Run: 2026-09-03-01M1KRHP43HGVCZQR3815YF8X3

Run Details

Duration:
1m
Cost:
$0.004054
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 sign buzzed above the door on Frith Street and threw a thin wash of light across the wet pavement. Aurora pushed the door of The Raven's Nest with her shoulder, the insulated bag thumping against her hip. The bell gave a short, flat chime. The bar smelled of old wood and spilled beer. Maps hung crooked on the walls. Black-and-white photographs watched from the corners. Silas stood behind the bar, polishing a glass with a cloth that had seen better years. His grey-streaked auburn hair caught the low light. The silver signet ring on his right hand caught it and threw it back. "Yu-Fei sent two orders," Aurora said. She set the bag down on the bar. "One for the kitchen, one for table four." Silas glanced up. His eyes moved from her face to the crescent-shaped scar on her left wrist where the strap of the bag dug in. "You’re late," he said. "I got stuck on Wardour." She lifted the lid. Steam rose. "Traffic was a mess." He nodded once. The limp in his left leg was quieter when he leaned on the bar. He took the bag without touching her. A voice came from the far stool. "Rory?" Aurora turned. Eva sat at the bar with her back to the room. She had turned, and the movement brought her profile into the light. Her hair was cut short now, dyed a dark, almost black brown. The softness she had worn in Cardiff was gone. A thin line ran through her left eyebrow. She wore a leather jacket over a black tee, and her hands rested on the bar like they were deciding whether to stay. Aurora’s grip tightened on the empty bag. "Eva." Eva smiled, and the smile did not reach her eyes. "You still bring food like you’re running an errand for the world," Eva said. "I thought you’d be a barrister by now." "I’m a delivery person," Aurora said. "It pays rent." "You’re living above the bar," Eva said. "I saw the flat." "Silas lets me stay cheap." "Silas." Eva looked past Aurora to the bar. "He looks the same." "He limps more." Eva laughed, a short sound. She slid off the stool. The two of them stood in the narrow space between tables. The bar was quiet. A couple in the corner talked low. "I didn’t know you were in London," Aurora said. "I moved last year," Eva said. "I work at the clinic on Dean Street. Nights." Aurora studied her. The girl who had taught her how to skip stones on the Taff, who had shown up at her flat the night she left Evan, who had taken her hand and said come with me. That girl had been soft around the edges. This woman held herself like someone who expected a blow. "You look different," Aurora said. "You look tired," Eva said. "Is it the job?" "It’s the hours." "You used to hate nights." "I hate a lot of things now." Silas set a glass down between them. It made a clean sound on wood. "Water," he said to Eva. "You’re on shift." Eva didn’t thank him. She picked up the glass and drank. Aurora watched the way Eva’s fingers curled around it. The knuckles were white. "You didn’t answer me about Cardiff," Eva said. "You just left." "I told you why." "You told me he hit you." Eva’s voice stayed even. "You didn’t tell me you were scared." "I wasn’t scared." "You were shaking when you packed." Aurora felt the memory press against her ribs. The flat in Cardiff, the suitcase half full, the phone buzzing with Evan’s name. Eva had driven her to the train station at three in the morning. "I was angry," Aurora said. "You were quiet." "I was quiet because I was done." Eva set the glass down harder than she needed to. A little water spilled. "I kept waiting for you to call," Eva said. "You didn’t." "I didn’t know what to say." "You could have said you were sorry I dragged you into it." "You didn’t drag me into anything." "I did." Eva looked at the floor. "I took you away. I put you in a flat above a spy’s bar. I left you to figure out London on your own." Aurora stepped closer. The scar on her wrist itched. "You gave me a way out," she said. "I was grateful." "You never said it." "I didn’t have the words." Eva’s jaw worked. She was older than Aurora remembered, not in years but in the way she carried them. "I married," Eva said. "It didn’t last." Aurora waited. "He was good at first," Eva said. "Then he wasn’t. I left him in a flat that looked like mine. I left everything." The air between them thickened. Aurora thought of the night she had stood in the doorway of Silas’s building, bag over her shoulder, no plan. Eva had opened the door before she knocked. "You could have stayed in Cardiff," Aurora said. "And do what? Watch you become a barrister you hated?" "I would have been miserable." "We were both miserable," Eva said. "We just called it different things." Silas moved behind the bar, restocking glasses. He did not look at them. The maps on the wall seemed to shift in the low light. "You still think I’m cool-headed," Aurora said. "I think you’re good at not feeling things," Eva said. "That’s not the same." Aurora’s mouth opened. She closed it. The bag strap cut into her wrist. "I feel things," she said. "Do you?" Eva asked. "You left without a word. You never wrote. You never came to visit." "I wrote you a letter," Aurora said. "You never replied." "I got it," Eva said. "It was two lines. Thank you for getting me out. I’m safe now." "I didn’t know what else to say." "You could have said my name more than once." The silence that followed held the weight of a decade. The bar hummed. The neon sign flickered outside. Aurora reached into her pocket and pulled out a folded receipt from Yu-Fei’s. She smoothed it on the bar. "I still owe you for the train ticket," she said. Eva laughed, real this time. The sound cracked. "You still keep receipts." "I keep things." Eva picked up the receipt, looked at it, and tore it in half. She let the pieces fall to the floor. "I don’t want it," she said. "I know." Eva pushed off the stool again, but slower this time. She stood close enough that Aurora could smell citrus and antiseptic. "Are you happy?" Eva asked. Aurora thought of the flat above the bar, the delivery bag, the scar on her wrist, the way Silas always left a lamp on for her. "I’m not unhappy," she said. Eva nodded. She didn’t ask for more. "I have to go," Eva said. "Shift starts." Aurora watched her pick up her coat from the back of the stool. She watched her check the door. Eva paused at the threshold. She looked back once. "Rory," she said. Aurora met her eyes. "Don’t disappear again," Eva said. Aurora didn’t answer. Eva walked out into the wet street. The bell chimed. Silas stepped forward and swept the torn receipt pieces into his palm. "You’re leaving the food," he said. Aurora picked up the bag. Her wrist ached where the strap had pressed. "Table four can wait," she said. She left the bag on the bar and pushed through the door before he could ask her to stay.
