Run: 2026-02-19-01KHTYRYFJ8T3D3YAMRX8T0BQ0

Run Details

Duration:
1m 3s
Cost:
$0.000709
Provider:
DeepInfra

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 hammered against the pavement, turning the neon reflections into liquid streaks of color. Harlow Quinn sprinted down the alley, her boots splashing through puddles that swallowed the sound of her footsteps. Ahead, the figure in the dark hoodie darted around a corner—too fast for an ordinary civilian. Too fast for someone who wasn’t hiding something. She skidded around the bend, her sharp jaw set, fingers brushing the holster at her hip. The hooded figure vaulted over a stack of crates without breaking stride. Military training kicked in—she gauged the distance, planted a foot on the wet wood, and hauled herself over. The alley opened onto a narrow street lined with shuttered shops. The hooded figure bolted left, toward the flickering green glow of a neon sign—The Raven’s Nest. Harlow’s pulse spiked. That bar had come up too many times in her case files to be coincidence. She pushed harder, lungs burning. The suspect ducked inside. The door swung shut behind them as she reached it. She caught it with her palm, hesitated. The worn leather watch on her wrist ticked softly, a reminder of time slipping away. Inside, the bar was dim, the air thick with the scent of whiskey and old paper. Maps and photographs covered the walls, their edges blurred by shadows. No sign of the runner. A man leaned against the counter, swirling a glass of something amber. His dark curls were damp from the rain, the Saint Christopher medallion glinting at his throat. Tomás Herrera. Former paramedic. Current problem. "You lost, Detective?" He didn’t look up. "Cut the crap, Herrera. Who just came in here?" His fingers tapped the glass. "Lots of people come and go." She stepped closer, rain dripping from her coat onto the hardwood. "Try again." Tomás finally met her gaze, warm brown eyes assessing. "You’re chasing ghosts tonight." A crash from the back room. Harlow’s head snapped toward the sound. Tomás sighed. "You really don’t want to go back there." She was already moving. The bookshelf along the far wall stood slightly ajar. Behind it, a narrow passage led downward, the air growing colder with each step. The walls were rough brick, slick with condensation. Voices echoed up from below—hushed, urgent. Harlow eased her gun from its holster. The descent opened into a cavernous space, the arched ceiling of an abandoned Tube station looming overhead. Stalls lined the platforms, their wares obscured by flickering lantern light. The Veil Market. Bone tokens clinked as traders exchanged them. A woman with too-sharp teeth grinned at her from behind a table of vials. Her target was halfway across the platform, weaving through the crowd. Harlow hesitated. This wasn’t her jurisdiction. Wasn’t even her world. But Morris had vanished chasing leads like this. She stepped forward. The market went quiet. Dozens of eyes turned toward her. The hooded figure stopped running. Slowly, they turned. Harlow’s finger hovered near the trigger. "Wrong place to bring a gun, Detective," a voice murmured behind her. She didn’t look back. The figure pulled down their hood. Her breath caught. It wasn’t a suspect. It was DS Morris.
created_at"2026-02-19T12:42:37.944Z" 2/19/2026, 12:42:37 PM
model"deepseek/deepseek-chat-v3-0324"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency630
moderation_latency(null)
generation_time63328
tokens_prompt1140
tokens_completion868
native_tokens_prompt1002
native_tokens_completion741
native_tokens_completion_images(null)
native_tokens_reasoning0
native_tokens_cached960
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"
usage0.00070857
router(null)
provider_responses
0
endpoint_id"820376cb-f110-4d56-ab52-5bd6ca269420"
id"chatcmpl-RhAnaAIvHtlf17JUWVInECHh"
is_byokfalse
latency82
model_permaslug"deepseek/deepseek-chat-v3-0324"
provider_name"DeepInfra"
status200
api_type"completions"
id"gen-1771504957-iuqRNgRPLjyZAJirYKPD"
upstream_id"chatcmpl-RhAnaAIvHtlf17JUWVInECHh"
total_cost0.00070857
cache_discount0.0000624
upstream_inference_cost0
provider_name"DeepInfra"

