Run: 2026-04-25-01KQ2FN1EZ99154HWB800G3WNJ

Run Details

Duration:
45.3s
Cost:
$0.001654
Provider:
DeepSeek

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 bled through the Soho drizzle, pooling on the wet pavement like spilled chartreuse. Inside, the place clung to its perpetual twilight. Old maps hung in faded dignity on the walls, their edges curled. Black-and-white photographs of people long dead watched the living with silvered eyes. Aurora Carter shook rain from her shoulder-length black hair and slid onto her usual stool at the end of the bar. She pulled the day’s delivery receipts from her jacket pocket, smoothed them flat. The Golden Empress logo on her sleeve had faded to a ghost of its former gold. Silas emerged from the back, his slight limp a rhythmic hitch on the floorboards. He dried a glass with a towel that had seen better decades. “Yu-Fei work you hard?” “The usual. Kung pao to Kensington. Chow mein to Chelsea.” She pushed the receipts toward him. “Your order’s on the house Tuesday, by the way. She found out you sent that procurement specialist her way.” Silas’s hazel eyes crinkled. The silver signet ring on his right hand caught the low light as he took the papers. “Tell her thanks are unnecessary.” “Tell her yourself. You know she loves fussing over you.” He gave a near-imperceptible nod and moved to serve another patron. The door swung open. Cold air cut through the warmth. A man stood in the entrance, silhouetted against the streetlamp glow. Tall. Broad-shouldered in a way that spoke of discipline rather than genetics. He moved to the bar with an economy of motion that made Aurora’s spine stiffen before her conscious mind understood why. Three stools down. He ordered Scotch. Neat. The voice landed in her chest like a stone dropped into still water. She knew that voice. She’d heard it crack jokes during university lectures. Heard it soft with concern when she’d shown up to his flat with a bruise she’d lied about. Heard it hard with fury when the truth finally spilled out. “Marcus.” Her own voice surprised her. It came out level. Composed. Nothing like the girl who’d fled Cardiff with a single suitcase and an emergency credit card Eva had mailed her in secret. The man turned. Marcus Holt had always been handsome in an unstudied way. The kind of face that suggested fresh air and early mornings. But the man who looked at her now wore a different skin. The jaw was sharper, the cheekbones more pronounced. His dark hair had retreated slightly at the temples. His eyes—still that deep amber-brown—carried a heaviness that hadn’t been there before. A weight that sat behind them like sediment. “Rory.” He said it like a question he already knew the answer to. Like a word in a language he hadn’t spoken in years and was surprised to find still on his tongue. Silas glanced between them. His face betrayed nothing. He drifted to the other end of the bar with the instinct of a man who’d spent decades reading rooms. Marcus picked up his Scotch and moved to the stool beside her. The three spaces between them collapsed. “You cut your hair,” he said. “You grew a beard.” He touched his jaw. The stubble was neat. Intentional. “Hides the jawline. Or so I’m told.” “Who told you that needed hiding?” “People whose opinions mattered at the time.” The sentence landed between them. Neither claimed it. Aurora studied his hands. Clean nails. No ring. A faint scar across the knuckles of his right hand that she didn’t remember. “You’re not in Cardiff anymore.” “Neither are you.” “That’s not an answer.” He took a slow sip. The ice shifted in the glass. “London. Three years now. Maybe four.” The pause that followed was deliberate. “I looked for you.” She felt her pulse in her throat. “When?” “When I got out.” The word *out* carried its own gravity. She didn’t know what he’d gotten out of. The military, maybe. The relationship he’d been in when she left. The version of himself that had existed before everything went wrong. “I didn’t leave a forwarding address,” she said. “I noticed.” Silas returned. He set a glass of white wine in front of Aurora without being asked. She hadn’t ordered it. She wrapped her fingers around the stem. The cold glass grounded her. “Old friend?” Silas asked. “Something like that.” She didn’t look away from Marcus. “Silas, this is Marcus. We studied together at Cardiff.” “Pre-Law,” Marcus said. “She was top of the class until she stopped showing up.” The accusation was soft. Almost gentle. But it was there. Aurora’s grip tightened on the wine glass. “I had reasons.” “Evan.” The name hit the bar top like a dropped blade. Aurora hadn’t spoken that name aloud in three years. She’d scrubbed it from her phone, her social media, the corners of her mind where bad memories nested. But Marcus said it like it was still present tense. Like the ghost of the man still occupied the space between them. “He’s why I looked for you,” Marcus continued. “After you left, he started running his mouth. Said things.” His amber eyes met hers. “I knew maybe half of it was lies. But the half that wasn’t…” “You didn’t know.” “I