Run: 2026-02-19-01KHTX6GPC8HPKYEPNKBREWAZ3

Run Details

Duration:
24.4s
Cost:
$0.000905
Provider:
ModelRun

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="4412" name="Aurora Carter" aliases="Rory, Laila, Aurora, Carter, Malphora" pronouns="she/her" species="Human" storyRole="Protagonist"> <eyeColor>bright blue</eyeColor> <hair>straight shoulder-length black</hair> <height>5'6"</height> <age>25</age> <scar>small crescent-shaped scar on her left wrist from a childhood accident</scar> <description>Aurora, referred to by her friends as Rory, is cool-headed, intelligent, and known for quick out-of-the-box thinking.</description> <backstory>Born in Cardiff to an Irish barrister father (Brendan Carter) and Welsh teacher mother (Jennifer Carter née Ellis), Rory reluctantly pursued Pre-Law at Cardiff University. She fled to London at the behest of her childhood friend Eva after leaving an abusive ex named Evan. By day, Rory works part-time as a delivery person for Yu-Fei Cheung's Golden Empress restaurant. She lives in a flat above Silas' bar.</backstory> </character> <character id="4413" name="Silas Blackwood" aliases="Silas, Si, the Spymaster" pronouns="he/him" species="Human" storyRole="Mentor"> <eyeColor>hazel</eyeColor> <hair>grey-streaked auburn</hair> <height>6'1"</height> <age>58</age> <beard>neatly trimmed, matching his grey-streaked auburn hair</beard> <limp>slight limp in his left leg from an old knee injury</limp> <signetRing>silver signet ring, always worn on his right hand</signetRing> <description>Silas is a retired intelligence operative turned bar owner. He carries himself with quiet authority.</description> <backstory>Former MI6 field agent who retired after a botched operation in Prague left him with a permanent knee injury. He opened "The Raven's Nest" bar in Soho as a front for his network of contacts.</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> </codex> Continue the story using the following instructions: <instructions> Write a fully fleshed out scene of at least 1000 words in the literary fiction genre. Two old friends who haven't seen each other in years run into each other unexpectedly at a bar. One of them has changed significantly. Through their conversation and the tension between who they were and who they've become, reveal the weight of time and unspoken regret. 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 neon sign buzzed overhead, its green glow pooling on the wet pavement outside The Raven’s Nest. Inside, the hum of murmured conversations and clinking glasses settled into a low din. Aurora wiped down the bartop, her sleeves rolled to her elbows, the crescent scar on her wrist catching the dim light. The scar was old—almost forgotten—but she’d been thinking about it lately. Funny how the past turned up when you least expected. Silas shuffled behind her, stacking glasses with methodical precision. "You’ve got that look,” he said without glancing up. “What look?” “Like you’re waiting for something to happen.” She smirked, tossing the rag into the sink. “Always am.” The door creaked open, letting in a gust of damp London air. She glanced up—habit more than curiosity—and froze. Evan stood there, dripping rainwater onto the floorboards. Not Evan-the-ex. Not Evan-the-abusive-prick. Just… Evan. Older. Softer around the edges. He wore a navy peacoat, his dark hair slightly longer than she remembered, streaked with the first threads of grey. His hands hovered awkwardly at