Run: 2026-07-25-01KYD7WJ9XR72QFPMDDYN2P6BB

Run Details

Duration:
1m 14s
Cost:
$0.027628
Provider:
Moonshot AI

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 buzzed against the wet pavement as Aurora pushed through the door of the Raven's Nest, shoulders damp from the October drizzle. She had finished her last delivery an hour ago, but the flat upstairs felt too quiet, and quiet had a way of turning into Evan's voice if she let it. So she came down to the bar, where Silas kept the noise at a low, human hum. She was halfway to her usual stool when a woman at the corner table stood up. "Rory? Rory Carter?" The voice hit some deep drawer in her memory and yanked it open. Aurora turned. The woman was tall, willowy, copper hair cut into a sharp bob that must have cost eighty quid, wearing a camel coat over a silk blouse. It took a full three seconds for the face to resolve into something recognisable. "Megan? Megan Price?" "Oh my God." Megan crossed the floor in four strides and gripped Aurora's forearms, scanning her face the way people examine banknotes. "It is you. What are you—I mean, London, obviously, but—God, how long has it been?" "Seven years?" Aurora's mouth had gone dry. "Since graduation. You went to that consultancy thing in Manchester." "Deloitte. Then Singapore, then back here." Megan's perfume smelled like money and airports. "Sit with me. Please. I'm waiting for my husband, he's always late, sit." Silas caught Aurora's eye from behind the bar and raised one brow, the question plain: everything all right? She gave him a small nod and let herself be pulled into the corner booth. Megan ordered two glasses of the Rioja without asking. "You still drink red, right? You used to nick your dad's Rioja and we'd drink it in the park behind the cathedral." "That was white, actually. From a bag." "It was not—" Megan laughed, and for a moment she was nineteen again, sprawled on the grass with her shoes off. Then the laugh settled and the forty-something polish came back down over her like a shutter. "Look at you. You look… different." "Older." "No. Not older. Harder?" Megan tilted her head. "That sounds awful. I mean—you used to be the soft one. You cried at that documentary about the bees." "I still cry at the bee documentary." "Do you?" The wine arrived. Silas set the glasses down himself, unhurried, his limp barely noticeable tonight. "Anything else, ladies?" "We're fine, thank you," Megan said, already turning back to Aurora, dismissing him the way she'd dismiss furniture. Aurora watched Silas walk away and felt something small and hot rise in her chest. "He's my landlord," she said. "And my friend." "Oh. God, sorry, I didn't—" Megan waved it off. "So. Landlord. You live around here? What are you doing? Please tell me you finally ditched the law thing and went into journalism like you wanted." Aurora turned her glass by the stem. The crescent scar on her wrist caught the candlelight. "I deliver food. For a restaurant in Chinatown." Silence. Megan's face performed several manoeuvres. "Part-time? While you—" "Just the deliveries." "Right." Megan took a long drink. "Right. Well. London's expensive, everyone does what they—" She stopped, visibly rearranging her own sentence. "Sorry. I'm being a cow. It's just—you were top of our year. You were going to be QC by thirty. We all said it. Your dad said it." "My dad says a lot of things." There it was. The first stone dropped into the well, and they both heard the depth of it. Megan set her glass down carefully. "Is he all right? Brendan?" "He's fine. He's Brendan." Aurora watched the candle flame lean and straighten. "We don't talk much. Since I left Cardiff." "Because of the law thing?" "Because of a lot of things." The words came out flat, rehearsed by years of not being said. "There was a man. After uni. Evan." Megan went very still. "The tall one. You brought him to Sian's birthday that time. He didn't let you finish a sentence all night and I thought—" She stopped. "You thought what?" "Nothing. I thought nothing, that's the problem." Megan's manicured fingers found the base of her glass and worried at it. "I said something to Rhiannon afterwards. That he seemed off. And then I got on a plane to Manchester and I never said it to