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags2
adverbTagCount0
adverbTags(empty)
dialogueSentences7
tagDensity0.286
leniency0.571
rawRatio0
effectiveRatio0
61.83% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount524
totalAiIsmAdverbs4
found
0
adverb"softly"
count1
1
adverb"really"
count1
2
adverb"slightly"
count1
3
adverb"slowly"
count1
highlights
0"softly"
1"really"
2"slightly"
3"slowly"
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)
42.75% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount524
totalAiIsms6
found
0
word"footsteps"
count1
1
word"pulse"
count1
2
word"reminder"
count1
3
word"glinting"
count1
4
word"echoed"
count1
5
word"looming"
count1
highlights
0"footsteps"
1"pulse"
2"reminder"
3"glinting"
4"echoed"
5"looming"
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
narrationSentences59
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount0
narrationSentences59
filterMatches
0"watch"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences64
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
maxSentenceWordsSeen19
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords519
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions2
unquotedAttributions0
matches(empty)
87.50% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions20
wordCount480
uniqueNames12
maxNameDensity1.25
worstName"Harlow"
maxWindowNameDensity2
worstWindowName"Harlow"
discoveredNames
Quinn1
Raven1
Nest1
Saint1
Christopher1
Herrera1
Tube1
Veil1
Market1
Morris2
Harlow6
Tomás3
persons
0"Quinn"
1"Raven"
2"Saint"
3"Christopher"
4"Herrera"
5"Market"
6"Morris"
7"Harlow"
8"Tomás"
places(empty)
globalScore0.875
windowScore1
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences35
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount519
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences64
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs32
mean16.22
std15.99
cv0.986
sampleLengths
057
146
245
39
459
55
634
77
89
911
1013
1113
1212
1310
144
1531
166
1738
1821
1911
2010
218
223
2310
248
256
2612
274
286
293
304
314
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount0
totalSentences59
matches(empty)
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount1
totalVerbs91
matches
0"wasn’t hiding"
0.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount4
semicolonCount0
flaggedSentences4
totalSentences64
ratio0.063
matches
0"Ahead, the figure in the dark hoodie darted around a corner—too fast for an ordinary civilian."
1"Military training kicked in—she gauged the distance, planted a foot on the wet wood, and hauled herself over."
2"The hooded figure bolted left, toward the flickering green glow of a neon sign—The Raven’s Nest."
3"Voices echoed up from below—hushed, urgent."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount485
adjectiveStacks0
stackExamples(empty)
adverbCount14
adverbRatio0.0288659793814433
lyAdverbCount4
lyAdverbRatio0.008247422680412371
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences64
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences64
mean8.11
std4.8
cv0.591
sampleLengths
015
118
216
38
416
512
618
711
816
93
1015
115
124
1310
147
1515
1616
1711
185
1912
2016
212
222
232
247
259
265
276
2811
292
309
314
326
336
342
358
364
379
3814
398
406
417
4217
4311
443
457
4614
4711
482
494
76.04% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats3
diversityRatio0.484375
totalSentences64
uniqueOpeners31
100.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount2
totalSentences54
matches
0"Too fast for someone who"
1"Slowly, they turned."
ratio0.037
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount14
totalSentences54
matches
0"She skidded around the bend,"
1"She pushed harder, lungs burning."
2"She caught it with her"
3"His dark curls were damp"
4"He didn’t look up"
5"His fingers tapped the glass."
6"She stepped closer, rain dripping"
7"She was already moving."
8"Her target was halfway across"
9"She stepped forward."
10"She didn’t look back."
11"Her breath caught."
12"It wasn’t a suspect."
13"It was DS Morris."
ratio0.259
34.07% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount46
totalSentences54
matches
0"The rain hammered against the"
1"Harlow Quinn sprinted down the"
2"She skidded around the bend,"
3"The hooded figure vaulted over"
4"Military training kicked in—she gauged"
5"The alley opened onto a"
6"The hooded figure bolted left,"
7"Harlow’s pulse spiked."
8"That bar had come up"
9"She pushed harder, lungs burning."
10"The suspect ducked inside."
11"The door swung shut behind"
12"She caught it with her"
13"The worn leather watch on"
14"Maps and photographs covered the"
15"A man leaned against the"
16"His dark curls were damp"
17"He didn’t look up"
18"His fingers tapped the glass."
19"She stepped closer, rain dripping"
ratio0.852
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences54
matches(empty)
ratio0
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences21
technicalSentenceCount1
matches
0"Harlow Quinn sprinted down the alley, her boots splashing through puddles that swallowed the sound of her footsteps."
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags2
uselessAdditionCount0
matches(empty)
7.14% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags1
fancyCount1
fancyTags
0"a voice murmured (murmur)"
dialogueSentences7
tagDensity0.143
leniency0.286
rawRatio1
effectiveRatio0.286
83.6446%