Run: 2026-07-25-01KYCWFYN4ADVP0EW3MVJ3M360

Run Details

Duration:
3.2s
Cost:
$0.001593
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 slicked the pavement of the Soho back alley, reflecting the green neon hum of The Raven's Nest. Detective Harlow Quinn adjusted the collar of her trench coat, her gaze locked on the frantic figure darting between rust-stained dumpsters. Eighteen years on the force built a tolerance for miserable weather, but tonight the chill bit straight through wool and skin. Tomás Hernandez scrambled over a waist-high brick wall, his Saint Christopher medallion flashing silver in the sodium streetlamps before he vanished into the subterranean depths of the old Camden Tube station. Harlow covered the distance in long, measured strides, military precision guiding every footfall despite the slick concrete. She reached the iron-grated stairs leading downward into the abandoned station, the smell of damp earth and stale ozone rising to meet her. A yellowing sign warned off trespassers, but the scrape of rubber soles echoed from the darkness below. She touched the worn leather watch on her left wrist, checking the time. Three minutes past midnight. Iron steps groaned beneath her boots as she descended into the pitch, flashlights slicing beams against soot-covered tile walls. The air grew thick, carrying the metallic tang of spilled copper and something ancient, like dust undisturbed for centuries. A heavy oak door barred the lower landing, carved with jagged runes that caught the beam of her torch. Tomás pulled the latch from the other side, revealing a chaotic underground bazaar carved deep into the London clay. The Veil Market pulsed with a sickly green illumination from hundreds of glowing vials hung from vaulted brick ceilings. Hooded figures milled between stalls draped in velvet, trading bone tokens for glass jars of iridescent fluids and rusted surgical instruments. Harlow stepped past the threshold, hand hovering over her holster. The ambient chatter died instantly, dozens of pale faces turning toward her uniform with predatory curiosity. A vendor dropped a heavy brass scale onto a wooden counter, the metallic clang ringing off the curved arches. Tomás vanished behind a curtain of heavy iron chains at the far end of the cavernous platform. Shadows shifted behind a stack of mahogany crates, blocking the path toward the hanging chains. A towering figure with scales crawling up his neck stepped forward, brandishing a curved skinning knife. Put the badge away, copper. This floor belongs to the market now. Harlow didn't blink, her sharp jaw setting as she closed the distance to the scaled brawler. Step aside or spend the night in my holding cell.
created_at"2026-07-25T14:57:27.726Z" 7/25/2026, 2:57:27 PM
model"google/gemini-3.5-flash-lite-20260721"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency333
moderation_latency(null)
generation_time3092
tokens_prompt1104
tokens_completion657
native_tokens_prompt1042
native_tokens_completion512
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"
usage0.0015926
router(null)
provider_responses
0
endpoint_id"6bd8f433-79e1-416c-b407-1772eb796c9a"
id"185kav3zNOHVjMcPkpus8AY"
is_byokfalse
latency333
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-1784991447-U6bFcF8b25LDxJin7xhO"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1784991447-22ycODdKvDMHhmBXIqwx"
upstream_id"185kav3zNOHVjMcPkpus8AY"
total_cost0.0015926
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)
wordCount412
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)
2.91% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount412
totalAiIsms8
found
0
word"chill"
count1
1
word"depths"
count1
2
word"measured"
count1
3
word"footfall"
count1
4
word"echoed"
count1
5
word"chaotic"
count1
6
word"pulsed"
count1
7
word"velvet"
count1
highlights
0"chill"
1"depths"
2"measured"
3"footfall"
4"echoed"
5"chaotic"
6"pulsed"
7"velvet"
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
maxSentenceWordsSeen32
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords412
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions0
unquotedAttributions0
matches(empty)
100.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions19
wordCount412
uniqueNames14
maxNameDensity0.97
worstName"Harlow"
maxWindowNameDensity1
worstWindowName"Harlow"
discoveredNames
Soho1
Raven1
Nest1
Harlow4
Quinn1
Hernandez1
Saint1
Christopher1
Camden1
Tube1
London1
Veil1
Market1
Tomás3
persons
0"Raven"
1"Harlow"
2"Quinn"
3"Hernandez"
4"Saint"
5"Christopher"
6"Tomás"
places
0"Soho"
1"London"
2"Market"
globalScore1
windowScore1
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences23
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount412
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
totalParagraphs12
mean34.33
std18.61
cv0.542
sampleLengths
060
131
274
338
438
540
645
717
831
912
1016
1110
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)
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences25
ratio0
matches(empty)
94.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount416
adjectiveStacks1
stackExamples
0"against soot-covered tile"
adverbCount4
adverbRatio0.009615384615384616
lyAdverbCount2
lyAdverbRatio0.004807692307692308
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences25
echoCount0
echoWords(empty)
80.04% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences25
mean16.48
std5.77
cv0.35
sampleLengths
018
121
221
331
417
523
617
713
84
919
1019
1119
1219
1319
1421
1510
1616
1719
1817
1915
2016
215
227
2316
2410
100.00% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats0
diversityRatio0.6
totalSentences25
uniqueOpeners15
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 iron-grated stairs"
1"She touched the worn leather"
ratio0.08
80.00% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount19
totalSentences25
matches
0"Water slicked the pavement of"
1"Detective Harlow Quinn adjusted the"
2"Tomás Hernandez scrambled over a"
3"Harlow covered the distance in"
4"She reached the iron-grated stairs"
5"A yellowing sign warned off"
6"She touched the worn leather"
7"The air grew thick, carrying"
8"A heavy oak door barred"
9"Tomás pulled the latch from"
10"The Veil Market pulsed with"
11"Harlow stepped past the threshold,"
12"The ambient chatter died instantly,"
13"A vendor dropped a heavy"
14"Tomás vanished behind a curtain"
15"Shadows shifted behind a stack"
16"A towering figure with scales"
17"This floor belongs to the"
18"Harlow didn't blink, her sharp"
ratio0.76
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
analyzedSentences22
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
88.0890%