Run: 2026-09-03-01M1KD062BF64HDWGWMMKJQFYJ

Run Details

Duration:
2m 3s
Cost:
$0.026792
Provider:
Phala

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 green neon of The Raven’s Nest stained the puddles along Brewer Street. Inside, the air smelled of yeast and old paper. Aurora sat at a table near the wall of photographs, a half-finished pint in front of her. Her black hair had dried flat from the rain. She wore the red delivery jacket with Golden Empress stitched on the chest, the sleeves bunched at her elbows. Silas moved behind the bar with a cloth, wiping down the taps. The limp in his left leg barely slowed him. The signet ring on his right hand clicked against a glass. The door swung in on a gust of wet air. A woman stepped inside, furling a black umbrella. She scanned the room with the quick efficiency of someone used to assessing exits. Her coat was long and the color of wet slate. Chestnut hair pulled back at the nape. She carried a leather satchel over one shoulder. Aurora’s hand stopped halfway to her glass. The woman’s gaze swept past, then snapped back. Her mouth opened a fraction. “Rory?” Aurora’s spine straightened. The name landed like a stone in still water. “Eva.” Eva crossed the room in four steps, stopped at the edge of the table as if unsure whether to sit. She laughed once, a brittle sound. “God. I thought I was seeing things.” “You’re in London.” “Conference. Family law.” Eva’s eyes moved over Aurora’s face, her hair, the delivery jacket. A pause of adjustment. “You look—” “Like I just worked a double shift.” Eva sat down, placed her satchel on the empty chair beside her. “I was going to say different.” Silas appeared at the table, his approach quiet. He looked at Aurora, then at Eva. “Another for you, Rory?” “Please.” He turned to Eva, one eyebrow raised. “White wine. Whatever’s open.” Silas nodded and moved back toward the bar, his limp a soft rhythm on the floorboards. Eva watched him go. “Friend of yours?” “Landlord.” “You live here?” “Above the bar.” Aurora turned her glass in slow circles on the table. “It’s cheap.” Silence settled between them like a third person at the table. The old photographs on the wall stared out—black-and-white faces, decades dead. “You work for Golden Empress,” Eva said, reading the jacket. “Deliveries. Pay’s decent. I know the streets.” “I thought you’d be—” “Taking the bar exam?” Aurora’s voice came out sharper than she intended. She softened it. “Plans change.” Eva pressed her lips together. Her hands lay flat on the table, nails clean and squared. She wore a thin gold band on her left hand. “Married?” Aurora asked. “Engaged.” “Who’s the lucky—” “His name’s Tom. He’s a barrister.” Eva spoke quickly, as if ridding herself of something heavy. “We’re getting married in the spring.” Aurora lifted her pint. “Congratulations.” The word hung in the air, unaccompanied by anything else. Silas returned with a glass of wine and a fresh pint. He set them down without a word. His eyes met Aurora’s for a fraction of a second—a question in them. She shook her head, the motion barely there. He left them to it. Eva took a sip of wine. “Your mum said you stopped calling.” Aurora’s fingers went to the cuff of her left sleeve, where the small crescent scar sat pale against her wrist. A childhood accident. A swing chain. Eva had been there, screaming for help. The memory surfaced before she could press it down. “I needed a clean break.” “From everything?” “From Evan.” Aurora spoke the name and it tasted like rust. “You know why I left.” Eva looked down at her wine. “I know why you left Cardiff. I didn’t know it meant leaving me.” The words cut. Aurora held herself still and let them pass through her. “You told me to go,” she said. “I told you to get out of that flat. I didn’t tell you to disappear.” “What was I supposed to do, Eva? Send postcards? ‘Wish you were here, hiding from my—’” She stopped. The bar hummed around them. A man laughed too loudly near the door. Silas stacked glasses behind the bar, the clink of glass against glass a steady metronome. Eva leaned forward. “I looked for you.” Aurora blinked. “I called your dad’s office. Twice. Your mum told me you’d phoned once from a payphone and then nothing for months.” “I didn’t want him to find me.” “Evan?” Aurora nodded. Eva’s face shifted—something hard and old rising to the surface. “He came looking for you, you know.” A cold hand closed around Aurora’s ribs. “When?” Her voice came out low. “About a week after you left. Showed up at my flat, drunk, demanding to know where you’d gone. I told him I had no idea. He didn’t believe me.” Eva tugged at her sleeve, a small nervous motion. “He put his fist through my kitchen cupboard.” Aurora stared at her. The weight of that moment—Eva standing in her own kitchen, the splintered wood, the man they had both once trusted—pressed down on her chest. “I never knew.” “You weren’t there to know.” Eva’s voice broke slightly, then steadied. “I moved out the next week. Stayed with my aunt in Swansea until the lease was up.” Aurora reached across