Run: 2026-02-19-01KHT0Z05PWVBK2KNJT4Y7T3M1

Run Details

Duration:
30.1s
Cost:
$0.027901
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="4414" name="Eva Kowalski" aliases="Eva, Evie" pronouns="she/her" species="Human" storyRole="Best Friend"> <eyeColor>green</eyeColor> <hair>curly red</hair> <height>5'4"</height> <age>26</age> <glasses>round glasses</glasses> <satchel>worn leather satchel full of books</satchel> <freckles>freckled complexion</freckles> <nervousHabit>tucking hair behind her left ear</nervousHabit> <description>Aurora's childhood friend and an occult researcher.</description> <backstory>Moved to London two years before Aurora and works as a research assistant at the British Museum's restricted archives. She holds a master's degree in Ancient History from Oxford.</backstory> </character> <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> <item id="2004" name="Veil Compass" aliases="the Compass, shadow compass" type="Tool" origin="The Veil Market"> <casingMaterial>small brass compass</casingMaterial> <faceMarkings>face etched with protective sigils</faceMarkings> <needle>points toward the nearest supernatural rift or portal</needle> <patina>casing has a patina of verdigris</patina> <creator>crafted by a Shade artisan</creator> <description>A compass attuned to supernatural energy.</description> </item> </codex> Continue the story using the following instructions: <instructions> Write a fully fleshed out scene of at least 1000 words in the mystery genre. A detective arrives at a crime scene in an unusual location. Something is wrong — the evidence doesn't add up. A colleague is present, offering a different interpretation. Through careful observation and deduction, the detective begins to see what others have missed. 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
The air grew cold and heavy the deeper she descended. Each step down the iron spiral staircase echoed in the cavernous dark, a metallic complaint against the silence. Below, portable floodlights cast long, distorted shadows that danced across grimy, tiled walls. The familiar stench of the Tube—stale air, hot metal, and a century of London's grime—was layered with something else. The sharp, clean scent of ozone and the cloying sweetness of rot. Detective Harlow Quinn’s boots crunched on loose gravel at the bottom. She ducked under the blue and white tape, her gaze sweeping the platform. It was a ghost station, a forgotten pocket beneath Camden's thriving streets. Posters from a bygone era peeled from the walls in damp, curling sheets. Forensics officers in white paper suits moved like spectres through the artificial glare, their hushed tones absorbed by the oppressive quiet. A young constable with a face too earnest for a murder scene met her by the tracks. PC Evans. He clutched a tablet, his knuckles white. "DI Quinn. Not much to see. We got the call an hour ago from a transit patrol. Looks like a transient dispute got out of hand." Quinn slid on a pair of latex gloves, her movements brisk and efficient. She walked towards the body without a word, her attention fixed on the scene. "Victim's a John Doe. No ID, no phone. Another rough sleeper found him. He’s over there, giving his statement." Evans gestured with his chin towards a huddled figure wrapped in a foil blanket. The victim lay near the platform's edge, sprawled on his back. Quinn knelt, the knees of her trousers darkening on the damp concrete. She angled her torch, the beam cutting a clean cone through the gloom. The man was young, maybe mid-twenties. His coat was expensive, a dark wool overcoat now stained and torn at the sleeve. Beneath the grime smeared on his face, his features were sharp, his jaw clean-shaven. She lifted one of his hands. The fingernails were immaculate. "This man doesn't sleep on concrete, Constable." Evans shifted his weight. "Could be recent. Lost his job, his flat. It happens fast." Quinn ignored him, her light tracing the man’s torso. His shirt was burned away in patches, but the skin beneath wasn't charred black. It was a pale, waxy white, etched with intricate patterns that spiralled across his chest. They were familiar, like something she'd seen in a dusty textbook on ancient cultures. The edges of the burns were too precise, too deliberate for an accidental fire. "Pathologist have a preliminary idea?" "She's baffled," Evans admitted, stepping closer. "Says it looks like a massive electrical burn, but there’s no entry or exit wound. The third rail is dead on this line, has been for fifty years. No scorch marks on his clothes, either. Just… that." He pointed at the dead man's chest. Quinn stood, turning her attention to the surrounding area. There was no blood, save for a small trickle from the back of the victim’s head