Run: 2026-07-25-01KYCYA87WHF828JN7C6D0QD4K

Run Details

Duration:
2.4s
Cost:
$0.001303
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
Water poured from copper gutters, pooling in grease-filmed troughs along the curb. Detective Harlow Quinn checked the worn leather watch on her left wrist. Midnight. Salt-and-pepper crop plastered flat against her skull. A sharp jaw set hard as she rounded the corner of the brick terrace. Footsteps echoed ahead, splashing through standing puddles down the dead-end alleyway behind the rail line. Tomás Herrera scrambled over a rusting chain-link fence, copper jacket tearing on the upper bar. Copper buttons scraped metal. Quinn hauled herself up the wire mesh, heels catching the lower links before dropping hard onto the ballast stones of the abandoned rail spur. The scent of ozone and rotting diesel hung thick in the damp air. Ahead, the suspect vanished down a gaping concrete stairwell leading into the disused Tube station beneath Camden. A flicker of sickly yellow light bled up from the subterranean depths. A carved sliver of ribcage clattered onto the bottom step from the runner's pocket. Quinn halted at the threshold of the iron gate. Below stretched the Veil Market. The cavernous platform swallowed the city's noise, replacing it with the hum of arcane generators and the sharp tang of alchemical solvents. Stalls made of salvaged corrugated iron and plastic sheeting stretched along the tracks where commuter trains once stopped. Hooded figures leaned over tables laden with jars of iridescent powder and twitching specimens. The heat rose in greasy waves, carrying the stench of scorched feathers and wet slate. Quinn gripped the butt of her service pistol beneath her trench coat. The darkness below tasted of sulfur. Tomás darted past a merchant selling dried mandrake roots, disappearing into a labyrinth of stalls hung with rotting kelp and copper wire. Cold sweat cut a path down Quinn’s spine. She stepped past the iron gate, her boots crunching on broken tile as she descended into the subterranean bazaar.
created_at"2026-07-25T15:29:18.09Z" 7/25/2026, 3:29:18 PM
model"google/gemini-3.5-flash-lite-20260721"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency292
moderation_latency(null)
generation_time2345
tokens_prompt1104
tokens_completion493
native_tokens_prompt1042
native_tokens_completion396
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"
usage0.0013026
router(null)
provider_responses
0
endpoint_id"6bd8f433-79e1-416c-b407-1772eb796c9a"
id"TtZkaqXsCYq4sOIP3qGPkAo"
is_byokfalse
latency292
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-1784993358-fFhacRApcxZMlMFnYuJj"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1784993358-hlOGBbh9Eu53effQspVI"
upstream_id"TtZkaqXsCYq4sOIP3qGPkAo"
total_cost0.0013026
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)
wordCount310
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)
35.48% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount310
totalAiIsms4
found
0
word"footsteps"
count1
1
word"echoed"
count1
2
word"flicker"
count1
3
word"depths"
count1
highlights
0"footsteps"
1"echoed"
2"flicker"
3"depths"
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
narrationSentences24
matches(empty)
83.33% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount0
narrationSentences24
filterMatches
0"watch"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences24
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen24
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords310
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions0
unquotedAttributions0
matches(empty)
69.35% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions11
wordCount310
uniqueNames7
maxNameDensity1.61
worstName"Quinn"
maxWindowNameDensity1.5
worstWindowName"Quinn"
discoveredNames
Harlow1
Quinn5
Herrera1
Tube1
Camden1
Veil1
Market1
persons
0"Harlow"
1"Quinn"
2"Herrera"
places(empty)
globalScore0.694
windowScore1
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences21
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount310
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences24
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs10
mean31
std24.04
cv0.775
sampleLengths
061
115
24
366
414
568
615
740
88
919
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount0
totalSentences24
matches(empty)
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs46
matches(empty)
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences24
ratio0
matches(empty)
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount315
adjectiveStacks0
stackExamples(empty)
adverbCount4
adverbRatio0.012698412698412698
lyAdverbCount1
lyAdverbRatio0.0031746031746031746
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences24
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences24
mean12.92
std5.75
cv0.445
sampleLengths
012
112
21
37
414
515
615
74
824
913
1017
1112
1214
139
145
1522
1618
1714
1815
1912
206
2122
228
2319
95.83% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats1
diversityRatio0.6666666666666666
totalSentences24
uniqueOpeners16
0.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount0
totalSentences23
matches(empty)
ratio0
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount1
totalSentences23
matches
0"She stepped past the iron"
ratio0.043
46.96% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount19
totalSentences23
matches
0"Water poured from copper gutters,"
1"Detective Harlow Quinn checked the"
2"Salt-and-pepper crop plastered flat against"
3"A sharp jaw set hard"
4"Footsteps echoed ahead, splashing through"
5"Tomás Herrera scrambled over a"
6"Copper buttons scraped metal."
7"Quinn hauled herself up the"
8"The scent of ozone and"
9"A flicker of sickly yellow"
10"A carved sliver of ribcage"
11"Quinn halted at the threshold"
12"The cavernous platform swallowed the"
13"Stalls made of salvaged corrugated"
14"The heat rose in greasy"
15"Quinn gripped the butt of"
16"The darkness below tasted of"
17"Tomás darted past a merchant"
18"She stepped past the iron"
ratio0.826
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences23
matches(empty)
ratio0
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences17
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
87.6987%