Run: 2026-09-03-01M1K5FK5JE8QAKBTHPZR8M6HH

Run Details

Duration:
1m 39s
Cost:
$0.018007
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
Rain hammered the pavement outside The Raven's Nest. Green neon bled down the Soho brick and pooled in the cracks. Old maps stared from the windows. Black-and-white photographs curled behind glass. Bass thumped through the door each time it swung. Harlow Quinn stood across the street under a dead awning. Water ran off the canvas and hit her boots. She checked the worn leather strap on her left wrist. Ten past one. Her brown eyes fixed on the mouth of the alley beside the bar. Her salt-and-pepper crop stuck to her scalp. Her sharp jaw set hard. The side door opened. Tomás Herrera stepped out with his collar up. Olive skin shone wet under the sign. Short curly dark brown hair clung to his forehead. A Saint Christopher medallion flashed at his throat. His left sleeve rode up and exposed white scar tissue along his forearm. Quinn pushed off the wall. Her stride ate the distance. Military precision lived in her shoulders, in the straight line of her back. “Tomás Herrera! Met Police!” Herrera froze for half a breath. His warm brown eyes met hers across the rain. “Quinn, you need to walk off.” He bolted. Quinn sprinted. Her boots slapped standing water. Spray shot up her trousers. The streetlights smeared into long orange ribbons. A taxi horn blared. She cut around its bonnet and kept her gaze locked on Herrera’s back. Herrera vaulted a stack of crates outside a shuttered grocer. Bottles rattled. He hit the ground and dodged left into Berwick Street. Stalls loomed under tarps. Rain drummed the canvas. The smell of damp cardboard and rotten fruit filled the air. Quinn vaulted the same crates. Wood bit her palm. “Stop where you are!” Her voice cracked through the downpour. A vendor ducked. Herrera shouldered past a rack of coats and sent hangers clattering across the wet tarmac. He ran with his head low. His arms pumped. His medallion bounced against his chest. Quinn closed two paces. Her lungs burned. Water streamed down her face and into her mouth. She tasted copper and exhaust. Herrera glanced back. Fear widened his eyes. “You chase a man who patches wounds. Let it go.” “You patch wounds off the books. You know names I need. Stand still.” A bus lumbered across the junction ahead. Herrera sprinted for its tail lights. Quinn swore under her breath and poured more speed into her legs. The bus braked. Red light washed the rain. Herrera slid between the bus and a parked van with inches to spare. Metal shrieked as his jacket caught the mirror. Quinn followed. The van mirror clipped her shoulder and spun her half round. Pain shot down her arm. She caught her balance on a lamppost and shoved forward. The bus pulled off and left diesel smoke hanging in the wet air. Oxford Street opened wide and slick. Crowds thinned under umbrellas. Neon signs reflected in black puddles. Herrera wove through late drinkers outside a club. Quinn tracked the dark shape of his jacket. She fumbled her radio from her pocket. Static hissed. “Quinn to control. Foot pursuit north past Soho. Male, late twenties, dark jacket. Headed toward Tottenham Court Road.” The reply dissolved into crackle. Rain killed the signal. She shoved the radio back. Herrera hit the steps to the Underground and took them three at a time. Quinn followed. Water sheeted down the tiles. The handrail felt slick under her grip. Posters peeled from the walls. A busker snatched his guitar case from the path as boots thundered past. The Northern line train stood with doors open. A chime rang. Herrera dived through the gap. Quinn lunged. Her fingers brushed his sleeve. The doors sealed between them with a rubber thud. She slammed her palm against the glass. Herrera stared back from inside the carriage. Chest heaved. Scarred forearm pressed to the door frame. “Next stop, Quinn. Lose me there if you can.” “Doors open again. I find you.” The train pulled out. Quinn turned and ran for the next platform readout. Camden Town. Four minutes. She vaulted the barrier. An attendant shouted. She flashed her warrant card without breaking stride and took the southbound escalator down two steps at a time. Cold air pushed up from the tunnels. It smelled of iron and oil and old dust. Her boots hit the platform as the next train roared in. She boarded and gripped the pole. Water dripped from her chin onto her