Run: 2026-09-03-01M1KCTRBEGMSHMQEY7H360RXA

Run Details

Duration:
3m 60s
Cost:
$0.044314
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 rain had come in hard off Soho, streaking the windows of The Raven’s Nest and turning the green neon sign into something blurred and underwater. Aurora sat at the end of the bar in her damp delivery jacket. A carton of cold noodles from Golden Empress had gone slick with oil beside her. Silas stood behind the taps, drawing a pint with a slow, practiced pull, the silver signet ring on his right hand catching the light each time he moved. The door opened. A woman stepped inside, shaking the rain from a folded umbrella. She paused just inside the threshold, her silhouette cut against the green glow. Her hair was dark and blunt at the jaw. Her coat looked expensive. Aurora’s hand stilled over her chopsticks. The woman’s eyes found her. “Rory.” The word carried an accent Aurora knew from home. Silas glanced between them. “Friend?” Aurora nodded. “Old friend.” He placed two glasses of water on the bar. “I’ll leave you to it.” His left leg dragged slightly as he crossed to the bookshelf and disappeared into the hidden room. Eva walked over. She sat on the stool beside Aurora, smoothing her coat as she did so. No ring in her nose. No chipped polish on her nails. The girl who once painted her hands with sunflowers had been replaced by someone who looked like she filed her own tax returns for fun. “You look like a solicitor,” Aurora said. “I am.” The answer landed flat. Aurora let it sit. “You used to say law was a machine for chewing people up.” Eva lifted the water glass. “Maybe I got tired of watching it chew from the outside.” Aurora turned toward the window. The rain moved in sheets down the glass. “That’s not the same as liking it.” “Who said anything about liking it?” Eva took a sip and set the glass down. “I used to think you’d be the one standing in front of a judge. Now you’re delivering noodles in the rain.” Aurora met her eyes. “I’m still standing.” “Are you?” The question stretched. Aurora did not answer. Eva said, “I found you by accident. A Google review of the Golden Empress. ‘Dark-haired courier with the quick smile.’ I read it four times before I believed it.” “You looked for me?” “For two years.” Eva’s voice didn’t rise. “Your old number. Social media. I called your mother once. She didn’t know where you’d gone.” Aurora’s jaw tightened. “I didn’t want to be found.” “That much was clear.” Eva’s fingers curled around the glass. “I thought maybe he’d found you first. I thought maybe you’d gone back to him. I thought maybe you were dead.” Aurora reached below the bar and lifted a bottle of whisky. Her hands knew where it lived. She poured a measure into a glass. The action looked like something from a life she had built without Eva in it. “I didn’t go back to him,” Aurora said. “To him or to Cardiff?” “Both.” The word fell between them. The neon hummed. A car passed outside, its tyres slicing through standing water. Aurora drank. “Do you still paint?” Eva laughed once, without warmth. “Do you still argue with professors?” “I don’t have professors.” “Then no. I don’t paint.” Eva looked at her hands. “I packed the brushes into a box two years ago and gave them to a school in Newport.” Aurora stared. “You were better than anyone I knew.” “I couldn’t stop seeing your face in every canvas.” Eva’s voice was flat. “So I stopped looking.” Silence built between them like a wall. Aurora slid the whisky glass away, then pulled it back. “I should’ve phoned.” “Yes.” Eva did not look away. “You should have.” “I owe you an explanation.” “You don’t owe me anything. I helped you because I loved you. That’s not a debt.” “Then why did you walk through that door?” Eva was quiet for a long moment. The rain had softened against the windows. The maps on the walls watched them with their faded cartographic eyes. “To see if the girl I put on that train still existed.” Aurora turned on her stool. The bright blue of her eyes had dulled with weather and tiredness. “She does. She’s not the same.” “Neither am I.” The two women sat in the green light. Outside, Soho moved on without them. “Does your mother know you’re alive?” Eva asked. Aurora flinched. “Don’t.” “She asked me about you last month. In Tesco. Her hair’s gone grey.” Aurora closed her eyes. The green glow pressed against her lids. “I know.” “Then why let her wonder?” “Because every time I think about Cardiff, I feel the walls of that flat closing around me again.” Aurora’s voice cracked at the edges. “I can’t go back. Not even for her.” Eva studied her. “I stayed in Cardiff. I stayed in that flat for six months after you left. I paid your share of the deposit until the lease ran out.” Aurora opened her eyes. “Why would you do that?” “In case you came back.” The words sat between them like a held breath. “I never planned to,” Aurora said. “I know that now.” Eva pulled her coat around her, not leaving, but drawing herself in. “Do you ever think about that night?” Aurora looked at her. “The platform.” “All of it. The train. The rain. The money in your pocket.” “Every day.” Eva nodded slowly. For a moment, her composure cracked and the old girl surfaced—the one who had pressed damp banknotes into Aurora’s hands and told her to run. Then the crack closed. “Good,” Eva said.
