Run: 2026-02-19-01KHTYAZKMPN5CH0VH7KQQT5KV

Run Details

Duration:
8.0s
Cost:
$0.003268
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 lashed against the grimy brickwork of the Soho alleyway. Detective Harlow Quinn’s breath plumed in the frigid night air, her closely cropped salt-and-pepper hair plastered to her scalp. Water streamed down her face, mingling with the sweat that pricked her eyebrows. The silhouette of Tomás Herrera, a fleeting shadow against the flickering neon glow of distant streetlights, disappeared around a corner. “Hold it, Herrera!” Her voice, a ragged bellow, fought against the roar of traffic and the hammering rain. He didn't slow. The rhythmic slap of his trainers on the wet pavement, a faint drumbeat, drew her forward. Her worn leather watch, a dark band on her left wrist, pressed against her skin. Eighteen years on the force, and the thrill of the chase still coiled a tight knot in her gut. She pushed past overflowing bins, their stench of stale ale and rotten food momentarily lost in the downpour. A discarded umbrella, its ribs splayed like a broken wing, snagged at her ankle. She kicked it aside, her sharp jaw setting with grim determination. The alley opened onto a wider street, a shimmering black ribbon under the streetlights. Herrera, a dark blur, wove through the handful of late-night pedestrians, his short, curly dark-brown hair catching the light as he glanced back. His olive skin, usually warm, now looked pale under the relentless rain. His strides were long, powerful. He moved with a practised agility, the kind she knew came from years of navigating unpredictable environments. A familiar glint caught her eye, the Saint Christopher medallion around his neck, a small anchor in the chaos. Harlow accelerated, her military precision bearing pushing her legs harder. The slick pavement offered little purchase. A taxi, its yellow paint dull in the rain, blared its horn as she darted in front of it. The driver, a dark shape behind the misted window, shouted an obscenity. She ignored him. All that mattered was Herrera. He veered left, into a labyrinth of narrow lanes, their historical names carved into crumbling stone. The ambient light of the city thinned, swallowed by the close-set buildings. Rain continued its relentless assault, turning the cobblestones into treacherous, polished obsidian. She slid, a gasp catching in her throat, catching herself on a cold, damp wall. Her palm smarted. A flash of movement ahead. Herrera ducked into a shadowed archway, the entrance to what looked like a derelict building. The air grew heavy, smelling of damp earth and decay. Her brown eyes narrowed. A flicker of doubt, cold and unwelcome, brushed against her resolve. This was not a familiar path. This was the kind of place where things went missing and never resurfaced. She pushed past the threshold, the world plunging into near darkness. A faint, metallic clang echoed from deeper within, followed by the distant rumble of a train. An abandoned Tube station. Her mind clicked. The Veil Market. Her hand went to the grip of her service pistol, a reassuring weight. The air grew colder, thick with a strange, cloying scent she couldn’t place – like ozone and old incense. The walls, she could just make them out, were rough-hewn stone, patched with crumbling concrete. Water dripped from unseen cracks, splashing into puddles that reflected the barest slivers of light from above. “Herrera!” Her voice echoed, swallowed by the cavernous space. Silence. Only the faint thrum of the underground. She moved cautiously, her boots crunching on loose gravel. The scar on his left forearm, a thin white line from a knife attack she’d read in his file, played across her mind. He was a medic. A good one, by all accounts. So why was he running? And what connection did he have to this hidden, supernatural underbelly of London? Morris’s ghost, never far, whispered at the back of her mind. Unexplained circumstances. Supernatural origins. He lost his partner under them. A faint light, a sickly green glow, pulsed ahead. It beckoned, an unnatural beacon in the gloom. The air grew warmer, carrying with it a cacophony of sounds: hushed murmurs, strange chimes, the crackle of unknown energies. The scent intensified, becoming a dizzying mix of roasted spices, something floral and sweet, and an acrid tang that made her nose twitch. This was not a normal place. This was the Veil. She reached an opening, an archway carved roughly into the stone. Beyond it, a world of impossible vibrancy exploded into view. Stalls, draped with shimmering fabrics and flickering lanterns, lined a wide underground platform. Figures, shadowed and indistinct, moved through the throng. Some were human, others… less so. Horns, extra limbs, eyes that glittered with unnatural light. It was a carnival of the arcane, pulsing with an unsettling energy. Her breath hitched. The bone token, she remembered the briefing. The entry requirement. She didn't have one. Stepping in meant a direct violation of protocol, a dive into an unknown that could swallow her whole. The uniform, the shield, the law – all of it meant nothing here. Here, a different kind of order reigned. But Herrera was in there. The small glimpse she’d had of him, a flash of his dark hair, a flicker of his familiar medallion, just before the crowd swallowed him. He was a familiar face in a landscape of nightmares. To let him go now, to turn back… it felt like a betrayal. A cold certainty settled in her gut. She had to follow.
created_at"2026-02-19T12:35:00.348Z" 2/19/2026, 12:35:00 PM
model"google/gemini-2.5-flash"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency250
moderation_latency(null)
generation_time7954
tokens_prompt1140
tokens_completion1386
native_tokens_prompt1042
native_tokens_completion1182
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)
origin"https://ncbench.com/"
is_byokfalse
finish_reason"stop"
native_finish_reason"STOP"
usage0.0032676
router(null)
provider_responses
0
endpoint_id"16c01e26-9b91-4d22-b487-ed35634b017d"
is_byokfalse
latency250
model_permaslug"google/gemini-2.5-flash"
provider_name"Google AI Studio"
status200
api_type"completions"
id"gen-1771504500-X4VBlq01wYJj6u2pEr6I"
upstream_id(null)
total_cost0.0032676
cache_discount(null)
upstream_inference_cost0
provider_name"Google AI Studio"