his sides, as if he wasn’t sure where to put them. Aurora’s throat tightened. Silas straightened, his eyes flicking between them. He said nothing. She was grateful for that. Evan cleared his throat. “Rory.” The name sounded foreign on his tongue. Nobody called her that anymore. Silas nudged a glass toward her. Subtle. A prompt. Aurora exhaled, forced her fingers to unclench. “Evan.” A beat passed. Neither moved. "You’re—working here?" He gestured vaguely at the bar. "Temporarily." Her tone was sharper than she intended. Evan nodded stiffly, rainwater dripping from his coat hem onto the floor. "Can I... sit?" She wanted to say no. To tell him to turn around and walk out. Instead, she jerked her chin toward the stool at the far end of the bar. Silas disappeared into the back room without a word, leaving them alone in the dim glow of the bar lights. Evan slid onto the stool, his fingers tapping against the polished wood. “You look good,” he said finally. Aurora poured him a whiskey—neat, because she remembered. She pushed it toward him with more一切的力气 than necessary. “You don’t.” He laughed, but it was hollow. “Fair.” They sat in silence while he drank. She watched the way his throat moved when he swallowed, the way his fingers flexed around the glass. Familiar, but not. "I heard you left Cardiff," he said eventually. "Yeah." "Why London?" She shrugged. "Why not?" Evan exhaled, swirling the amber liquid in his glass. "I’m sorry," he said quietly. Aurora leaned against the counter, arms folded. "For which part?" His jaw tightened. "All of it." That wasn’t good enough. It would never be good enough. She wanted to ask what he was doing here—how he’d even found her. What right he had to walk back into her life like he deserved a place in it. But the words caught in her throat. Evan traced the rim of his glass with a fingertip. "You changed your hair." It was such a stupid, pointless observation that she almost laughed. "Yeah. Six years is a long time." He looked up then, his expression unreadable. "Too long." She didn’t answer. Outside, the rain picked up, tapping against the windows like impatient fingers. Silas reappeared, his limp more pronounced in the damp weather. He glanced between them, then nodded toward the back room. “Got a shipment coming in. Need a hand.” Aurora pushed off from the bar. Her pulse thrummed in her ears, loud enough that she barely heard Evan say her name as she walked away. Silas closed the door behind them. “Well,” he muttered. She pressed her palms against the cool metal of the storage shelves. “Don’t.” He didn’t.
created_at"2026-02-19T12:15:05.424Z" 2/19/2026, 12:15:05 PM
model"deepseek/deepseek-chat-v3-0324"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency256
moderation_latency(null)
generation_time24401
tokens_prompt1094
tokens_completion1049
native_tokens_prompt991
native_tokens_completion918
native_tokens_completion_images(null)
native_tokens_reasoning0
native_tokens_cached5
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"
usage0.00090506
router(null)
provider_responses
0
endpoint_id"a3938710-1b99-4a1f-85f4-2494f3f659d3"
id"chatcmpl-b15a62715b7545c89b3bd4e1e83c3be8"
is_byokfalse
latency66
model_permaslug"deepseek/deepseek-chat-v3-0324"
provider_name"ModelRun"
status200
api_type"completions"
id"gen-1771503305-XZveuGfFQMBOi3qt3IOc"
upstream_id"chatcmpl-b15a62715b7545c89b3bd4e1e83c3be8"
total_cost0.00090506
cache_discount(null)
upstream_inference_cost0
provider_name"ModelRun"