the table, her hand stopping just short of Eva’s. She didn’t close the distance. The gesture hung in the space between them, unfinished. “I’m sorry.” Eva looked at her. The years sat in the lines around her eyes—fine, faint, not yet deep. “He’s gone now. Moved to Manchester. I heard he’s done it again with someone else.” Aurora pulled her hand back. “I thought about calling you. So many times.” “Why didn’t you?” The question was simple and devastating. Aurora looked around the bar—the maps on the walls, the black-and-white photographs, the green neon bleeding through the front windows. What could she say? That every time she picked up the phone, she heard Evan’s voice in her head? That she had been ashamed of what her life had become? That she had been too afraid to hear the worry in Eva’s voice and have to lie about being fine? “I didn’t know who I was yet,” she said finally. “And I didn’t want you to see that.” Eva’s eyes softened. “Rory.” “That’s not my name anymore.” A beat of silence. “What do I call you?” “Aurora.” Eva tested it. “Aurora.” The name sat between them like a stranger. Then Eva laughed—a real laugh this time, surprising and warm. “You always hated Aurora. You used to say it sounded like a grandmother’s perfume.” Aurora smiled, a small cracked thing. “Things change.” “Some things don’t.” Eva lifted her wine. “To old friends.” Aurora lifted her pint. They didn’t touch glasses. They just drank. After a while, Eva’s phone buzzed. She glanced at it, silenced it, then looked at Aurora with an expression that held too much. “I have a dinner. Tom’s meeting me at the hotel in an hour.” “You should go.” Eva didn’t move. “We could have breakfast tomorrow. Before I leave.” Aurora nodded. She didn’t trust herself to speak. Eva stood, gathered her satchel and umbrella. She looked down at Aurora, her eyes bright with something unsaid. Then she pulled a pen from her bag, grabbed a napkin from the table, and wrote a number. “Six months from now, I want to get a call,” she said. “Or I’m coming back and breaking down this bar’s door.” “Six months.” “Starting now.” She placed the napkin next to Aurora’s glass and walked toward the door. The green neon caught her hair as she left, turning it ghostly. The door closed behind her. Aurora sat alone at the table. The napkin sat beside her pint, the ink already smudging from the condensation. Silas approached and stopped a respectful distance away. “All right?” he asked. Aurora didn’t answer. She picked up the napkin, folded it once, and tucked it into the pocket of her delivery jacket. Then she finished her pint and watched the rain streak the windows, the old photographs waiting on the walls like memories that refused to fade.
created_at"2026-09-03T10:28:28.899Z" 9/3/2026, 10:28:28 AM
model"deepseek/deepseek-v4-pro-20260813"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency1002
moderation_latency(null)
generation_time123046
tokens_prompt1063
tokens_completion6679
native_tokens_prompt1071
native_tokens_completion6094
native_tokens_completion_images(null)
native_tokens_reasoning4172
native_tokens_cached1024
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"
service_tier(null)
usage0.02679159
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.19.0; linux; x64))"
http_referer(null)
request_id"req-1788431308-vAmZeG3gCgS5dpQQ9LWN"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1788431308-VUnxtc10fpiCatNLi8do"
upstream_id"req_c59c984ddae6fae204715809a3413db2"
provider_responses
0
endpoint_id"bb1fb528-2000-460c-a65e-b82dc347c019"
id"req_c59c984ddae6fae204715809a3413db2"
is_byokfalse
latency666
model_permaslug"deepseek/deepseek-v4-pro-20260813"
provider_name"Phala"
status200
total_cost0.02679159
cache_discount0.0013312
upstream_inference_cost0
provider_name"Phala"
response_cache_source_id(null)
data_region"global"
workspace_id"97e315e5-d303-487d-83c1-83180e8a13d4"

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags15
adverbTagCount3
adverbTags
0"Eva spoke quickly [quickly]"
1"Eva’s voice broke slightly [slightly]"
2"she said finally [finally]"
dialogueSentences70
tagDensity0.214
leniency0.429
rawRatio0.2
effectiveRatio0.086
92.64% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1358
totalAiIsmAdverbs2
found
0
adverb"quickly"
count1
1
adverb"slightly"
count1
highlights
0"quickly"
1"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)
81.59% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1358
totalAiIsms5
found
0
word"scanned"
count1
1
word"eyebrow"
count1
2
word"silence"
count2
3
word"weight"
count1
highlights
0"scanned"
1"eyebrow"
2"silence"
3"weight"
66.67% Cliché density
Target: ≤1 cliche(s) per 800-word window
totalCliches2
maxInWindow2
found
0
label"weight of words/silence"
count1
1
label"hung in the air"
count1
highlights
0"The weight of that moment"
1"hung in the air"
100.00% Emotion telling (show vs. tell)
Target: ≤3% sentences with emotion telling
emotionTells0
narrationSentences114
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount0
hedgeCount0
narrationSentences114
filterMatches(empty)