created_at"2026-09-03T13:50:16.713Z" 9/3/2026, 1:50:16 PM
model"meta/muse-glimmer-30b-20260810"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency273
moderation_latency(null)
generation_time59962
tokens_prompt1063
tokens_completion4076
native_tokens_prompt1008
native_tokens_completion3649
native_tokens_completion_images(null)
native_tokens_reasoning1978
native_tokens_cached1007
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)
usage0.00405448
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.19.0; linux; x64))"
http_referer(null)
request_id"req-1788443416-msugegHbkRtMla5mxZLP"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1788443416-ImplrLmuiL6cHmXGd5C8"
upstream_id"req_2646800359b850a526e97b6a3fd42118"
provider_responses
0
endpoint_id"6244f10e-1e45-488b-a47f-f575e0edd12b"
id"req_2646800359b850a526e97b6a3fd42118"
is_byokfalse
latency229
model_permaslug"meta/muse-glimmer-30b-20260810"
provider_name"Phala"
status200
total_cost0.00405448
cache_discount0.00026182
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
totalTags37
adverbTagCount0
adverbTags(empty)
dialogueSentences83
tagDensity0.446
leniency0.892
rawRatio0
effectiveRatio0
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1264
totalAiIsmAdverbs0
found(empty)
highlights(empty)
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)
84.18% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1264
totalAiIsms4
found
0
word"eyebrow"
count1
1
word"silence"
count1
2
word"weight"
count1
3
word"flickered"
count1
highlights
0"eyebrow"
1"silence"
2"weight"
3"flickered"
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
narrationSentences123
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount0
hedgeCount1
narrationSentences123
filterMatches(empty)
hedgeMatches
0"seemed to"
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
maxSentenceWordsSeen35
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1264
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions43
unquotedAttributions0
matches(empty)
0.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions79
wordCount839
uniqueNames12
maxNameDensity4.05
worstName"Eva"
maxWindowNameDensity7.5
worstWindowName"Eva"
discoveredNames
Frith1
Street1
Raven1
Nest1
Steam1
Cardiff2
Aurora27
Eva34
Taff1
Evan2
Silas7
Yu-Fei1
persons
0"Raven"
1"Aurora"
2"Eva"
3"Evan"
4"Silas"
places
0"Frith"
1"Street"
2"Cardiff"
3"Yu-Fei"
globalScore0
windowScore0
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences58
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches1
per1kWords0.791
wordCount1264
matches
0"not in years but in the way she carried them"
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
totalParagraphs97
mean13.03
std12.38
cv0.95
sampleLengths
047
159
222
325
44
515
624
77
81
92
1075
117
121
1310
1422
159
1611
175
1812
193
2032
219
2215
2356
245
259
263
275
287
2914
308
3111
3213
3311
344
3517
363
376
3835
395
403
417
4214
4311
446
4512
466
4731
489
4911
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount1
totalSentences123
matches
0"was gone"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount1
totalVerbs175
matches
0"were deciding"
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences169
ratio0
matches(empty)
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount844
adjectiveStacks0
stackExamples(empty)
adverbCount10
adverbRatio0.011848341232227487
lyAdverbCount0
lyAdverbRatio0
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
mean7.48
std5.08
cv0.679
sampleLengths
022
118
27
39
46
56
616
78
814
96
108
118
123
1322
144
159
162
174
183
1914
207
217
221
232
2411
2512
2612
279
288
2923
307
311
3210
3314
348
356
363
377
384
395
408
414
423
435
445
4511
464
477
489
496
39.94% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats17
diversityRatio0.1834319526627219
totalSentences169
uniqueOpeners31
0.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount0
totalSentences87
matches(empty)
ratio0
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount24
totalSentences87
matches
0"His grey-streaked auburn hair caught"
1"She set the bag down"
2"His eyes moved from her"
3"She lifted the lid"
4"He nodded once."
5"He took the bag without"
6"She had turned, and the"
7"Her hair was cut short"
8"She wore a leather jacket"
9"She slid off the stool."
10"It made a clean sound"
11"he said to Eva"
12"She picked up the glass"
13"She was older than Aurora"
14"He did not look at"
15"She closed it."
16"She smoothed it on the"
17"She let the pieces fall"
18"She stood close enough that"
19"She didn’t ask for more."
ratio0.276
0.00% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount86
totalSentences87
matches
0"The green neon sign buzzed"
1"Aurora pushed the door of"
2"The bell gave a short,"
3"The bar smelled of old"
4"Maps hung crooked on the"
5"Silas stood behind the bar,"
6"His grey-streaked auburn hair caught"
7"The silver signet ring on"
8"She set the bag down"
9"Silas glanced up."
10"His eyes moved from her"
11"She lifted the lid"
12"He nodded once."
13"The limp in his left"
14"He took the bag without"
15"A voice came from the"
16"Eva sat at the bar"
17"She had turned, and the"
18"Her hair was cut short"
19"The softness she had worn"
ratio0.989
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences87
matches(empty)
ratio0
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences29
technicalSentenceCount1
matches
0"Silas stood behind the bar, polishing a glass with a cloth that had seen better years."
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags37
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags33
fancyCount0
fancyTags(empty)
dialogueSentences83
tagDensity0.398
leniency0.795
rawRatio0
effectiveRatio0
84.1373%