created_at"2026-09-03T10:25:31.005Z" 9/3/2026, 10:25:31 AM
model"deepseek/deepseek-v4-pro-20260813"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency844
moderation_latency(null)
generation_time239702
tokens_prompt1063
tokens_completion11008
native_tokens_prompt1071
native_tokens_completion10113
native_tokens_completion_images(null)
native_tokens_reasoning8818
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)
usage0.04431443
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.19.0; linux; x64))"
http_referer(null)
request_id"req-1788431131-TpRix0uUSjobIasJfOUT"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1788431131-Rac2PwXSFtQkQpIhB1jH"
upstream_id"req_c766fc112be6babb07d4866b373d79fc"
provider_responses
0
endpoint_id"bb1fb528-2000-460c-a65e-b82dc347c019"
id"req_c766fc112be6babb07d4866b373d79fc"
is_byokfalse
latency379
model_permaslug"deepseek/deepseek-v4-pro-20260813"
provider_name"Phala"
status200
total_cost0.04431443
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
totalTags14
adverbTagCount1
adverbTags
0"Eva’s fingers curled around [around]"
dialogueSentences57
tagDensity0.246
leniency0.491
rawRatio0.071
effectiveRatio0.035
89.40% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount943
totalAiIsmAdverbs2
found
0
adverb"slightly"
count1
1
adverb"slowly"
count1
highlights
0"slightly"
1"slowly"
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)
89.40% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount943
totalAiIsms2
found
0
word"warmth"
count1
1
word"silence"
count1
highlights
0"warmth"
1"silence"
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
narrationSentences73
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount0
hedgeCount0
narrationSentences73
filterMatches(empty)
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences115
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen29
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords942
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions11
unquotedAttributions0
matches(empty)
0.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions48
wordCount535
uniqueNames8
maxNameDensity4.49
worstName"Aurora"
maxWindowNameDensity6
worstWindowName"Aurora"
discoveredNames
Soho2
Raven1
Nest1
Golden1
Empress1
Aurora24
Eva17
Silence1
persons
0"Raven"
1"Empress"
2"Aurora"
3"Eva"
4"Silence"
places
0"Soho"
1"Golden"
globalScore0
windowScore0
7.14% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences35
glossingSentenceCount2
matches
0"looked like she filed her own tax returns"
1"looked like something from a life she had"
93.84% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches1
per1kWords1.062
wordCount942
matches
0"not leaving, but drawing herself in"
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences115
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs63
mean14.95
std14.2
cv0.95
sampleLengths
082
13
237
36
46
59
65
74
831
953
107
112
1220
1316
1420
1536
167
172
187
1929
204
2123
229
2331
2439
258
265
271
2818
296
3011
314
3228
339
3417
357
3613
379
385
3916
408
4126
4212
4323
443
4514
468
473
4813
4913
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount1
totalSentences73
matches
0"been replaced"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs111
matches(empty)
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount1
semicolonCount0
flaggedSentences1
totalSentences115
ratio0.009
matches
0"For a moment, her composure cracked and the old girl surfaced—the one who had pressed damp banknotes into Aurora’s hands and told her to run."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount536
adjectiveStacks0
stackExamples(empty)
adverbCount14
adverbRatio0.026119402985074626
lyAdverbCount2
lyAdverbRatio0.0037313432835820895
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences115
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences115
mean8.19
std6.48
cv0.791
sampleLengths
026
113
215
328
43
511
613
79
84
96
105
111
129
134
141
152
162
179
1822
193
2014
215
226
2325
247
252
264
274
2812
295
3011
315
328
337
3415
3521
364
373
382
393
404
4129
424
437
4416
453
466
4710
4821
4911
49.28% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats5
diversityRatio0.3217391304347826
totalSentences115
uniqueOpeners37
52.91% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount1
totalSentences63
matches
0"Then the crack closed."
ratio0.016
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount8
totalSentences63
matches
0"She paused just inside the"
1"Her hair was dark and"
2"Her coat looked expensive."
3"He placed two glasses of"
4"His left leg dragged slightly"
5"She sat on the stool"
6"Her hands knew where it"
7"She poured a measure into"
ratio0.127
0.00% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount58
totalSentences63
matches
0"The rain had come in"
1"Aurora sat at the end"
2"A carton of cold noodles"
3"Silas stood behind the taps,"
4"The door opened."
5"A woman stepped inside, shaking"
6"She paused just inside the"
7"Her hair was dark and"
8"Her coat looked expensive."
9"Aurora’s hand stilled over her"
10"The woman’s eyes found her."
11"The word carried an accent"
12"Silas glanced between them."
13"He placed two glasses of"
14"His left leg dragged slightly"
15"Eva walked over."
16"She sat on the stool"
17"The girl who once painted"
18"The answer landed flat."
19"Aurora let it sit."
ratio0.921
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences63
matches(empty)
ratio0
95.24% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences15
technicalSentenceCount1
matches
0"A car passed outside, its tyres slicing through standing water."
89.29% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags14
uselessAdditionCount1
matches
0"Eva pulled, not leaving, but drawing herself in"
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags6
fancyCount0
fancyTags(empty)
dialogueSentences57
tagDensity0.105
leniency0.211
rawRatio0
effectiveRatio0
82.2162%