Run: 2026-02-17-01KHMPCK76J4PBB497MHJQ28Z7

Run Details

Duration:
15.1s
Cost:
$0.025285
Provider:
OpenAI

Model input

System
You are an expert novelist with a gift for vivid, immersive prose. You write in tight third-person limited point of view with a strong narrative voice. Your prose is clean, precise, and engaging — you favor strong verbs, concrete details, and natural-sounding dialogue. You will be given a story bible (codex) containing canonical details about characters, locations, items, and lore. Use these details to ground your writing in the established world. Stay consistent with the codex. Write only the prose of the scene. Do not include titles, chapter headings, markdown formatting, or any commentary before or after the scene.
User/Human
<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> 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.

Model response

AI
Aurora Carter pushed open the heavy wooden door to The Raven’s Nest and was greeted by a wave of deep, familiar nostalgia. The atmosphere inside was rich with the scent of aged whiskey and the low hum of jazz filtering through unseen speakers. The green neon sign outside had beckoned her in, a siren’s call she couldn’t resist. She had almost laughed at the absurdity of it all; meeting Eva here of all places. Her bright blue eyes scanned the dimly lit space, settling momentarily on the walls lined with old maps and black-and-white photographs. Secrets hidden in plain sight. She tugged at the sleeve of her worn leather jacket, a defense against the cold night outside—and perhaps the memories drifting through the room. Silas was at the bar, polishing a glass with a cloth. The dim light caught the silver signet ring on his right hand, a small but constant part of his character. He glanced up, his hazel eyes lighting up as they found her. “Rory,” he greeted, using the nickname she had adopted since moving to London. His voice was warm, if a bit gravelly, like the comforting rumble of distant thunder. She smiled back, though it didn’t quite reach her eyes. “Silas,” she replied, her voice soft but clear. A few patrons dotted the bar, enough to give the place life but not so many that it felt crowded. Silas set the glass down and leaned on the bar, his knee barely registering a complaint that only she would notice. “What brings you here tonight? The usual trouble?” he asked, his tone a perfect blend of curiosity and playful concern. “Meeting a friend, believe it or not,” Rory said, her eyes searching. “She should already be here.” Silas raised an eyebrow. “At the Nest? I’m intrigued already.” Before Rory could respond, a figure emerged from the shadows of a far corner booth. Eva. Rory’s breath caught in her throat. The woman approaching her was both familiar and utterly foreign. The once fiery redhead had traded her careless curls for a sleek, platinum bob. Expensive clothes draped her frame with an elegance that screamed of success. Eva’s green eyes, however, were unmistakably the same—determined and sharp. “Aurora,” Eva said, the name sounding almost strange in her clipped, polished accent. “Eva,” Rory replied, her voice faltering for only a heartbeat. She offered a half-smile. “Or should I say Evelyn now?” Eva’s laugh was light, almost tinkling. “Eva is fine, though I do go by Evelyn in more... professional circles.” The tension between them was palpable, an unspoken understanding that things had changed, irrevocably so. Silas, sensing the need for privacy, nodded to Rory. “I’ll be around if you need anything,” he said before disappearing into the back. “Shall we sit?” Eva suggested, gesturing towards the booth she had occupied. Rory slipped into the plush seat opposite Eva. The dim light above their heads cast a soft glow, highlighting the lines of worry and experience etched into their faces. For a moment, the weight of years pressed down on them, making the air feel heavy. “So, London,” Rory began, a simple statement but one that carried a multitude of questions. “What brings you here?” “The firm,” Eva said, her fingers tracing the rim of her glass, leaving faint