you." "You weren't the only one who saw it." "But I was the only one who—" Megan's voice cracked, just slightly, and the consultancy polish cracked with it. "Rory, I heard things. Years later. Through Rhiannon's cousin. About what he did. And I sat in my office in Singapore with my seventy-hour weeks and my view of the harbour, and I thought, I should call her. I should have called her seven years ago. And I didn't even have your number anymore. I'd let it lapse. Like a magazine subscription." Aurora looked at her. Really looked. The sharp bob, the good coat, the wedding band with a diamond the size of a pea. And underneath it all, the girl who'd once driven forty minutes at two in the morning because Aurora had a panic attack before her contract law exam, who'd sat on the floor of the student union toilets holding her hair back, who'd promised—we'll be old ladies together, we'll have adjacent bungalows and fight about the hedge. "I ran," Aurora said. "I didn't tell anyone where I was going except Eva. You couldn't have called." "I could have tried." "And said what?" "Anything. 'I saw it too. You're not mad. Get out.' Anything." Megan's eyes had gone bright, and she looked away, out at the rain-streaked window, at the green neon bleeding across the glass. "You know what I do now? I restructure companies. I fly in, I tell four hundred people their jobs are redundant, I fly out. And I'm brilliant at it. Everyone says so. And some nights I lie in bed and think about the year I didn't phone my best friend, and I can't remember a single one of those companies' names." The bar noise moved around them—glasses, low laughter, Silas saying something dry to a regular. Aurora reached across the table and, after a moment's hesitation, put her hand over Megan's. The diamond was cold. "I got out," she said. "Eva got me out. I live above a bar with maps on the walls and a landlord who taught me how to throw a punch and spot a tail, which is a long story. I deliver dumplings and I'm—" She searched for the honest word. "I'm rebuilding. Some days it feels like a life. Some days it feels like the wreckage of one. But it's mine." "Delivering dumplings." Megan laughed wetly, and squeezed her hand. "The pride of Cardiff University." "The pride of Cardiff University." They sat like that while the rain worked at the windows. Then Megan straightened, wiped under her eyes with the heel of her hand, and pulled out her phone. "Give me your number. Not so I can feel better about myself—well, partly that—but because I'm not doing it again. Losing it. Whatever time does to people, whatever it did to you, whatever it did to me." She looked up, and there was the nineteen-year-old again, fierce and tearful on the union toilets floor. "Adjacent bungalows. I haven't forgotten." "You'll fight me about the hedge." "I will absolutely fight you about the hedge." Aurora recited her number, and Megan typed it in with shaking thumbs, and the candle burned down a quarter inch, and neither of them said the thing that lay beneath everything else—that the years were gone, and no phone call, however overdue, would bring them back, and that this was precisely why the next ones had to be made.
created_at"2026-07-25T18:16:35.396Z" 7/25/2026, 6:16:35 PM
model"moonshotai/kimi-k3-20260715"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency2833
moderation_latency(null)
generation_time73737
tokens_prompt1063
tokens_completion1961
native_tokens_prompt1081
native_tokens_completion1810
native_tokens_completion_images(null)
native_tokens_reasoning78
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)
usage0.0276282
router(null)
provider_responses
0
endpoint_id"650c9b12-7b6d-444d-8d92-df8daef84d7a"
id"chatcmpl-6a64fd84406b1b489a309edb"
is_byokfalse
latency2833
model_permaslug"moonshotai/kimi-k3-20260715"
provider_name"Moonshot AI"
status200
user_agent"langchainjs-openai/1.0.0 ((node/v24.18.0; linux; x64))"
http_referer(null)
request_id"req-1785003395-Gz8L7pTiI3pNnGv7vE1F"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1785003395-WewFMjwnDWAq4theH0Ab"
upstream_id"chatcmpl-6a64fd84406b1b489a309edb"
total_cost0.0276282
cache_discount0.0027648
upstream_inference_cost0
provider_name"Moonshot AI"
response_cache_source_id(null)
data_region"global"

