. One step. Two. The darkness swallowed his ankles, his knees. He kept eye contact until the last second, begging without words. Quinn looked over her shoulder. Rain street. Empty street. No sirens. No witness. Her radio useless this deep in concrete and old iron. If she went down, she went alone. If she let him go, the thread snapped. Three years of cold trails snapped with it. Her hand found the gap in the fence. She squeezed through. Metal bit into her coat, into her shoulder. She yanked free. She stood before the steps. Water dripped from her crop of hair into her eyes. She wiped it away with the back of her hand. The murmur below grew louder. Something metallic chimed. Something exhaled. She took a breath that tasted of ozone and old incense. "Police! Stay where you are!" She stepped down into the dark.
created_at"2026-07-25T17:33:58.334Z" 7/25/2026, 5:33:58 PM
model"meta/muse-spark-1.1-20260709"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency2651
moderation_latency(null)
generation_time13029
tokens_prompt1104
tokens_completion1425
native_tokens_prompt1132
native_tokens_completion1589
native_tokens_completion_images0
native_tokens_reasoning296
native_tokens_cached448
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"completed"
service_tier"auto"
usage0.00767545
router(null)
provider_responses
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endpoint_id"b2b9f6f9-8880-41c1-bd0c-867650fd5238"
id"resp_6a64f386800d15b2753e4f18"
is_byokfalse
latency364
model_permaslug"meta/muse-spark-1.1-20260709"
provider_name"Meta"
status200
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request_id"req-1785000838-cRNSv37nIFdXHsWZCnGW"
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api_type"completions"
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total_cost0.00767545
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provider_name"Meta"
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data_region"global"

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags1
adverbTagCount0
adverbTags(empty)
dialogueSentences10
tagDensity0.1
leniency0.2
rawRatio0
effectiveRatio0
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount977
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)
79.53% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount977
totalAiIsms4
found
0
word"footsteps"
count1
1
word"echoed"
count1
2
word"flickered"
count1
3
word"electric"
count1
highlights
0"footsteps"
1"echoed"
2"flickered"
3"electric"
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
narrationSentences126
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount2
hedgeCount0
narrationSentences126
filterMatches
0"watch"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences135
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
totalWords977
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions5
unquotedAttributions0
matches(empty)
66.67% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions42
wordCount837
uniqueNames18
maxNameDensity1.43
worstName"Quinn"
maxWindowNameDensity3
worstWindowName"Quinn"
discoveredNames
Soho1
Raven1
Nest1
Quinn12
Christopher1
Herrera9
Greek1
Street2
Charing1
Cross1
Road2
Camden3
High1
Tube1
Veil1
Market2
Morris1
Spanish1
persons
0"Raven"
1"Quinn"
2"Christopher"
3"Herrera"
4"Market"
5"Morris"
places
0"Soho"
1"Greek"
2"Street"
3"Charing"
4"Cross"
5"Road"
6"Camden"
7"High"
8"Spanish"
globalScore0.783
windowScore0.667
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences60
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount977
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences135
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs49
mean19.94
std15.99
cv0.802
sampleLengths
04
148
26
320
43
549
62
79
817
95
1040
1113
124
1346
144
152
1623
1732
1825
198
2030
2142
2217
2342
2417
2544
2613
271
283
2911
3018
3159
327
3310
3429
3533
365
3727
383
3947
4010
4124
4246
4322
4425
4510
4611
475
486
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount0
totalSentences126
matches(empty)
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs157
matches(empty)
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences135
ratio0
matches(empty)
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount563
adjectiveStacks0
stackExamples(empty)
adverbCount7
adverbRatio0.012433392539964476
lyAdverbCount1
lyAdverbRatio0.0017761989342806395
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences135
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences135
mean7.24
std6.58
cv0.909
sampleLengths
04
125
223
36
49
53
61
77
83
94
1012
117
1217
139
142
159
166
176
185
195
208
214
2218
237
243
255
264
274
284
2917
3011
3113
322
333
344
352
365
375
383
394
403
413
427
433
448
4512
462
4711
484
497
60.95% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats10
diversityRatio0.41044776119402987
totalSentences134
uniqueOpeners55
0.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount0
totalSentences111
matches(empty)
ratio0
75.86% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount40
totalSentences111
matches
0"It turned the pavement black"
1"She had been there three"
2"Her left wrist itched under"
3"She checked it."
4"Her brown eyes never left"
5"Her boots slapped water."
6"She kept five metres, then"
7"Her salt-and-pepper hair darkened as"
8"He didn't glance back."
9"He picked up pace."
10"He reached the end of"
11"His shoes splashed through puddles."
12"He vaulted a low crate."
13"Her coat snagged, tore."
14"She ignored it."
15"Her breath burned."
16"He burst out onto Charing"
17"She kept going."
18"He sprinted north, towards Camden."
19"He cut through a pedestrian"
ratio0.36
50.09% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount91
totalSentences111
matches
0"The rain hammered Soho."
1"It turned the pavement black"
2"Harlow Quinn stood under the"
3"She had been there three"
4"Her left wrist itched under"
5"She checked it."
6"Her brown eyes never left"
7"The door opened."
8"A man slipped out."
9"Olive skin gone pale under"
10"Saint Christopher medallion catching the"
11"Herrera looked left, right, then"
12"That was worse than running."
13"Quinn pushed off the wall."
14"The rain hit her face"
15"Her boots slapped water."
16"She kept five metres, then"
17"Her salt-and-pepper hair darkened as"
18"Herrera cut down Greek Street."
19"He didn't glance back."
ratio0.82
90.09% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount2
totalSentences111
matches
0"If she went down, she"
1"If she let him go,"
ratio0.018
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences26
technicalSentenceCount1
matches
0"She had three dead informants who spoke of it before they stopped speaking at all."
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags1
uselessAdditionCount0
matches(empty)
50.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags1
fancyCount1
fancyTags
0"Quinn muttered (mutter)"
dialogueSentences10
tagDensity0.1
leniency0.2
rawRatio1
effectiveRatio0.2
89.1059%