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags2
adverbTagCount0
adverbTags(empty)
dialogueSentences2
tagDensity1
leniency1
rawRatio0
effectiveRatio0
94.47% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount904
totalAiIsmAdverbs1
found
0
adverb"cautiously"
count1
highlights
0"cautiously"
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)
wordCount904
totalAiIsms20
found
0
word"fleeting"
count1
1
word"rhythmic"
count1
2
word"navigating"
count1
3
word"familiar"
count4
4
word"glint"
count1
5
word"treacherous"
count1
6
word"flicker"
count2
7
word"resolve"
count1
8
word"echoed"
count2
9
word"weight"
count1
10
word"silence"
count1
11
word"pulsed"
count1
12
word"beacon"
count1
13
word"gloom"
count1
14
word"cacophony"
count1
highlights
0"fleeting"
1"rhythmic"
2"navigating"
3"familiar"
4"glint"
5"treacherous"
6"flicker"
7"resolve"
8"echoed"
9"weight"
10"silence"
11"pulsed"
12"beacon"
13"gloom"
14"cacophony"
66.67% Cliché density
Target: ≤1 cliche(s) per 800-word window
totalCliches2
maxInWindow2
found
0
label"eyes widened/narrowed"
count1
1
label"flicker of emotion"
count1
highlights
0"eyes narrowed"
1"A flicker of doubt"
100.00% Emotion telling (show vs. tell)
Target: ≤3% sentences with emotion telling
emotionTells0
narrationSentences86
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount0
narrationSentences86
filterMatches
0"watch"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences86
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
maxSentenceWordsSeen25
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords900
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions1
unquotedAttributions0
matches(empty)
100.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions18
wordCount896
uniqueNames12
maxNameDensity0.56
worstName"Herrera"
maxWindowNameDensity1.5
worstWindowName"Herrera"
discoveredNames
Soho1
Harlow2
Quinn1
Tomás1
Herrera5
Saint1
Christopher1
Tube1
Veil2
Market1
Silence1
London1
persons
0"Harlow"
1"Quinn"
2"Tomás"
3"Herrera"
4"Saint"
5"Christopher"
places
0"Soho"
1"London"
globalScore1
windowScore1
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences62
glossingSentenceCount1
matches
0"looked like a derelict building"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount900
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences86
matches(empty)
68.60% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs15
mean60
std23.41
cv0.39
sampleLengths
062
118
296
390
455
558
664
737
864
99
1089
1170
1269
1355
1464
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount0
totalSentences86
matches(empty)
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs140
matches(empty)
76.41% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount2
semicolonCount0
flaggedSentences2
totalSentences86
ratio0.023
matches
0"The air grew colder, thick with a strange, cloying scent she couldn’t place – like ozone and old incense."
1"The uniform, the shield, the law – all of it meant nothing here."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount900
adjectiveStacks0
stackExamples(empty)
adverbCount22
adverbRatio0.024444444444444446
lyAdverbCount9
lyAdverbRatio0.01
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences86
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences86
mean10.47
std5.98
cv0.572
sampleLengths
010
119
213
320
418
53
616
715
819
918
1014
1111
1214
1323
1412
155
1617
1719
1810
196
2019
2112
223
235
2416
2512
2612
2715
283
295
3015
3110
324
3311
346
3513
3611
3716
384
393
403
4113
4219
4315
4417
459
461
477
489
4923
58.91% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats6
diversityRatio0.3953488372093023
totalSentences86
uniqueOpeners34
81.30% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount2
totalSentences82
matches
0"All that mattered was Herrera."
1"Only the faint thrum of"
ratio0.024
83.41% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount28
totalSentences82
matches
0"Her voice, a ragged bellow,"
1"He didn't slow."
2"Her worn leather watch, a"
3"She pushed past overflowing bins,"
4"She kicked it aside, her"
5"His olive skin, usually warm,"
6"His strides were long, powerful."
7"He moved with a practised"
8"She ignored him."
9"He veered left, into a"
10"She slid, a gasp catching"
11"Her palm smarted."
12"Her brown eyes narrowed."
13"She pushed past the threshold,"
14"Her mind clicked."
15"Her hand went to the"
16"Her voice echoed, swallowed by"
17"She moved cautiously, her boots"
18"He was a medic."
19"He lost his partner under"
ratio0.341
27.07% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount71
totalSentences82
matches
0"Rain lashed against the grimy"
1"Detective Harlow Quinn’s breath plumed"
2"Water streamed down her face,"
3"The silhouette of Tomás Herrera,"
4"Her voice, a ragged bellow,"
5"He didn't slow."
6"The rhythmic slap of his"
7"Her worn leather watch, a"
8"She pushed past overflowing bins,"
9"A discarded umbrella, its ribs"
10"She kicked it aside, her"
11"The alley opened onto a"
12"Herrera, a dark blur, wove"
13"His olive skin, usually warm,"
14"His strides were long, powerful."
15"He moved with a practised"
16"A familiar glint caught her"
17"Harlow accelerated, her military precision"
18"The slick pavement offered little"
19"A taxi, its yellow paint"
ratio0.866
60.98% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount1
totalSentences82
matches
0"To let him go now,"
ratio0.012
63.49% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences45
technicalSentenceCount5
matches
0"Water streamed down her face, mingling with the sweat that pricked her eyebrows."
1"She slid, a gasp catching in her throat, catching herself on a cold, damp wall."
2"Water dripped from unseen cracks, splashing into puddles that reflected the barest slivers of light from above."
3"The scent intensified, becoming a dizzying mix of roasted spices, something floral and sweet, and an acrid tang that made her nose twitch."
4"Stepping in meant a direct violation of protocol, a dive into an unknown that could swallow her whole."
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags2
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags0
86.0440%