fingerprints behind. “We opened an office here two years ago. I oversee the European operations now.” Rory's eyebrows rose. “Quite the leap from what we used to joke about in Cardiff.” The corner of Eva’s mouth twitched upwards. “Things change. People change.” “Yeah,” Rory nodded, looking down at her hands. A small crescent-shaped scar on her left wrist caught her eye. A childhood accident, one of so many shared moments with Eva. Then she looked up, meeting Eva's gaze. “And some things stay exactly the same.” Eva’s smile faltered, and she sighed. “You’re right. There are things... and people... that we carry with us, no matter how much we want to let go.” Rory’s mind wandered back to Cardiff, to the nights they’d spent talking about their dreams and fears, to the laughter that had once come so easily. Then to Eva’s call that had urged her to leave Evan behind, to come to London. A lifeline she had grabbed with both hands. “Why did you reach out now?” Rory asked, her voice softer, laced with an unspoken plea for honesty. Eva’s eyes softened. “I’ve missed you, Rory. And I guess... I needed a friend. Someone who knew me before all of this.” “All of this?” Rory tilted her head, genuinely curious. Eva sighed, her shoulders dropping as if shedding an invisible burden. “The money, the power, the constant game of one-upmanship. It’s exhausting. Sometimes, I feel like I’ve lost myself in it all.” There it was, the raw truth between veils of sophistication and distance. A flicker of the old Eva breaking through. Rory reached out, her hand covering Eva’s. “You’re still in there. Just buried a little deeper, maybe.” Eva squeezed Rory’s hand, a small semblance of connection reestablishing itself. “Thank you,” Eva whispered. “I needed to hear that.” A silence settled between them, but it wasn’t uncomfortable. It was the kind of quiet that held promise, the weight of shared history slowly lifting. “So,” Rory said, her voice lighter, “tell me about this big-shot firm of yours. Actually doing some good in the world?” Eva chuckled, a genuine sound. “Trying to, yes. It’s a corporate jungle out there, but I like to think we’re making strides.” Rory leaned back, feeling a little of the old familiarity return. “Knowing you, I’m sure you are.” Their conversation wove through the years they had missed, touching briefly on the highs and delving hesitantly into the lows. Each story shared was a stepping stone towards rebuilding a bridge they both thought had long since collapsed. As the night deepened, Silas returned to check on them, bringing another round of drinks with a knowing smile. “Old friends are the best kind, aren’t they?” he said, his eyes twinkling with the wisdom of a man who had seen too much. “They are,” Rory agreed, her smile genuine this time. Eva raised her glass. “To old friends, and new beginnings.” They clinked glasses, the soft chime a promise of reconciliation and the enduring strength of their bond. And in that moment, within the dim, nostalgic cocoon of The Raven’s Nest, they found a fragment of their past and a glimmer of hope for the future.
created_at"2026-02-17T02:20:53.502073+00:00" 2/17/2026, 2:20:53 AM
model"openai/gpt-4o-2024-05-13"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency251
moderation_latency(null)
generation_time14923
tokens_prompt867
tokens_completion1723
native_tokens_prompt809
native_tokens_completion1416
native_tokens_completion_images(null)
native_tokens_reasoning0
native_tokens_cached0
num_media_prompt(null)
num_input_audio_prompt(null)
num_media_completion0
num_search_results(null)
origin"https://ncbench.com/"
is_byokfalse
finish_reason"stop"
native_finish_reason"stop"
usage0.025285
router(null)
provider_responses
0
id"chatcmpl-DA4zWGLUwJBoLgonCYFhMkxVvi78l"
status200
is_byokfalse
latency224
endpoint_id"3d6584e7-a2bb-48d6-903d-24e3d90e7e55"
provider_name"OpenAI"
model_permaslug"openai/gpt-4o-2024-05-13"
api_type"completions"
id"gen-1771294838-27eCsyvgcir7x6HrQ5pO"
upstream_id"chatcmpl-DA4zWGLUwJBoLgonCYFhMkxVvi78l"
total_cost0.025285
cache_discount(null)
upstream_inference_cost0
provider_name"OpenAI"