didn’t know.” The silence stretched. Somewhere behind them, the door opened and closed. A laugh rose and fell. The bar’s ambient noise wrapped around their pocket of stillness like water around a stone. “I should have told you,” she said. “At the time, I couldn’t.” “Couldn’t or wouldn’t?” “Does the distinction matter now?” Marcus ran a thumb along the rim of his glass. The motion was slow. Meditative. “I spent a long time being angry at you. Then I spent a long time being angry at myself for not seeing it.” “There was nothing to see. I made sure of that.” “You were good at it.” Not a compliment. Not an insult. A fact. “The concealer. The long sleeves. The excuses about being clumsy.” He listed them like items on an inventory. “I believed every one.” “Eva believed me,” Aurora said. “Near the end. That’s why she helped me leave.” “Eva always was sharper than me.” Aurora took a breath. The wine sat untouched. Her throat was too tight to drink. “What did you do, Marcus? When you found out?” The question hung between them. He didn’t answer right away. Instead, he reached into his jacket and pulled out his wallet. From it, he extracted a business card. White. Simple. A name and a number. *Marcus Holt, Private Investigator.* “I left the force two years ago. Went private.” He slid the card across the bar. “Specialize in domestic cases. Stalking. Abuse. The ones the system fails.” Aurora stared at the card. The letters blurred then sharpened. “You became a cop.” “For a while. Cardiff PD. Thought I could make a difference from the inside.” A bitter twist pulled at the corner of his mouth. “Reality’s less romantic.” “And now you chase the kind of men I ran from.” “I find them. I build cases. I make sure the next woman doesn’t have to disappear to survive.” The weight of time pressed down. The years they’d spent apart. The paths they’d taken. Both of them running from the same thing in different directions. “You changed,” she said. “We both did.” She looked at him then. Really looked. Past the harder edges and the tired eyes. Past the new scar and the careful way he held himself. She looked for the boy who’d shared his lecture notes with her. Who’d walked her home through the Cardiff rain. Who’d told her she was the smartest person he’d ever met and meant it. He was still there. Buried. Waiting. “I’m not the person you remember,” she said. “Neither am I.” Marcus finished his Scotch. The glass clicked against the wood. “But I’d like to find out who you are now. If you’ll let me.” The neon hummed outside. The maps watched from the walls. And somewhere in the quiet, the distance between two old friends began to shrink.
created_at"2026-04-25T14:10:45.86Z" 4/25/2026, 2:10:45 PM
model"deepseek/deepseek-v4-pro-20260423"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency1240
moderation_latency(null)
generation_time45089
tokens_prompt1094
tokens_completion2159
native_tokens_prompt992
native_tokens_completion1816
native_tokens_completion_images(null)
native_tokens_reasoning0
native_tokens_cached896
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"
usage0.00165416
router(null)
provider_responses
0
endpoint_id"d084170b-dd99-4e53-9ae1-b63881f3cfbf"
id"df9ad02d-ce43-4a2d-8d22-14c4e3f4b841"
is_byokfalse
latency375
model_permaslug"deepseek/deepseek-v4-pro-20260423"
provider_name"DeepSeek"
status200
user_agent"langchainjs-openai/1.0.0 ((node/v24.14.1; linux; x64))"
http_referer(null)
request_id"req-1777126245-MYs92CzVwwzFQHLlkr9b"
session_id(null)
api_type"completions"
id"gen-1777126245-QYZKxOeOdgP0Edejb8gD"
upstream_id"df9ad02d-ce43-4a2d-8d22-14c4e3f4b841"
total_cost0.00165416
cache_discount0.00035728
upstream_inference_cost0
provider_name"DeepSeek"
response_cache_source_id(null)

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags16
adverbTagCount0
adverbTags(empty)
dialogueSentences58
tagDensity0.276
leniency0.552
rawRatio0
effectiveRatio0
92.56% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1344
totalAiIsmAdverbs2
found
0
adverb"slightly"
count1
1
adverb"really"
count1
highlights
0"slightly"
1"really"
80.00% AI-ism character names
Target: 0 AI-default names (16 tracked, −20% each)
codexExemptions
0"Blackwood"
found
0"Marcus"
100.00% AI-ism location names
Target: 0 AI-default location names (33 tracked, −20% each)
codexExemptions(empty)
found(empty)
77.68% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1344
totalAiIsms6
found
0
word"rhythmic"
count1
1
word"warmth"
count1
2
word"weight"
count2
3
word"pulse"
count1
4
word"silence"
count1
highlights
0"rhythmic"
1"warmth"
2"weight"
3"pulse"
4"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
emotionTells2
narrationSentences134
matches
0"d with fury"
1"was surprised"
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount0
hedgeCount1
narrationSentences134
filterMatches(empty)
hedgeMatches
0"began to"
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences174
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen24
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans2
markdownWords5
totalWords1343
ratio0.004
matches
0"out"
1"Marcus Holt, Private Investigator."
