Run: 2026-02-19-01KHTXRRH5AX768ASS67RN8W4H

Run Details

Duration:
5.4s
Cost:
$0.000215
Provider:
Clarifai

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
The rain lashed down, a cold, relentless curtain over London’s Soho. Detective Harlow Quinn’s polished shoes slipped on the slick pavement as she surged forward, the neon sign of The Raven’s Nest – a sickly green glow – blurring past her windshield. Her breath misted in the frigid air, visible in the sudden flash of a streetlamp. The suspect, a shadow in a dark coat, had bolted from the bar’s entrance, disappearing into the maze of narrow, rain-slicked streets. Quinn’s hand tightened on the steering wheel, knuckles white against the leather. She’d seen the way he’d looked at Herrera – that fleeting, desperate glance before vanishing. The paramedic’s involvement wasn’t just a hunch anymore; it was a lead, cold and sharp. She floored the accelerator, the engine roaring as the car skidded around the corner, tires spitting gravel. The chase was on, the city’s pulse pounding in her ears. Quinn’s mind raced, not just with the pursuit, but with the ghost of DS Morris. The unexplained circumstances, the supernatural edge to the case – it all pointed here, to this man, to this bar. She couldn’t let him slip away again. Not like Morris. The suspect turned down a narrower alley, ducking between dripping dumpsters. Quinn followed, heart hammering against her ribs, the sound swallowed by the drumming rain. The air grew colder, heavier, smelling faintly of ozone and damp stone. The alley opened into a dead end, a brick wall looming ahead. The suspect pressed himself against it, breathing hard, eyes wide with panic. Quinn pulled up short, hand hovering near her holster, her gaze fixed on him. “Herrera,” she breathed, the name a low command. “You know why I’m here.” He didn’t move, just stared at the wall, sweat beading on his forehead despite the chill. “Detective,” he managed, his voice rough, strained. “Just… let me go.” “Not yet,” Quinn said, stepping closer. “Where’s the girl?” His eyes darted, searching for an escape. “I don’t know what you mean.” “Don’t lie to me,” she pressed, her voice low but cutting through the rain’s roar. “You were with her at the Nest. You know something.” He flinched, a muscle jumping in his cheek. “She’s gone. Safe. Now let me go.” Quinn’s hand tightened on her gun. “Safe? From who? From you?” She took another step, closing the distance. “Tell me where she is, or I swear to God, I’ll make you talk.” He swallowed hard, his gaze flicking towards the brick wall. “She’s… she’s down there,” he whispered, jerking a thumb towards the shadowed alley behind him. “In the… the market.” Quinn’s breath hitched. The Veil Market. Herrera’s secret. The bone token. Her pulse hammered against her ribs. The market moved locations every full moon. Tonight, it was beneath Camden. But was it safe? Was it even real? The supernatural edge to Morris’s death clawed at her thoughts. She’d seen things, felt things, things that didn’t belong in a police report. Following Herrera into that darkness… it was like stepping off a cliff. But letting him walk away… that was worse. A cold dread settled in her gut, a weight she couldn’t shake. The choice was hers, and the rain fell, indifferent, on the rain-slicked brick wall.
created_at"2026-02-19T12:25:03.276Z" 2/19/2026, 12:25:03 PM
model"arcee-ai/trinity-mini-20251201"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency129
moderation_latency(null)
generation_time5320
tokens_prompt1140
tokens_completion1396
native_tokens_prompt949
native_tokens_completion1150
native_tokens_completion_images(null)
native_tokens_reasoning534
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"
usage0.000215205
router(null)
provider_responses
0
endpoint_id"73d82c49-90ae-4223-a860-83ed0810821f"
id"c68a0dd56d1c4ea3b6c88cb1fad0ac32"
is_byokfalse
latency129
model_permaslug"arcee-ai/trinity-mini-20251201"
provider_name"Clarifai"
status200
api_type"completions"
id"gen-1771503903-sT7h7uzbnU3RveKaxZkF"
upstream_id"c68a0dd56d1c4ea3b6c88cb1fad0ac32"
total_cost0.000215205
cache_discount(null)
upstream_inference_cost0
provider_name"Clarifai"