Evaluation details

Result Evaluator Details Meta Data
64.41% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags21
adverbTagCount4
adverbTags
0"Megan's perfume smelled like [like]"
1"She stopped visibly [visibly]"
2"Megan's voice cracked just [just]"
3"Megan laughed wetly [wetly]"
dialogueSentences59
tagDensity0.356
leniency0.712
rawRatio0.19
effectiveRatio0.136
80.81% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1303
totalAiIsmAdverbs5
found
0
adverb"carefully"
count1
1
adverb"very"
count1
2
adverb"slightly"
count1
3
adverb"really"
count1
4
adverb"precisely"
count1
highlights
0"carefully"
1"very"
2"slightly"
3"really"
4"precisely"
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)
80.81% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1303
totalAiIsms5
found
0
word"silk"
count1
1
word"resolve"
count1
2
word"scanning"
count1
3
word"silence"
count1
4
word"absolutely"
count1
highlights
0"silk"
1"resolve"
2"scanning"
3"silence"
4"absolutely"
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
narrationSentences54
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount0
hedgeCount0
narrationSentences54
filterMatches(empty)
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences92
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen63
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1294
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions16
unquotedAttributions1
matches
0"The bar noise moved around them—glasses, low laughter, Silas saying something dry to a regular."
0.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions42
wordCount669
uniqueNames8
maxNameDensity2.69
worstName"Megan"
maxWindowNameDensity5.5
worstWindowName"Megan"
discoveredNames
Aurora14
Raven1
Nest1
October1
Evan1
Silas5
Megan18
Rioja1
persons
0"Aurora"
1"Raven"
2"Evan"
3"Silas"
4"Megan"
places
0"October"
globalScore0.155
windowScore0
14.86% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences37
glossingSentenceCount2
matches
0"smelled like money and airports"
1"She stopped, visibly rearranging her own"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1294
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences92
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs50
mean25.88
std23.95
cv0.926
sampleLengths
071
116
23
355
43
537
617
726
833
931
107
1143
121
1327
147
152
1618
1733
188
1935
2024
216
223
233
2449
257
2624
275
2820
295
3025
3129
323
3346
348
3581
3679
3718
384
393
4094
4134
4271
4314
445
4529
4659
476
488
4959
92.27% Passive voice overuse
Target: ≤2% passive sentences
passiveCount2
totalSentences54
matches
0"being said"
1"were gone"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs120
matches(empty)
49.69% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount3
semicolonCount0
flaggedSentences3
totalSentences92
ratio0.033
matches
0"And underneath it all, the girl who'd once driven forty minutes at two in the morning because Aurora had a panic attack before her contract law exam, who'd sat on the floor of the student union toilets holding her hair back, who'd promised—we'll be old ladies together, we'll have adjacent bungalows and fight about the hedge."
1"The bar noise moved around them—glasses, low laughter, Silas saying something dry to a regular."
2"Aurora recited her number, and Megan typed it in with shaking thumbs, and the candle burned down a quarter inch, and neither of them said the thing that lay beneath everything else—that the years were gone, and no phone call, however overdue, would bring them back, and that this was precisely why the next ones had to be made."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount676
adjectiveStacks0
stackExamples(empty)
adverbCount22
adverbRatio0.03254437869822485
lyAdverbCount7
lyAdverbRatio0.010355029585798817
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences92
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences92
mean14.07
std13.49
cv0.959
sampleLengths
024
130
217
316
43
513
62
726
814
93
1022
1115
127
1310
1413
1513
1618
1715
189
1922
207
2121
2216
236
241
258
2619
277
282
293
3012
313
3218
3315
345
353
369
3726
387
399
408
411
425
433
443
456
4615
4728
487
493
70.65% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats5
diversityRatio0.45652173913043476
totalSentences92
uniqueOpeners42
100.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount2
totalSentences47
matches
0"Then the laugh settled and"
1"Then Megan straightened, wiped under"
ratio0.043
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount8
totalSentences47
matches
0"She had finished her last"
1"She was halfway to her"
2"It took a full three"
3"She gave him a small"
4"She stopped, visibly rearranging her"
5"She searched for the honest"
6"They sat like that while"
7"She looked up, and there"
ratio0.17
13.19% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount42
totalSentences47
matches
0"The green neon buzzed against"
1"She had finished her last"
2"She was halfway to her"
3"The voice hit some deep"
4"The woman was tall, willowy,"
5"It took a full three"
6"Megan crossed the floor in"
7"Aurora's mouth had gone dry"
8"Megan's perfume smelled like money"
9"Silas caught Aurora's eye from"
10"She gave him a small"
11"Megan ordered two glasses of"
12"Megan laughed, and for a"
13"Megan tilted her head"
14"The wine arrived."
15"Silas set the glasses down"
16"Megan said, already turning back"
17"Aurora watched Silas walk away"
18"Megan waved it off"
19"Aurora turned her glass by"
ratio0.894
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences47
matches(empty)
ratio0
71.43% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences20
technicalSentenceCount2
matches
0"The woman was tall, willowy, copper hair cut into a sharp bob that must have cost eighty quid, wearing a camel coat over a silk blouse."
1"And underneath it all, the girl who'd once driven forty minutes at two in the morning because Aurora had a panic attack before her contract law exam, who'd sat …"
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags21
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags6
fancyCount2
fancyTags
0"Megan laughed (laugh)"
1"Megan laughed wetly (laugh)"
dialogueSentences59
tagDensity0.102
leniency0.203
rawRatio0.333
effectiveRatio0.068
81.2709%