Run: 2026-07-25-01KYCSXQVDAB619XTXHR0YB712

Run Details

Duration:
3.4s
Cost:
$0.001855
Provider:
Google AI Studio

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
Neon bleeding into wet asphalt traced the path of the fleeing figure. Detective Harlow Quinn jammed her hands deeper into her coat pockets, boots slapping against the puddles of Soho. Up ahead, the suspect ducked beneath the green neon sign of The Raven's Nest, shoulders rounding against the downpour. Water sluiced from the brim of Quinn’s hat. She checked the worn leather watch on her left wrist, pulse hammering against her ribs with military precision. Eighteen years on the force built a tolerance for midnight foot pursuits, but this runner possessed an unnatural speed. The heavy oak door of the bar shuddered and swung shut before Quinn reached the threshold. Inside, the air hung thick with stale tobacco and old beer. Maps and black-and-white photographs smeared into dark blurs against the wood-paneled walls. Silas stood behind the zinc counter, wiping down a glass with a greasy rag, eyes fixed on the back of the room. Where did he go? Silas tipped his chin toward the corner, grunting. Quinn crossed the floorboards, boots creaking in rhythm with the low hum of the refrigeration unit. A tall bookshelf stood flush against the far wall, volumes of encyclopedias canted at odd angles. She traced her fingers along the spine of a leather-bound atlas, pressing inward. The heavy shelving unit groaned, pivoting smoothly into the darkness to reveal a flight of concrete stairs plunging downward. Damp air smelled of ozone and rusted iron rushed up the stairwell. Quinn drew her service pistol, metal sliding from leather with a sharp click. She descended into the gloom, concrete steps giving way to packed dirt and the distant, rhythmic rumble of subterranean trains. The tunnel opened into a vast, vaulted cavern carved from London clay. Torchlight flickered off damp brick walls. Makeshift stalls crowded the platform of an abandoned Tube station, draped in canvas and hung with rattling charms. Battered bone tokens changed hands between hooded figures over crates of glowing vials and jars containing shifting, iridescent shadows. The Veil Market hummed with a low, collective murmur that vibrated in Quinn's teeth. Footsteps splashed through standing water fifty yards ahead, splashing toward a rusted tunnel archway choked with briars and hanging cables. The runner slipped through the gap, vanishing into the pitch-black perimeter of the subterranean tracks. Quinn halted at the edge of the rusted arch, breath pluming in the chill air. The tunnel swallowed all light beyond the first few yards, dipping deep beneath Camden where municipal maps ended and old tunnels branched into mazes of forgotten utility lines. Her radio emitted only a wall of static, the thick earth blocking all precinct frequencies. Shadows shifted within the black mouth of the rail line, a faint scratching sound echoing off the curved iron ceiling. She lowered the hammer of her pistol, staring into the abyss where the air grew noticeably colder, carrying the unmistakable copper tang of fresh blood.
created_at"2026-07-25T14:12:33.78Z" 7/25/2026, 2:12:33 PM
model"google/gemini-3.5-flash-lite-20260721"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency316
moderation_latency(null)
generation_time3398
tokens_prompt1104
tokens_completion765
native_tokens_prompt1042
native_tokens_completion617
native_tokens_completion_images0
native_tokens_reasoning0
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"STOP"
service_tier"default"
usage0.0018551
router(null)
provider_responses
0
endpoint_id"6bd8f433-79e1-416c-b407-1772eb796c9a"
id"UcRkavjjNYyQ-8YP-dHKoAk"
is_byokfalse
latency316
model_permaslug"google/gemini-3.5-flash-lite-20260721"
provider_name"Google AI Studio"
status200
user_agent"langchainjs-openai/1.0.0 ((node/v24.18.0; linux; x64))"
http_referer(null)
request_id"req-1784988753-4AQaqwVPO1ZKzQO82DLf"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1784988753-hmNobzZwLGWl4W2Spw19"
upstream_id"UcRkavjjNYyQ-8YP-dHKoAk"
total_cost0.0018551
cache_discount(null)
upstream_inference_cost0
provider_name"Google AI Studio"
response_cache_source_id(null)
data_region"global"

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)
wordCount483
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)
0.00% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount483
totalAiIsms10
found
0
word"traced"
count2
1
word"pulse"
count1
2
word"gloom"
count1
3
word"rhythmic"
count1
4
word"flickered"
count1
5
word"vibrated"
count1
6
word"footsteps"
count1
7
word"chill"
count1
8
word"echoing"
count1
highlights
0"traced"
1"pulse"
2"gloom"
3"rhythmic"
4"flickered"
5"vibrated"
6"footsteps"
7"chill"
8"echoing"
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
narrationSentences31
matches(empty)
96.77% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount0
narrationSentences31
filterMatches
0"watch"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences31
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen28
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords483
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions0
unquotedAttributions0
matches(empty)
77.54% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions16
wordCount483
uniqueNames10
maxNameDensity1.45
worstName"Quinn"
maxWindowNameDensity2
worstWindowName"Quinn"
discoveredNames
Harlow1
Quinn7
Soho1
Raven1
Nest1
London1
Tube1
Veil1
Market1
Camden1
persons
0"Harlow"
1"Quinn"
2"Raven"
3"Market"
places
0"Soho"
1"London"
globalScore0.775
windowScore1
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences30
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount483
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences31
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs15
mean32.2
std18.97
cv0.589
sampleLengths
049
145
216
345
44
58
664
712
833
955
1014
1135
1258
1320
1425
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount0
totalSentences31
matches(empty)
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs81
matches(empty)
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences31
ratio0
matches(empty)
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount488
adjectiveStacks0
stackExamples(empty)
adverbCount6
adverbRatio0.012295081967213115
lyAdverbCount3
lyAdverbRatio0.006147540983606557
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences31
echoCount0
echoWords(empty)
73.44% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences31
mean15.58
std5.2
cv0.334
sampleLengths
012
118
219
38
418
519
616
711
812
922
104
118
1216
1316
1413
1519
1612
1713
1820
1912
206
2118
2219
2314
2420
2515
2615
2728
2815
2920
3025
100.00% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats0
diversityRatio0.6451612903225806
totalSentences31
uniqueOpeners20
0.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount0
totalSentences31
matches(empty)
ratio0
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount5
totalSentences31
matches
0"She checked the worn leather"
1"She traced her fingers along"
2"She descended into the gloom,"
3"Her radio emitted only a"
4"She lowered the hammer of"
ratio0.161
72.90% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount24
totalSentences31
matches
0"Neon bleeding into wet asphalt"
1"Detective Harlow Quinn jammed her"
2"Water sluiced from the brim"
3"She checked the worn leather"
4"The heavy oak door of"
5"Maps and black-and-white photographs smeared"
6"Silas stood behind the zinc"
7"Silas tipped his chin toward"
8"Quinn crossed the floorboards, boots"
9"A tall bookshelf stood flush"
10"She traced her fingers along"
11"The heavy shelving unit groaned,"
12"Quinn drew her service pistol,"
13"She descended into the gloom,"
14"The tunnel opened into a"
15"Torchlight flickered off damp brick"
16"The Veil Market hummed with"
17"Footsteps splashed through standing water"
18"The runner slipped through the"
19"Quinn halted at the edge"
ratio0.774
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences31
matches(empty)
ratio0
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences27
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
87.3553%