Run: 2026-04-25-01KQ2F4XTN55V1D0VYQW8FTHEZ

Run Details

Duration:
50.9s
Cost:
$0.001468
Provider:
DeepSeek

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
Detective Harlow Quinn’s lungs burned as her boots hammered against wet pavement. Rain lashed her face in diagonal sheets, each drop a needle of cold against her cheeks. The man she was chasing—Tomás Herrera, former paramedic, current person of interest in three separate supernatural-related incidents—glanced over his shoulder and put on a burst of speed. He moved well for someone who’d just vaulted a police barrier. “Police! Stop!” The words tore from her throat, useless and obligatory. They never stopped. Tomás ducked left into an alley, his dark jacket flaring behind him. Quinn followed without breaking stride, her hand brushing the rough brick as she rounded the corner. A stack of pallets clattered as he shoved past them. She hurdled the debris, her worn leather watch catching the glint of a security light. The alley spat them out onto Charing Cross Road. Traffic hissed through standing water. A double-decker bus groaned past, its windows fogged with breath and body heat. Tomás dodged between two cabs and made for the Tube entrance on the opposite side. Quinn’s jaw tightened. He was heading underground. Predictable. Stupid, even. The Northern Line at this hour would be packed tight with last-call commuters. Nowhere to run. Except he didn’t slow for the ticket barriers. Tomás vaulted the gate with a dancer’s grace, his Saint Christopher medallion swinging loose from his collar as he landed. The Transport Police officer on duty shouted something that got lost in the station’s echo. Quinn flashed her warrant card without pausing. “Met Police—clear the platform!” The escalator carried her down into the fluorescent hum of the Underground. Her eyes swept the platform as she descended. A cluster of late-night travelers milled near the vending machines. A busker packed away his guitar. And there—Tomás Herrera, moving fast along the yellow line, heading for the tunnel mouth where the darkness swallowed the tracks. “Bloody hell,” Quinn muttered. She hit the platform running. A train announcement crackled overhead, something about a signal failure at Camden. The passengers grumbled. Quinn pressed past them, her hand on the grip of her extendable baton. “Herrera! The tunnel’s live. You’ll fry.” Tomás glanced back. His olive skin looked sallow under the station lights, but his eyes held something she hadn’t expected. Not fear. Calculation. “You don’t want to follow me, Detective.” “Try me.” He jumped down onto the tracks. Quinn’s training screamed at her—wait for backup, secure the scene, do not pursue into an active rail tunnel. She was already swinging herself down after him, her shoes crunching on the gravel bed. The rails hummed with a faint vibration that she felt through her soles. Distant train. Maybe two minutes out. Tomás moved deeper into the tunnel, his figure dissolving into shadow. Quinn pulled her Maglite and thumbed it on. The beam cut a narrow path through the dark, illuminating rusted maintenance ladders, old posters plastered to the curved walls, a rat that skittered away from the light. She followed the sound of his footsteps. The tunnel bent left, and the ambient glow of the station vanished entirely. Quinn’s world shrank to the circle of her torch and the crunch of her own feet. The air grew colder, thick with the mineral smell of old stone and something else—something sharp and herbal, like burnt sage. A light flickered ahead. Not electric. Orange and unsteady, like a flame. “Herrera?” The tunnel opened into a disused service alcove. Graffiti covered the walls in layers so thick they looked like scales. And there, beside a rusted maintenance door, Tomás Herrera stood with a small glass lantern in his hand. The flame inside burned blue at the edges. “Last chance,” he said. “Turn back.” Quinn unclipped her baton. Extended it with a snap. “Step away from the door.” “You don't know what you’re walking into.” “I know you’ve been running off-the-books medical treatments for three months. I know your patients all have connections to the Veil. And I know my partner died investigating something that didn’t fit the official report.” The words came out harder than she intended. Three years, and Morris was still a raw nerve. “So don’t tell me what I don’t know.” Tomás’s expression shifted. Something flickered behind his eyes—recognition, maybe even sympathy. He touched the medallion at his throat. “Morris,” he said quietly. “The DS who went missing near the old Bethnal Green station.” Quinn’s grip tightened on the baton. “What do you know about that?” “Enough to tell you that following me through this door won’t give you the answers you want.” A horn sounded behind them. The train. Closer now, maybe thirty seconds out. The rails began to sing. Tomás pushed the maintenance door open. Beyond it, Quinn saw stairs—old ironwork spiraling down into a warm, amber glow. Voices drifted up, dozens of them, a low murmur punctuated by the clink of glass and the rattle of what sounded like dice. The herbal smell intensified, undercut with iron and incense. The Veil Market. She’d heard whispers. Dismissed them as street mythology. A supernatural black market that moved locations every full moon, accessible only with the right token. Her superiors laughed it off. Morris hadn’t. “Detective.” Tomás stood in the doorway, his silhouette rimmed with golden light. “You come down there with that badge and that baton, you won’t make it past the first stall. These people don’t recognize Metropolitan Police