shirt. Her reflection stared back from the dark window: tall frame, cropped hair plastered flat, jaw clenched tight. Camden arrived in a rush of brakes and heat. Doors opened. Crowds spilled. Quinn scanned heads. No dark curls. No scar. She pushed through bodies toward the exit and caught a flash of the Saint Christopher medallion near the gates. Herrera vaulted the gate. Staff shouted. He hit the rain outside and ran east past shuttered stalls and graffiti. Quinn chased. Her legs screamed. The worn leather watch slapped her wrist with each stride. The streets narrowed. Cobbled lanes twisted behind the market. Abandoned shopfronts loomed. A rusted sign creaked over a brick arch: Camden Station Disused Access. No lights burned beyond. Herrera slowed at the arch. He pulled something from his pocket. Bone, yellowed and carved with small marks. He held it up to the dark. Quinn slowed to a walk ten metres back. Her hand dropped to the extendable baton at her belt. Rain needled her scalp. “Herrera! End of the line. Hands where I see them.” Herrera looked over his shoulder. Water ran down his olive cheeks. His brown eyes held no mockery now. “This door stays shut to your kind. Turn round.” “I chased you from Soho. I stand in rain for an hour. You think I turn round for a brick wall?” A figure detached from the shadows under the arch. Tall. Hooded. Face lost. A hand extended, palm up. Herrera placed the bone token in the palm. The hooded figure tilted its head toward Quinn. Stone ground against stone. A section of brick swung inward and revealed a stairwell. Warm air breathed out. It carried incense and copper and something sweet, like crushed herbs. Chant and low music rose from below. Light flickered, amber and green. Quinn stepped closer. Her boots crunched grit. She peered past Herrera down the steps. Stalls lined a vaulted tunnel. Glass vials glowed. Cages rattled. Masks hung from wires. People bartered in whispers. An old Tube platform stretched into dark, transformed into a bazaar. The Veil Market. Full moon light meant nothing down here, yet the place pulsed with its own cycle. Her grip tightened on the baton. Eighteen years of service rang in her ears. Procedure demanded backup, a warrant, a team. DS Morris grinned in her memory, then vanished into a case file with blacked-out pages and no body. Three years of unanswered questions pressed at her ribs. Herrera stood on the top step. He pocketed the empty hand where the token sat seconds before. “You enter without bone, you enter as meat. Your law means nothing down there.” “You hide suspects down there. That makes it my business.” The hooded figure waited. Stone hinges groaned. The gap narrowed inch by inch. Quinn checked her watch. Rain hammered her shoulders. The street behind her lay empty and black and cold. The stairwell in front breathed heat against her face. She met Herrera’s gaze. “You go first.”
created_at"2026-09-03T08:17:05.208Z" 9/3/2026, 8:17:05 AM
model"meta/muse-spark-1.3-20260902"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency51208
moderation_latency(null)
generation_time99407
tokens_prompt1104
tokens_completion1854
native_tokens_prompt989
native_tokens_completion3946
native_tokens_completion_images0
native_tokens_reasoning2287
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"completed"
service_tier"auto"
usage0.01800675
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.19.0; linux; x64))"
http_referer(null)
request_id"req-1788423425-b2XgYlpnQVfpB0jQQBLq"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1788423425-TuOO36b27RFLeBkVWXfe"
upstream_id"resp_6a992d01a058c0dc1a7646b4"
provider_responses
0
endpoint_id"cf4f1b4e-1719-4b65-9111-7dd7635e5a2f"
id"resp_6a992d01a058c0dc1a7646b4"
is_byokfalse
latency976
model_permaslug"meta/muse-spark-1.3-20260902"
provider_name"Meta"
status200
total_cost0.01800675
cache_discount(null)
upstream_inference_cost0
provider_name"Meta"
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
totalTags0
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1240
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)
71.77% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1240
totalAiIsms7
found
0
word"loomed"
count2
1
word"thundered"
count1
2
word"jaw clenched"
count1
3
word"scanned"
count1
4
word"flickered"
count1
5
word"pulsed"
count1
highlights
0"loomed"
1"thundered"
2"jaw clenched"
3"scanned"
4"flickered"
5"pulsed"
100.00% Cliché density
