Run: 2026-07-25-01KYCWXKX97X5FZ683747FGG96

Run Details

Duration:
4.9s
Cost:
$0.001475
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
Rain slicked the asphalt across Camden High Street, turning the glare of neon store signs into distorted crimson streaks. Rubber soles slapped against the puddles. Detective Harlow Quinn punched her long stride through the downpour, leather watch strapped to her left wrist catching the amber streetlamp light. A sharp jaw set tight. Eighteen years on the force left zero room for footraces against elusive targets, yet here she pounded the pavement. The figure ahead rounded the corner toward the abandoned Tube station, ducking beneath a rusted corrugated awning. Quinn closed the gap, heels slamming down hard. Water soaked through her trench coat, freezing against her shoulders. She reached the top of the abandoned station stairs, boots scraping over slick concrete steps descending into pitch-black gloom. A rusted iron gate hung half-off its hinges, groaning in the draft. A jagged piece of bone clattered against the bottom step. Quinn paused at the threshold, nostrils catching a foul draft of ozone, copper, and damp earth. No municipal train ran these tracks for decades. Beneath the street level, the air grew thick, humming with an invisible static charge that made the hairs on her arms stand upright. Shadows stretched weirdly down the tunnel, defying the single flickering amber bulb overhead. Footsteps echoed ahead, splashing through stagnant puddles deeper into the subterranean gloom. Quinn gripped the butt of her service weapon, thumb flicking the retention strap loose. She descended past the rusted ticket turnstiles, boots crunching on broken glass and discarded bone tokens. The tunnel walls wept black moisture, stone blocks ancient and scorched. A market carved out of forgotten brick sprawled across the disused platform. Stalls fashioned from rotting timber lined the tracks where commuters once waited. Lanterns cast sickly green and purple glows across bizarre wares hung from iron hooks—shriveled roots, jars containing churning violet smoke, and weapons forged from dark, light-absorbing metal. Hooded figures huddled around crates, whispering in overlapping tongues that sounded like grinding stones. The target slipped between two stalls selling preserved animal pelts. Quinn stepped onto the platform, eyes scanning the shifting crowd of cloaked figures turning toward her intrusion.
created_at"2026-07-25T15:04:55.479Z" 7/25/2026, 3:04:55 PM
model"google/gemini-3.5-flash-lite-20260721"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency2111
moderation_latency(null)
generation_time4731
tokens_prompt1104
tokens_completion594
native_tokens_prompt1042
native_tokens_completion465
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"
usage0.0014751
router(null)
provider_responses
0
endpoint_id"6bd8f433-79e1-416c-b407-1772eb796c9a"
id"mdBkapuIHIiQjMcPw-30kAY"
is_byokfalse
latency2111
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-1784991895-Lc4gDOl8gvmjxd6gP1bn"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1784991895-kJhQdmLuirMDHBGshtbL"
upstream_id"mdBkapuIHIiQjMcPw-30kAY"
total_cost0.0014751
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)
wordCount353
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)
15.01% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount353
totalAiIsms6
found
0
word"gloom"
count2
1
word"footsteps"
count1
2
word"echoed"
count1
3
word"churning"
count1
4
word"scanning"
count1
highlights
0"gloom"
1"footsteps"
2"echoed"
3"churning"
4"scanning"
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
narrationSentences25
matches(empty)
85.71% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount0
narrationSentences25
filterMatches
0"watch"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences25
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen29
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords352
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions0
unquotedAttributions0
matches(empty)
78.98% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions10
wordCount352
uniqueNames6
maxNameDensity1.42
worstName"Quinn"
maxWindowNameDensity2
worstWindowName"Quinn"
discoveredNames
Camden1
High1
Street1
Harlow1
Quinn5
Tube1
persons
0"Harlow"
1"Quinn"
places
0"Camden"
1"High"
2"Street"
globalScore0.79
windowScore1
45.83% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences24
glossingSentenceCount1
matches
0"sounded like grinding stones"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount352
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences25
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs14
mean25.14
std17.69
cv0.704
sampleLengths
019
16
246
317
437
512
610
747
813
912
1041
1165
1210
1317
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount0
totalSentences25
matches(empty)
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs65
matches(empty)
28.57% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount1
semicolonCount0
flaggedSentences1
totalSentences25
ratio0.04
matches
0"Lanterns cast sickly green and purple glows across bizarre wares hung from iron hooks—shriveled roots, jars containing churning violet smoke, and weapons forged from dark, light-absorbing metal."
94.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount356
adjectiveStacks1
stackExamples
0"over slick concrete steps"
adverbCount4
adverbRatio0.011235955056179775
lyAdverbCount2
lyAdverbRatio0.0056179775280898875
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences25
echoCount0
echoWords(empty)
90.95% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences25
mean14.08
std5.31
cv0.377
sampleLengths
019
16
222
35
419
517
68
710
819
912
1010
1116
128
1323
1413
1512
1614
1716
1811
1912
2012
2127
2214
2310
2417
96.00% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats1
diversityRatio0.64
totalSentences25
uniqueOpeners16
0.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount0
totalSentences25
matches(empty)
ratio0
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount2
totalSentences25
matches
0"She reached the top of"
1"She descended past the rusted"
ratio0.08
40.00% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount21
totalSentences25
matches
0"Rain slicked the asphalt across"
1"Rubber soles slapped against the"
2"Detective Harlow Quinn punched her"
3"A sharp jaw set tight."
4"The figure ahead rounded the"
5"Quinn closed the gap, heels"
6"Water soaked through her trench"
7"She reached the top of"
8"A rusted iron gate hung"
9"A jagged piece of bone"
10"Quinn paused at the threshold,"
11"Shadows stretched weirdly down the"
12"Footsteps echoed ahead, splashing through"
13"Quinn gripped the butt of"
14"She descended past the rusted"
15"The tunnel walls wept black"
16"A market carved out of"
17"Stalls fashioned from rotting timber"
18"Lanterns cast sickly green and"
19"The target slipped between two"
ratio0.84
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences25
matches(empty)
ratio0
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences21
technicalSentenceCount1
matches
0"Beneath the street level, the air grew thick, humming with an invisible static charge that made the hairs on her arms stand upright."
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
82.5021%