where he'd hit the platform. No weapon. No discarded bottles or drug paraphernalia. The scene was clean. Too clean. "You said there was a dispute?" "That’s what the witness said. Heard shouting. A lot of it. Then a scream." "What were they shouting about?" Quinn’s voice was low, cutting through the ambient hum of the lights. "He couldn't make it out. Said it didn't sound like English." Quinn swept her torch beam across the floor. The tiles were slick with decades of damp, but near the body, a wide section seemed different. Fainter. She crouched again, her light almost parallel to the ground. Faint, swirling lines were visible, patterns that mirrored the marks on the victim's skin. Someone had tried to scrub them away. "Forensics get these?" Evans craned his neck. "They logged them. Figured it was just old graffiti. This whole place is covered in it." "This isn't graffiti." Quinn ran a gloved finger over the faint markings. "This was done recently. And someone made an effort to get rid of it." Her eyes narrowed, scanning the length of the abandoned platform. She walked slowly, her gaze fixed on the ground, tracing the invisible lines of the crime. Nothing made sense. A well-dressed man with clean hands, killed by an impossible force, in a place no one should be, with symbols scrubbed from the floor. This wasn’t a squabble. This was a ritual. Her gaze fell on something small, nestled in the grimy trough between the rails. A pale fleck against the dark ballast. It was out of place, catching the light in a way the dull stones did not. "Bag that for me." She pointed. A forensics officer carefully descended onto the track bed, tweezers in hand. A few moments later, he presented her with a small plastic evidence bag. Quinn took it. Inside was a small piece of bone, no bigger than her thumb. It was carved, polished by countless hands into the shape of a distorted animal skull. It was smooth, almost warm to the touch through the thin plastic. It felt ancient. It felt wrong. She looked from the strange object in her hand to the body on the platform, then to the scrubbed symbols on the floor. Evans was still talking, offering theories about gang initiations or drug deals gone sideways, his voice a drone of predictable nonsense. But Quinn no longer heard him. The pieces rearranged themselves in her mind, not into a picture she understood, but into the outline of one she knew was vast and hidden. The victim wasn't a vagrant. The fight wasn't a simple dispute. This station wasn't just abandoned. It was a stage. And whatever happened here had nothing to do with the city she knew. The bone token felt heavy in her palm, a key to a door she hadn't realised existed until now.
created_at"2026-02-19T04:01:39.009Z" 2/19/2026, 4:01:39 AM
model"google/gemini-2.5-pro"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency3208
moderation_latency(null)
generation_time30087
tokens_prompt1149
tokens_completion2272
native_tokens_prompt1073
native_tokens_completion2656
native_tokens_completion_images0
native_tokens_reasoning1357
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"
usage0.02790125
router(null)
provider_responses
0
endpoint_id"b261d15b-95ce-4c8c-8bce-00eb0dc1ff77"
is_byokfalse
latency3208
model_permaslug"google/gemini-2.5-pro"
provider_name"Google AI Studio"
status200
api_type"completions"
id"gen-1771473699-fIjvgBnDw2FaCmrxRO8v"
upstream_id(null)
total_cost0.02790125
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
totalTags6
adverbTagCount0
adverbTags(empty)
dialogueSentences16
tagDensity0.375
leniency0.75
rawRatio0
effectiveRatio0
89.85% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount985
totalAiIsmAdverbs2
found
0
adverb"slowly"
count1
1
adverb"carefully"
count1
highlights
0"slowly"
1"carefully"
80.00% AI-ism character names
Target: 0 AI-default names (17 tracked, −20% each)
codexExemptions(empty)
found
0"Evans"
100.00% AI-ism location names
Target: 0 AI-default location names (33 tracked, −20% each)
codexExemptions(empty)
found(empty)
28.93% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount985
totalAiIsms14
found
0
word"echoed"
count1
1
word"silence"
count1
2
word"familiar"
count2
3
word"oppressive"
count1
4
word"efficient"
count1
5
word"gloom"
count1
6
word"weight"
count1
7
word"tracing"
count2
8
word"etched"
count1
9
word"intricate"
count1
10
word"scanning"
count1
11
word"predictable"
count1
highlights
0"echoed"
1"silence"
2"familiar"
3"oppressive"
4"efficient"
5"gloom"
6"weight"
7"tracing"
8"etched"
9"intricate"
10"scanning"
11"predictable"
100.00% Cliché density
Target: ≤1 cliche(s) per 800-word window
totalCliches1
maxInWindow1
found
0
label"eyes widened/narrowed"
count1
highlights
0"eyes narrowed"
100.00% Emotion telling (show vs. tell)
Target: ≤3% sentences with emotion telling