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags17
adverbTagCount0
adverbTags(empty)
dialogueSentences34
tagDensity0.5
leniency1
rawRatio0
effectiveRatio0
86.14% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1082
totalAiIsmAdverbs3
found
0
adverb"utterly"
count1
1
adverb"slowly"
count1
2
adverb"hesitantly"
count1
highlights
0"utterly"
1"slowly"
2"hesitantly"
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)
16.82% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1082
totalAiIsms18
found
0
word"familiar"
count2
1
word"scanned"
count1
2
word"comforting"
count1
3
word"perfect"
count1
4
word"eyebrow"
count1
5
word"determined"
count1
6
word"tension"
count1
7
word"palpable"
count1
8
word"unspoken"
count2
9
word"etched"
count1
10
word"weight"
count2
11
word"tracing"
count1
12
word"flicker"
count1
13
word"silence"
count1
14
word"delving"
count1
highlights
0"familiar"
1"scanned"
2"comforting"
3"perfect"
4"eyebrow"
5"determined"
6"tension"
7"palpable"
8"unspoken"
9"etched"
10"weight"
11"tracing"
12"flicker"
13"silence"
14"delving"
100.00% Cliché density
Target: ≤1 cliche(s) per 800-word window
totalCliches1
maxInWindow1
found
0
label"flicker of emotion"
count1
highlights
0"a glimmer of hope"
100.00% Emotion telling (show vs. tell)
Target: ≤3% sentences with emotion telling
emotionTells0
narrationSentences71
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount0
narrationSentences71
filterMatches
0"feel"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences88
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
maxSentenceWordsSeen28
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1080
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions16
unquotedAttributions0
matches(empty)
0.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions52
wordCount833
uniqueNames9
maxNameDensity2.52
worstName"Eva"
maxWindowNameDensity6
worstWindowName"Eva"
discoveredNames
Carter1
Raven2
Nest2
Eva21
London2
Rory17
Silas5
Cardiff1
Evan1
persons
0"Carter"
1"Raven"
2"Eva"
3"Rory"
4"Silas"
5"Evan"
places
0"London"
1"Cardiff"
globalScore0.239
windowScore0
66.67% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences60
glossingSentenceCount2
matches
0"quite reach her eyes"
1"as if shedding an invisible burden"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1080
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences88
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs39
mean27.69
std18.53
cv0.669
sampleLengths
074
193
228
318
441
520
617
710
868
913
1020
1119
1215
1323
1412
1545
1619
1730
1815
1911
2044
2127
2250
2318
2422
259
2632
2720
2817
2920
3025
3121
3222
3317
3438
3543
369
3710
3845
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount1
totalSentences71
matches
0"was greeted"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs136
matches(empty)
45.45% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount2
semicolonCount1
flaggedSentences3
totalSentences88
ratio0.034
matches
0"She had almost laughed at the absurdity of it all; meeting Eva here of all places."
1"She tugged at the sleeve of her worn leather jacket, a defense against the cold night outside—and perhaps the memories drifting through the room."
2"Eva’s green eyes, however, were unmistakably the same—determined and sharp."
92.50% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount839
adjectiveStacks1
stackExamples
0"small crescent-shaped scar"
adverbCount35
adverbRatio0.041716328963051254
lyAdverbCount14
lyAdverbRatio0.0166865315852205
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences88
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences88
mean12.27
std6.19
cv0.504
sampleLengths
022
121
215
316
421
55
624
711
820
912
1013
1115
1210
138
1420
1521
1620
1712
185
194
206
2115
221
236
2410
2514
2612
2710
2813
2910
304
316
326
3313
3415
359
3614
3712
388
3921
4016
4115
424
4316
4414
453
4612
477
484
498
73.11% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats4
diversityRatio0.4659090909090909
totalSentences88
uniqueOpeners41
96.62% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount2
totalSentences69
matches
0"Then she looked up, meeting"
1"Then to Eva’s call that"
ratio0.029
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount15
totalSentences69
matches
0"She had almost laughed at"
1"Her bright blue eyes scanned"
2"She tugged at the sleeve"
3"He glanced up, his hazel"
4"he greeted, using the nickname"
5"His voice was warm, if"
6"She smiled back, though it"
7"she replied, her voice soft"
8"he asked, his tone a"
9"She offered a half-smile."
10"he said before disappearing into"
11"It was the kind of"
12"Their conversation wove through the"
13"he said, his eyes twinkling"
14"They clinked glasses, the soft"
ratio0.217
25.22% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount60
totalSentences69
matches
0"Aurora Carter pushed open the"
1"The atmosphere inside was rich"
2"The green neon sign outside"
3"She had almost laughed at"
4"Her bright blue eyes scanned"
5"Secrets hidden in plain sight."
6"She tugged at the sleeve"
7"Silas was at the bar,"
8"The dim light caught the"
9"He glanced up, his hazel"
10"he greeted, using the nickname"
11"His voice was warm, if"
12"She smiled back, though it"
13"she replied, her voice soft"
14"Silas set the glass down"
15"he asked, his tone a"
16"Rory said, her eyes searching"
17"Silas raised an eyebrow."
18"Rory’s breath caught in her"
19"The woman approaching her was"
ratio0.87
72.46% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount1
totalSentences69
matches
0"Before Rory could respond, a"
ratio0.014
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences35
technicalSentenceCount1
matches
0"Eva sighed, her shoulders dropping as if shedding an invisible burden."
0.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags17
uselessAdditionCount7
matches
0"she replied, her voice soft but clear"
1"he asked, his tone a perfect blend of curiosity and playful concern"
2"Rory said, her eyes searching"
3"Eva said, the name sounding almost strange in her clipped, polished accent"
4"Rory replied, her voice faltering for only a heartbeat"
5"Rory asked, her voice softer, laced with an unspoken plea for honesty"
6"Rory agreed, her smile genuine this time"
61.76% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags13
fancyCount3
fancyTags
0"Eva suggested (suggest)"
1"Eva whispered (whisper)"
2"Rory agreed (agree)"
dialogueSentences34
tagDensity0.382
leniency0.765
rawRatio0.231
effectiveRatio0.176
81.2249%