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences169
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen38
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1351
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions19
unquotedAttributions0
matches(empty)
0.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions69
wordCount960
uniqueNames11
maxNameDensity2.92
worstName"Aurora"
maxWindowNameDensity5
worstWindowName"Eva"
discoveredNames
Raven1
Nest1
Brewer1
Street1
Golden1
Empress1
Aurora28
Eva27
Silence1
Evan1
Silas6
persons
0"Raven"
1"Nest"
2"Empress"
3"Aurora"
4"Eva"
5"Silence"
6"Evan"
7"Silas"
places
0"Brewer"
1"Street"
globalScore0.042
windowScore0
83.33% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences75
glossingSentenceCount2
matches
0"as if ridding herself of something heavy"
1"tasted like rust"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1351
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences169
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs94
mean14.37
std13.84
cv0.963
sampleLengths
067
132
210
347
47
513
61
712
81
933
103
1120
127
1318
1419
151
167
174
1816
197
201
213
2215
2322
2410
257
264
2717
2826
293
301
313
3222
335
3410
3544
3612
3742
385
392
4016
4119
4213
437
4415
4516
462
4728
487
492
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount1
totalSentences114
matches
0"been ashamed"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs174
matches(empty)
24.51% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount8
semicolonCount0
flaggedSentences7
totalSentences169
ratio0.041
matches
0"The old photographs on the wall stared out—black-and-white faces, decades dead."
1"His eyes met Aurora’s for a fraction of a second—a question in them."
2"Eva’s face shifted—something hard and old rising to the surface."
3"The weight of that moment—Eva standing in her own kitchen, the splintered wood, the man they had both once trusted—pressed down on her chest."
4"The years sat in the lines around her eyes—fine, faint, not yet deep."
5"Aurora looked around the bar—the maps on the walls, the black-and-white photographs, the green neon bleeding through the front windows."
6"Then Eva laughed—a real laugh this time, surprising and warm."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount970
adjectiveStacks0
stackExamples(empty)
adverbCount33
adverbRatio0.03402061855670103
lyAdverbCount7
lyAdverbRatio0.007216494845360825
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences169
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences169
mean7.99
std5.69
cv0.712
sampleLengths
013
19
217
39
419
512
69
711
810
98
1014
1110
127
138
147
158
165
171
183
199
201
2120
226
237
243
2514
264
272
287
2912
306
318
327
334
341
357
364
3716
384
393
401
413
4213
432
4411
4511
4610
477
484
4912
45.36% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats10
diversityRatio0.3076923076923077
totalSentences169
uniqueOpeners52
94.34% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount3
totalSentences106
matches
0"Then Eva laughed—a real laugh"
1"Then she pulled a pen"
2"Then she finished her pint"
ratio0.028
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount26
totalSentences106
matches
0"Her black hair had dried"
1"She wore the red delivery"
2"She scanned the room with"
3"Her coat was long and"
4"She carried a leather satchel"
5"Her mouth opened a fraction."
6"She laughed once, a brittle"
7"He looked at Aurora, then"
8"He turned to Eva, one"
9"She softened it."
10"Her hands lay flat on"
11"She wore a thin gold"
12"He set them down without"
13"His eyes met Aurora’s for"
14"She shook her head, the"
15"He left them to it."
16"Her voice came out low"
17"She didn’t close the distance."
18"she said finally"
19"They didn’t touch glasses."
ratio0.245
0.00% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount99
totalSentences106
matches
0"The green neon of The"
1"Aurora sat at a table"
2"Her black hair had dried"
3"She wore the red delivery"
4"Silas moved behind the bar"
5"The limp in his left"
6"The signet ring on his"
7"The door swung in on"
8"A woman stepped inside, furling"
9"She scanned the room with"
10"Her coat was long and"
11"Chestnut hair pulled back at"
12"She carried a leather satchel"
13"Aurora’s hand stopped halfway to"
14"The woman’s gaze swept past,"
15"Her mouth opened a fraction."
16"Aurora’s spine straightened."
17"The name landed like a"
18"Eva crossed the room in"
19"She laughed once, a brittle"
ratio0.934
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences106
matches(empty)
ratio0
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences38
technicalSentenceCount0
matches(empty)
58.33% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags15
uselessAdditionCount2
matches
0"Eva’s eyes moved, her hair, the delivery jacket"
1"Eva spoke quickly, as if ridding herself of something heavy"
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags8
fancyCount2
fancyTags
0"Eva spoke quickly (speak)"
1"Aurora spoke (speak)"
dialogueSentences70
tagDensity0.114
leniency0.229
rawRatio0.25
effectiveRatio0.057
81.5593%