Target: ≤1 cliche(s) per 800-word window
totalCliches1
maxInWindow1
found
0
label"jaw/fists clenched"
count1
highlights
0"jaw clenched"
100.00% Emotion telling (show vs. tell)
Target: ≤3% sentences with emotion telling
emotionTells0
narrationSentences168
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount2
hedgeCount0
narrationSentences168
filterMatches
0"watch"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences182
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen21
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1240
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions0
unquotedAttributions0
matches(empty)
63.87% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions69
wordCount1103
uniqueNames22
maxNameDensity1.72
worstName"Herrera"
maxWindowNameDensity3
worstWindowName"Herrera"
discoveredNames
Raven1
Nest1
Soho1
Quinn17
Herrera19
Saint2
Christopher2
Berwick1
Street2
Underground1
Northern1
Town1
Camden3
Station1
Disused1
Access1
Tube1
Veil1
Market1
Morris1
Rain5
Water5
persons
0"Quinn"
1"Herrera"
2"Saint"
3"Christopher"
4"Station"
5"Morris"
6"Rain"
7"Water"
places
0"Raven"
1"Soho"
2"Berwick"
3"Street"
4"Underground"
5"Town"
6"Camden"
globalScore0.639
windowScore0.667
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences88
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1240
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences182
matches(empty)
66.48% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs32
mean38.75
std14.83
cv0.383
sampleLengths
040
157
24
345
450
536
641
737
836
930
1054
1141
1232
1341
1446
1532
1638
1743
1858
1940
2034
2128
2225
2380
2434
2541
2661
2748
2841
2913
3027
317
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount0
totalSentences168
matches(empty)
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs212
matches(empty)
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences182
ratio0
matches(empty)
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount1108
adjectiveStacks0
stackExamples(empty)
adverbCount9
adverbRatio0.008122743682310469
lyAdverbCount2
lyAdverbRatio0.0018050541516245488
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences182
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences182
mean6.81
std3.94
cv0.579
sampleLengths
08
112
26
35
49
510
69
710
83
913
107
115
124
138
147
159
168
1713
185
195
2013
214
226
239
246
252
262
275
285
297
304
3113
3210
332
3410
354
364
3711
385
394
404
416
423
4315
446
453
466
474
483
499
56.41% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats9
diversityRatio0.36813186813186816
totalSentences182
uniqueOpeners67
0.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount0
totalSentences149
matches(empty)
ratio0
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount40
totalSentences149
matches
0"She checked the worn leather"
1"Her brown eyes fixed on"
2"Her salt-and-pepper crop stuck to"
3"Her sharp jaw set hard."
4"His left sleeve rode up"
5"Her stride ate the distance."
6"His warm brown eyes met"
7"Her boots slapped standing water."
8"She cut around its bonnet"
9"He hit the ground and"
10"Her voice cracked through the"
11"He ran with his head"
12"His arms pumped."
13"His medallion bounced against his"
14"Her lungs burned."
15"She tasted copper and exhaust."
16"She caught her balance on"
17"She fumbled her radio from"
18"She shoved the radio back."
19"Her fingers brushed his sleeve."
ratio0.268
27.11% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount129
totalSentences149
matches
0"Bass thumped through the door"
1"Harlow Quinn stood across the"
2"Water ran off the canvas"
3"She checked the worn leather"
4"Her brown eyes fixed on"
5"Her salt-and-pepper crop stuck to"
6"Her sharp jaw set hard."
7"The side door opened."
8"Tomás Herrera stepped out with"
9"Olive skin shone wet under"
10"A Saint Christopher medallion flashed"
11"His left sleeve rode up"
12"Quinn pushed off the wall."
13"Her stride ate the distance."
14"Military precision lived in her"
15"Herrera froze for half a"
16"His warm brown eyes met"
17"Her boots slapped standing water."
18"Spray shot up her trousers."
19"The streetlights smeared into long"
ratio0.866
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences149
matches(empty)
ratio0
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences33
technicalSentenceCount0
matches(empty)
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags0
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags0
86.1882%