authority. They recognize older laws.” “Is that a threat?” “It’s a professional courtesy. One I’m extending because I think you actually want justice for Morris, not just closure.” The train horn blared. Quinn could feel the vibration in her teeth now, the air pressure shifting as the train entered the tunnel behind them. She had seconds to decide. Back onto the platform, call for backup that would never believe her, file another report that would gather dust while the supernatural world kept its secrets. Or forward, down those stairs, into a place that operated by rules she didn’t understand. Tomás saw the decision on her face before she made it. He reached into his pocket and tossed something small and pale through the air. Quinn caught it reflexively—a bone token, carved with symbols that seemed to shift under her thumb. “Show that at the gate. Don’t speak unless spoken to. Don’t draw your weapon unless you mean to use it.” He paused. “And Detective—Morris didn’t die because he was a cop. He died because he was polite enough to ask questions, and stupid enough to believe the answers.” Tomás disappeared through the door. The train roared into the tunnel, its headlamp flooding the alcove with blinding white light. Quinn pressed herself flat against the wall, felt the rush of air tear at her coat, watched the carriages blur past inches from her face. When the train cleared, the maintenance door still stood open. The stairs still spiraled down into amber light. Quinn slipped the bone token into her pocket alongside her warrant card. Two methods of entry. Two kinds of authority. She didn’t know which one would keep her alive. She stepped through the door and started down.
created_at"2026-04-25T14:02:00.305Z" 4/25/2026, 2:02:00 PM
model"deepseek/deepseek-v4-pro-20260423"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency1000
moderation_latency(null)
generation_time48326
tokens_prompt1140
tokens_completion1949
native_tokens_prompt1003
native_tokens_completion1597
native_tokens_completion_images(null)
native_tokens_reasoning0
native_tokens_cached896
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"
usage0.001468415
router(null)
provider_responses
0
endpoint_id"d084170b-dd99-4e53-9ae1-b63881f3cfbf"
id"42530388-f042-480d-b701-a3d736f466de"
is_byokfalse
latency294
model_permaslug"deepseek/deepseek-v4-pro-20260423"
provider_name"DeepSeek"
status200
user_agent"langchainjs-openai/1.0.0 ((node/v24.14.1; linux; x64))"
http_referer(null)
request_id"req-1777125720-ydeVd52eEbCirljRc9Re"
session_id(null)
api_type"completions"
id"gen-1777125720-Cs0qnfklLgibSBHtmX4c"
upstream_id"42530388-f042-480d-b701-a3d736f466de"
total_cost0.001468415
cache_discount0.00035728
upstream_inference_cost0
provider_name"DeepSeek"
response_cache_source_id(null)

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags7
adverbTagCount1
adverbTags
0"he said quietly [quietly]"
dialogueSentences23
tagDensity0.304
leniency0.609
rawRatio0.143
effectiveRatio0.087
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1193
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)
66.47% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1193
totalAiIsms8
found
0
word"glint"
count1
1
word"predictable"
count1
2
word"echo"
count1
3
word"footsteps"
count1
4
word"flickered"
count2
5
word"electric"
count1
6
word"could feel"
count1
highlights
0"glint"
1"predictable"
2"echo"
3"footsteps"
4"flickered"
5"electric"
6"could feel"
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
narrationSentences102
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount2
narrationSentences102
filterMatches
0"watch"
hedgeMatches
0"began to"
1"seemed to"
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences118
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen45
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1183
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions9
unquotedAttributions0
matches(empty)
67.18% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions51
wordCount966
uniqueNames21
maxNameDensity1.66
worstName"Quinn"
maxWindowNameDensity2.5
worstWindowName"Quinn"
discoveredNames
Harlow1
Quinn16
Tomás13
Herrera3
Charing1
Cross1
Road1
Tube1
Northern1
Line1
Saint1
Christopher1
Transport1
Police1
Underground1
Camden1
Maglite1
Three1
Morris2
Veil1
Market1
persons
0"Harlow"
1"Quinn"
2"Tomás"
3"Herrera"
4"Line"
5"Saint"
6"Christopher"
7"Morris"
places
0"Charing"
1"Cross"
2"Road"
3"Camden"
4"Three"
globalScore0.672
windowScore0.833
36.36% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences66
glossingSentenceCount3
matches
0"looked like scales"
1"sounded like dice"
2"symbols that seemed to shift under her thumb"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1183
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences118
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs45
mean26.29
std18.62
cv0.708
sampleLengths
055
111
214
353
442
526
650
74
856
94
1033
116
1223
137
142
156
1652
1747
187
1950
2012
211
2246
236
2414
257
2660
2718
2815
2912
3017
3118
3251
3334
3441
354
3619
3725
3846
3941
4048
4145
4218
4329
448
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount1
totalSentences102
matches
0"got lost"
70.97% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount3
totalVerbs155
matches
0"was chasing"
1"was heading"
2"was already swinging"
0.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount8
semicolonCount0
flaggedSentences7
totalSentences118
ratio0.059
matches
0"The man she was chasing—Tomás Herrera, former paramedic, current person of interest in three separate supernatural-related incidents—glanced over his shoulder and put on a burst of speed."