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions19
unquotedAttributions0
matches(empty)
83.33% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions38
wordCount970
uniqueNames14
maxNameDensity0.93
worstName"Aurora"
maxWindowNameDensity2.5
worstWindowName"Aurora"
discoveredNames
Raven1
Nest1
Soho1
Carter1
Golden1
Empress1
Silas5
Aurora9
Scotch3
Cardiff2
Eva1
Holt2
Marcus9
Private1
persons
0"Raven"
1"Nest"
2"Carter"
3"Silas"
4"Aurora"
5"Eva"
6"Holt"
7"Marcus"
places
0"Soho"
1"Cardiff"
globalScore1
windowScore0.833
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences69
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1343
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount2
totalSentences174
matches
0"knew that voice"
1"spoken that name"
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs73
mean18.4
std16.14
cv0.877
sampleLengths
052
150
226
34
435
526
610
711
810
944
107
1113
1241
131
1432
153
1670
171
1832
1928
2018
216
224
2316
246
257
268
2727
283
294
3027
318
324
3337
348
352
3632
374
3818
3914
4010
4110
421
4359
4436
453
463
4731
4812
493
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount2
totalSentences134
matches
0"was surprised"
1"being asked"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs169
matches(empty)
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount1
semicolonCount0
flaggedSentences1
totalSentences174
ratio0.006
matches
0"His eyes—still that deep amber-brown—carried a heaviness that hadn’t been there before."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount978
adjectiveStacks0
stackExamples(empty)
adverbCount25
adverbRatio0.02556237218813906
lyAdverbCount4
lyAdverbRatio0.00408997955010225
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences174
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences174
mean7.72
std5.27
cv0.682
sampleLengths
020
18
212
312
421
513
616
714
812
94
1016
1119
124
1317
145
1510
1611
174
186
1911
201
2111
2221
233
243
251
2613
274
288
2918
3011
311
325
334
341
3522
363
3710
3811
3912
408
419
4212
438
441
4512
4620
474
484
4920
56.51% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats15
diversityRatio0.39080459770114945
totalSentences174
uniqueOpeners68
60.61% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount2
totalSentences110
matches
0"Somewhere behind them, the door"
1"Instead, he reached into his"
ratio0.018
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount32
totalSentences110
matches
0"She pulled the day’s delivery"
1"He dried a glass with"
2"She pushed the receipts toward"
3"He gave a near-imperceptible nod"
4"He moved to the bar"
5"He ordered Scotch."
6"She knew that voice."
7"She’d heard it crack jokes"
8"Her own voice surprised her."
9"It came out level."
10"His dark hair had retreated"
11"His eyes—still that deep amber-brown-carried"
12"He said it like a"
13"His face betrayed nothing."
14"He drifted to the other"
15"He touched his jaw."
16"He took a slow sip."
17"She felt her pulse in"
18"She didn’t know what he’d"
19"He set a glass of"
ratio0.291
64.55% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount87
totalSentences110
matches
0"The green neon of The"
1"Aurora Carter shook rain from"
2"She pulled the day’s delivery"
3"The Golden Empress logo on"
4"Silas emerged from the back,"
5"He dried a glass with"
6"She pushed the receipts toward"
7"Silas’s hazel eyes crinkled."
8"The silver signet ring on"
9"He gave a near-imperceptible nod"
10"The door swung open."
11"A man stood in the"
12"He moved to the bar"
13"He ordered Scotch."
14"The voice landed in her"
15"She knew that voice."
16"She’d heard it crack jokes"
17"Her own voice surprised her."
18"It came out level."
19"Nothing like the girl who’d"
ratio0.791
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences110
matches(empty)
ratio0
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences40
technicalSentenceCount2
matches
0"Broad-shouldered in a way that spoke of discipline rather than genetics."
1"His eyes—still that deep amber-brown—carried a heaviness that hadn’t been there before."
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags16
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags9
fancyCount1
fancyTags
0"Marcus continued (continue)"
dialogueSentences58
tagDensity0.155
leniency0.31
rawRatio0.111
effectiveRatio0.034
90.5079%