Evaluation details

Result Evaluator Details Meta Data
0.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags7
adverbTagCount4
adverbTags
0"He gestured vaguely [vaguely]"
1"he said finally [finally]"
2"he said eventually [eventually]"
3"he said quietly [quietly]"
dialogueSentences25
tagDensity0.28
leniency0.56
rawRatio0.571
effectiveRatio0.32
92.06% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount630
totalAiIsmAdverbs1
found
0
adverb"slightly"
count1
highlights
0"slightly"
100.00% AI-ism character names
Target: 0 AI-default names (16 tracked, −20% each)
codexExemptions
0"Blackwood"
found(empty)
100.00% AI-ism location names
Target: 0 AI-default location names (33 tracked, −20% each)
codexExemptions(empty)
found(empty)
52.38% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount630
totalAiIsms6
found
0
word"methodical"
count1
1
word"silence"
count1
2
word"familiar"
count1
3
word"traced"
count1
4
word"unreadable"
count1
5
word"pulse"
count1
highlights
0"methodical"
1"silence"
2"familiar"
3"traced"
4"unreadable"
5"pulse"
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
narrationSentences71
matches
0"was grateful"
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount0
hedgeCount0
narrationSentences71
filterMatches(empty)
hedgeMatches(empty)
95.70% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences89
gibberishSentences1
adjustedGibberishSentences1
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
maxSentenceWordsSeen21
ratio0.011
matches
0"She pushed it toward him with more一切的力气 than necessary."
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords619
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions7
unquotedAttributions0
matches(empty)
50.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions27
wordCount549
uniqueNames8
maxNameDensity1.82
worstName"Evan"
maxWindowNameDensity3.5
worstWindowName"Evan"
discoveredNames
Raven1
Nest1
London1
Evan-the-ex1
Evan-the-abusive-prick1
Evan10
Aurora6
Silas6
persons
0"Evan-the-ex"
1"Evan-the-abusive-prick"
2"Evan"
3"Aurora"
4"Silas"
places
0"Raven"
1"London"
globalScore0.589
windowScore0.5
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences44
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount619
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences89
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs43
mean14.4
std13.42
cv0.932
sampleLengths
073
118
22
37
410
519
68
747
83
915
105
1112
129
138
145
158
168
1715
1829
1920
2018
2119
227
2328
248
251
262
274
2814
2910
306
3140
327
3314
3418
359
363
3712
3828
3926
409
4113
422
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount0
totalSentences71
matches(empty)
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount1
totalVerbs109
matches
0"was doing"
14.45% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount6
semicolonCount0
flaggedSentences4
totalSentences89
ratio0.045
matches
0"The scar was old—almost forgotten—but she’d been thinking about it lately."
1"She glanced up—habit more than curiosity—and froze."
2"Aurora poured him a whiskey—neat, because she remembered."
3"She wanted to ask what he was doing here—how he’d even found her."
94.38% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount560
adjectiveStacks0
stackExamples(empty)
adverbCount26
adverbRatio0.04642857142857143
lyAdverbCount9
lyAdverbRatio0.01607142857142857
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences89
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences89
mean6.96
std5.1
cv0.733
sampleLengths
017
114
221
311
410
59
69
72
87
98
102
1112
127
138
142
152
161
171
181
194
2020
2116
223
237
243
255
264
271
287
295
306
311
322
337
341
353
362
378
388
3912
403
415
429
4315
4420
4512
466
478
489
492
79.40% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats1
diversityRatio0.48314606741573035
totalSentences89
uniqueOpeners43
55.56% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount1
totalSentences60
matches
0"Instead, she jerked her chin"
ratio0.017
46.67% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount26
totalSentences60
matches
0"he said without glancing up"
1"She smirked, tossing the rag"
2"She glanced up—habit more than"
3"He wore a navy peacoat,"
4"His hands hovered awkwardly at"
5"He said nothing."
6"She was grateful for that."
7"He gestured vaguely at the"
8"Her tone was sharper than"
9"She wanted to say no."
10"he said finally"
11"She pushed it toward him"
12"He laughed, but it was"
13"They sat in silence while"
14"She watched the way his"
15"he said eventually"
16"he said quietly"
17"His jaw tightened."
18"It would never be good"
19"She wanted to ask what"
ratio0.433
35.00% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount51
totalSentences60
matches
0"The neon sign buzzed overhead,"
1"Aurora wiped down the bartop,"
2"The scar was old—almost forgotten—but"
3"Silas shuffled behind her, stacking"
4"he said without glancing up"
5"She smirked, tossing the rag"
6"The door creaked open, letting"
7"She glanced up—habit more than"
8"Evan stood there, dripping rainwater"
9"He wore a navy peacoat,"
10"His hands hovered awkwardly at"
11"Aurora’s throat tightened."
12"Silas straightened, his eyes flicking"
13"He said nothing."
14"She was grateful for that."
15"Evan cleared his throat."
16"The name sounded foreign on"
17"Nobody called her that anymore."
18"Silas nudged a glass toward"
19"Aurora exhaled, forced her fingers"
ratio0.85
83.33% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount1
totalSentences60
matches
0"To tell him to turn"
ratio0.017
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences22
technicalSentenceCount0
matches(empty)
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
totalTags5
fancyCount1
fancyTags
0"he muttered (mutter)"
dialogueSentences25
tagDensity0.2
leniency0.4
rawRatio0.2
effectiveRatio0.08
83.2974%