emotionTells0
narrationSentences75
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount0
hedgeCount1
narrationSentences75
filterMatches(empty)
hedgeMatches
0"tried to"
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences84
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
maxSentenceWordsSeen44
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords980
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions5
unquotedAttributions0
matches(empty)
83.33% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions20
wordCount797
uniqueNames6
maxNameDensity1.25
worstName"Quinn"
maxWindowNameDensity2.5
worstWindowName"Quinn"
discoveredNames
Tube1
London1
Harlow1
Quinn10
Camden1
Evans6
persons
0"Harlow"
1"Quinn"
2"Camden"
3"Evans"
places
0"London"
globalScore0.873
windowScore0.833
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences56
glossingSentenceCount1
matches
0"seemed different"
97.96% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches1
per1kWords1.02
wordCount980
matches
0"not into a picture she understood, but into the outline of one she knew was vast"
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences84
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs27
mean36.3
std25.8
cv0.711
sampleLengths
072
170
226
326
427
533
681
77
815
966
105
1150
1244
136
1414
1517
1611
1757
183
1920
2087
2137
226
2325
2448
2550
2677
91.23% Passive voice overuse
Target: ≤2% passive sentences
passiveCount3
totalSentences75
matches
0"was layered"
1"was burned"
2"was carved"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs120
matches(empty)
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount2
semicolonCount0
flaggedSentences1
totalSentences84
ratio0.012
matches
0"The familiar stench of the Tube—stale air, hot metal, and a century of London's grime—was layered with something else."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount802
adjectiveStacks0
stackExamples(empty)
adverbCount18
adverbRatio0.022443890274314215
lyAdverbCount2
lyAdverbRatio0.0024937655860349127
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences84
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences84
mean11.67
std7.44
cv0.638
sampleLengths
010
118
213
319
412
511
613
712
813
921
1017
112
127
1326
1413
1514
1633
1711
1812
1913
206
2115
2214
236
244
257
264
2711
289
2914
3015
3114
3214
335
346
3544
369
3721
382
396
404
412
426
4314
4417
4511
468
4717
481
4910
61.51% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats10
diversityRatio0.44047619047619047
totalSentences84
uniqueOpeners37
0.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount0
totalSentences70
matches(empty)
ratio0
94.29% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount22
totalSentences70
matches
0"She ducked under the blue"
1"It was a ghost station,"
2"He clutched a tablet, his"
3"She walked towards the body"
4"She angled her torch, the"
5"His coat was expensive, a"
6"She lifted one of his"
7"His shirt was burned away"
8"It was a pale, waxy"
9"They were familiar, like something"
10"He pointed at the dead"
11"She crouched again, her light"
12"Her eyes narrowed, scanning the"
13"She walked slowly, her gaze"
14"Her gaze fell on something"
15"It was out of place,"
16"It was carved, polished by"
17"It was smooth, almost warm"
18"It felt ancient."
19"It felt wrong."
ratio0.314
24.29% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount61
totalSentences70
matches
0"The air grew cold and"
1"Each step down the iron"
2"The familiar stench of the"
3"The sharp, clean scent of"
4"Detective Harlow Quinn’s boots crunched"
5"She ducked under the blue"
6"It was a ghost station,"
7"Posters from a bygone era"
8"Forensics officers in white paper"
9"A young constable with a"
10"He clutched a tablet, his"
11"Quinn slid on a pair"
12"She walked towards the body"
13"Evans gestured with his chin"
14"The victim lay near the"
15"Quinn knelt, the knees of"
16"She angled her torch, the"
17"The man was young, maybe"
18"His coat was expensive, a"
19"She lifted one of his"
ratio0.871
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences70
matches(empty)
ratio0
89.29% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences40
technicalSentenceCount3
matches
0"Below, portable floodlights cast long, distorted shadows that danced across grimy, tiled walls."
1"It was a pale, waxy white, etched with intricate patterns that spiralled across his chest."
2"Faint, swirling lines were visible, patterns that mirrored the marks on the victim's skin."
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags6
uselessAdditionCount0
matches(empty)
87.50% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags1
fancyCount1
fancyTags
0"Evans admitted (admit)"
dialogueSentences16
tagDensity0.063
leniency0.125
rawRatio1
effectiveRatio0.125
84.2722%