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags6
adverbTagCount0
adverbTags(empty)
dialogueSentences14
tagDensity0.429
leniency0.857
rawRatio0
effectiveRatio0
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount536
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)
16.04% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount536
totalAiIsms9
found
0
word"fleeting"
count1
1
word"roaring"
count1
2
word"pulse"
count2
3
word"pounding"
count1
4
word"raced"
count1
5
word"looming"
count1
6
word"chill"
count1
7
word"weight"
count1
highlights
0"fleeting"
1"roaring"
2"pulse"
3"pounding"
4"raced"
5"looming"
6"chill"
7"weight"
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
emotionTells1
narrationSentences47
matches
0"e with panic"
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount0
hedgeCount0
narrationSentences47
filterMatches(empty)
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences55
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
maxSentenceWordsSeen29
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords538
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions5
unquotedAttributions0
matches(empty)
64.53% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions22
wordCount468
uniqueNames11
maxNameDensity1.71
worstName"Quinn"
maxWindowNameDensity2.5
worstWindowName"Quinn"
discoveredNames
London1
Soho1
Harlow1
Quinn8
Raven1
Nest1
Herrera3
Morris3
Veil1
Market1
Camden1
persons
0"Harlow"
1"Quinn"
2"Raven"
3"Herrera"
4"Morris"
5"Market"
places
0"London"
1"Soho"
globalScore0.645
windowScore0.833
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences35
glossingSentenceCount0
matches(empty)
14.13% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches1
per1kWords1.859
wordCount538
matches
0"not just with the pursuit, but with the ghost of DS Morris"
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences55
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs12
mean44.83
std37.16
cv0.829
sampleLengths
0121
173
275
313
427
59
613
725
815
932
1029
11106
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount0
totalSentences47
matches(empty)
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs77
matches(empty)
0.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount4
semicolonCount1
flaggedSentences4
totalSentences55
ratio0.073
matches
0"Detective Harlow Quinn’s polished shoes slipped on the slick pavement as she surged forward, the neon sign of The Raven’s Nest – a sickly green glow – blurring past her windshield."
1"She’d seen the way he’d looked at Herrera – that fleeting, desperate glance before vanishing."
2"The paramedic’s involvement wasn’t just a hunch anymore; it was a lead, cold and sharp."
3"The unexplained circumstances, the supernatural edge to the case – it all pointed here, to this man, to this bar."
94.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount466
adjectiveStacks1
stackExamples
0"narrow, rain-slicked streets."
adverbCount11
adverbRatio0.023605150214592276
lyAdverbCount2
lyAdverbRatio0.004291845493562232
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences55
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences55
mean9.78
std5.63
cv0.576
sampleLengths
011
131
215
322
412
515
615
717
811
915
1020
117
123
1311
1414
1512
1612
1712
1814
198
205
2116
227
234
246
253
267
276
2815
2910
308
317
326
3312
3414
3510
3615
374
383
393
402
413
426
437
445
454
464
4710
4813
495
69.09% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats2
diversityRatio0.43636363636363634
totalSentences55
uniqueOpeners24
0.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount0
totalSentences46
matches(empty)
ratio0
80.87% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount16
totalSentences46
matches
0"Her breath misted in the"
1"She’d seen the way he’d"
2"She floored the accelerator, the"
3"She couldn’t let him slip"
4"she breathed, the name a"
5"He didn’t move, just stared"
6"he managed, his voice rough,"
7"His eyes darted, searching for"
8"she pressed, her voice low"
9"He flinched, a muscle jumping"
10"She took another step, closing"
11"He swallowed hard, his gaze"
12"he whispered, jerking a thumb"
13"Her pulse hammered against her"
14"She’d seen things, felt things,"
15"it was like stepping off"
ratio0.348
14.35% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount41
totalSentences46
matches
0"The rain lashed down, a"
1"Detective Harlow Quinn’s polished shoes"
2"Her breath misted in the"
3"The suspect, a shadow in"
4"Quinn’s hand tightened on the"
5"She’d seen the way he’d"
6"The paramedic’s involvement wasn’t just"
7"She floored the accelerator, the"
8"The chase was on, the"
9"Quinn’s mind raced, not just"
10"The unexplained circumstances, the supernatural"
11"She couldn’t let him slip"
12"The suspect turned down a"
13"Quinn followed, heart hammering against"
14"The air grew colder, heavier,"
15"The alley opened into a"
16"The suspect pressed himself against"
17"Quinn pulled up short, hand"
18"she breathed, the name a"
19"He didn’t move, just stared"
ratio0.891
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences46
matches(empty)
ratio0
80.75% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences23
technicalSentenceCount2
matches
0"She’d seen the way he’d looked at Herrera – that fleeting, desperate glance before vanishing."
1"She’d seen things, felt things, things that didn’t belong in a police report."
0.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags6
uselessAdditionCount2
matches
0"he managed, his voice rough, strained"
1"she pressed, her voice low but cutting through the rain’s roar"
0.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags4
fancyCount3
fancyTags
0"she breathed (breathe)"
1"she pressed (press)"
2"he whispered (whisper)"
dialogueSentences14
tagDensity0.286
leniency0.571
rawRatio0.75
effectiveRatio0.429
71.1252%