1"And there—Tomás Herrera, moving fast along the yellow line, heading for the tunnel mouth where the darkness swallowed the tracks."
2"Quinn’s training screamed at her—wait for backup, secure the scene, do not pursue into an active rail tunnel."
3"The air grew colder, thick with the mineral smell of old stone and something else—something sharp and herbal, like burnt sage."
4"Something flickered behind his eyes—recognition, maybe even sympathy."
5"Beyond it, Quinn saw stairs—old ironwork spiraling down into a warm, amber glow."
6"Quinn caught it reflexively—a bone token, carved with symbols that seemed to shift under her thumb."
88.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount978
adjectiveStacks2
stackExamples
0"former paramedic, current person"
1"separate supernatural-related incidents—"
adverbCount22
adverbRatio0.022494887525562373
lyAdverbCount4
lyAdverbRatio0.00408997955010225
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences118
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences118
mean10.03
std7.33
cv0.731
sampleLengths
012
116
227
311
411
53
612
716
810
915
109
115
1213
1315
143
154
161
172
1813
193
208
2120
2215
237
244
2512
268
2710
286
2920
304
315
3212
333
3413
356
363
3717
382
391
407
412
426
4318
4415
4513
462
474
4811
498
68.64% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats4
diversityRatio0.4322033898305085
totalSentences118
uniqueOpeners51
73.26% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount2
totalSentences91
matches
0"Nowhere to run."
1"Maybe two minutes out."
ratio0.022
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount18
totalSentences91
matches
0"He moved well for someone"
1"They never stopped."
2"She hurdled the debris, her"
3"He was heading underground."
4"Her eyes swept the platform"
5"She hit the platform running."
6"His olive skin looked sallow"
7"He jumped down onto the"
8"She was already swinging herself"
9"She followed the sound of"
10"He touched the medallion at"
11"he said quietly"
12"She’d heard whispers."
13"Her superiors laughed it off."
14"She had seconds to decide."
15"He reached into his pocket"
16"She didn’t know which one"
17"She stepped through the door"
ratio0.198
47.91% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount75
totalSentences91
matches
0"Detective Harlow Quinn’s lungs burned"
1"Rain lashed her face in"
2"The man she was chasing—Tomás"
3"He moved well for someone"
4"The words tore from her"
5"They never stopped."
6"Tomás ducked left into an"
7"Quinn followed without breaking stride,"
8"A stack of pallets clattered"
9"She hurdled the debris, her"
10"The alley spat them out"
11"Traffic hissed through standing water."
12"A double-decker bus groaned past,"
13"Tomás dodged between two cabs"
14"Quinn’s jaw tightened."
15"He was heading underground."
16"The Northern Line at this"
17"Tomás vaulted the gate with"
18"The Transport Police officer on"
19"Quinn flashed her warrant card"
ratio0.824
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences91
matches(empty)
ratio0
74.83% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences42
technicalSentenceCount4
matches
0"The Transport Police officer on duty shouted something that got lost in the station’s echo."
1"She was already swinging herself down after him, her shoes crunching on the gravel bed."
2"The beam cut a narrow path through the dark, illuminating rusted maintenance ladders, old posters plastered to the curved walls, a rat that skittered away from …"
3"A supernatural black market that moved locations every full moon, accessible only with the right token."
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags7
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags3
fancyCount1
fancyTags
0"Quinn muttered (mutter)"
dialogueSentences23
tagDensity0.13
leniency0.261
rawRatio0.333
effectiveRatio0.087
83.1211%