Run: 2026-02-19-01KHTX5MRRZDFP6JXKYY8CGH2X

Run Details

Duration:
5.5s
Cost:
$0.000000
Provider:
Stealth

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 flickered above the doorway, a thin slice of light that cut through the night’s drizzle. Inside, the air smelled of stale whisky and old paper, the walls crowded with maps whose edges curled like forgotten routes. A photograph of a black‑and‑white street scene hung opposite the bar, its glass cracked, the image half‑lost. She pushed the door open, the bell’s tinny chime echoing off the low ceiling. Aurora Carter slipped past a cluster of regulars, her black hair catching the dim glow as she moved toward the back. Her bright blue eyes scanned the room, landing on a familiar silhouette perched on a stool near the corner, his grey‑streaked auburn hair catching the neon’s green hue. Silas Blackwood lifted his glass, the amber liquid catching the light, and turned. The limp in his left leg shifted his weight, a subtle tremor that belied the steady confidence of his posture. He wore the silver signet ring on his right hand, the metal glinting as his fingers curled around the glass. Aurora paused, the weight of years pressing against her ribs. She had not seen Silas since the night they’d walked out of the university library, arguing over a case file that never existed. Back then, she’d been a student of law, eyes sharp, voice steady. Now, the delivery bag slung over her shoulder bore the imprint of Yu‑Fei Cheung’s Golden Empress logo, a reminder of the life she’d chosen after the storm with Evan. She crossed the floor, each step a soft thud on the worn wooden boards. “Silas,” she said, the name slipping out like a secret she’d kept too long. He lifted his brow, the corners of his mouth twitching in a half‑smile that didn’t reach his eyes. “Aurora,” he replied, his voice low, the timbre still carrying the echo of a field operative’s command. The bar’s chatter dimmed around them, the clink of glasses a distant percussion. A lone saxophone moaned from the jukebox, its notes curling through the smoke. She lowered her bag onto the stool, the strap scraping the wood. “The Nest still keeps its ghosts,” she observed, glancing at the maps that seemed to pulse with forgotten missions. He set his glass down, the coaster thudding against the polished surface. “It’s a refuge for some,” he said, his fingers tracing the rim of the glass. “For others, it’s a reminder.” Aurora’s gaze lingered on the scar that traced a crescent on her left wrist, a faint line that caught the neon’s amber. “I left the law,” she said, the words matter little. “I delivered meals. I lived in a flat above this place. The city’s pulse beats faster now.” He chuckled, a dry sound that didn’t quite reach his eyes. “You always found a way out of the maze,” he said, his tone a blend of admiration and melancholy. “I retired after Prague. The knee didn’t heal, but the mind never did.” She watched the flicker of a candle on the bar, the flame dancing as if caught in a wind she couldn’t feel. “You gave everything to the service,” she said. “Now you serve drinks. You own this place.” He lifted his ringed hand, the silver catching the light. “The signet’s a reminder,” he said, “of who we were, of the vows we took. The bar is a front, a mask for the world that never forgets the past.” A pause settled, thick as the smoke curling from a cigarette in the corner. Aurora’s eyes drifted to a photograph of a rain‑slicked street, the image blurred like a memory. “Do you ever wonder,” she asked, “if the choices we made were the right ones?” He stared at the photograph, his face unreadable. “The rightness of a choice is a luxury,” he said, his voice low. “We live with the consequences.” She lifted her glass, the amber catching the neon. “We all carry regrets,” she said, her tone steady. “I’ve watched myself slip into a rhythm that never felt like mine. I’ve been haunted by the echo of a voice that never stopped.” He placed his glass on the bar, the sound echoing softly. “I’ve watched men disappear into shadows, swallowed by the very things they tried to protect.” The saxophone’s solo rose, a mournful cry that seemed to echo their unspoken words. Aurora’s fingers twitched, the scar on her wrist catching the light. “Do you think,” she said, “that we could have been something else? That the world could have turned differently?” He leaned forward, the limp in his leg shifting his weight onto the other foot. “We were young, full of ideals,” he said, his eyes narrowing. “The world has a way of reshaping us, of carving paths we never imagined.” She stared at the maps, the ink faded, the continents blurred. “I thought I’d be a barrister’s daughter, a lawyer, a voice for justice,” she said, her voice a whisper. “Now I’m a courier, delivering food to strangers.” He smiled, a thin line that seemed to hide more than it revealed. “You always had a talent for navigating mazes,” he said, the words warm but distant. “You found shortcuts where others saw walls.” She lifted her chin, the scar catching the neon’s green. “I think you always saw the world in black and white,” she said, “but you never saw the shades we lived in.” He pressed his thumb against the signet ring, the metal cool. “I learned to read between the lines,” he said, “to listen to the silence that follows a gunshot.” A sudden clatter of glasses from the bar’s far end broke their reverie. A patron spilled a drink, the amber spreading across the wood. The bartender, a wiry man with a tattoo of a raven on his forearm, rushed to clean, his movements swift. Aurora watched the bartender’s hands, the way they moved with practiced ease. “You taught me to survive,” she said, “to find a way when the doors close.” He turned his head, his eyes catching the neon’s glow. “I taught you to think outside the box,” he said, his voice soft. “You taught me that even a spy can become a bartender.” She laughed, a short, sharp sound that cut through the bar’s hum. “We’re both ghosts now,” she said, the words tasting like ash. He raised his glass, the amber catching the light. “To the ghosts that linger,” he said, his voice steady. “To the nights we missed.” She clinked her glass against his, the sound bright against the low murmur. “To the mornings we never had,” she said, the words heavy. The saxophone faded, leaving a lingering note that hung like a question in the air. Aurora’s eyes flickered to the doorway, where the rain hammered the pavement, the city outside a blur of neon and darkness. He stared at the door, his mind tracing the steps that had led him here, the years that had stretched between them. “I never expected to see you here,” he said, his tone a mixture of surprise and resignation. She nodded, the scar on her wrist a silent reminder of a childhood accident that had marked her forever. “Life has a way of looping back,” she said, her voice steady. The bar’s neon sign flickered again, a green pulse that seemed to echo the heartbeat of the city outside. The rain intensified, the sound of droplets on the windows a steady rhythm. He lifted his glass once more, the amber swirling like a storm. “We have a lot to say,” he said, his eyes meeting hers, “but the night’s thin.” She placed her hand on the edge of the bar, the wood warm from the heat of the room. “We have a lot to say,” she repeated, the words a promise and a warning. The bartender brushed past them, his steps quick, his eyes briefly meeting theirs before he disappeared into the back room, the secret door of the bookshelf moving with a soft click. She turned back to the maps, tracing a line with her fingertip. “Do you ever think about the people we left behind?” she asked, the question hanging like a thread. He stared at the signet ring, the silver catching the neon. “Every night,” he said, his voice low. “Every night I hear their names in the wind.” She swallowed, the scar on her wrist catching the light again. “I hear them too,” she said, the words a soft sob. The saxophone’s final note lingered, a low hum that seemed to vibrate through the bar’s floorboards. The rain outside intensified, a steady drum against the windows. He stood, his limp steady as he placed his glasses down. “We should talk more,” he said, his voice a mixture of hope and caution. She nodded, the scar on her left reflecting the neon’s glow. “We should,” she agreed, the words a promise, a question. The green neon sign flickered once more, a brief flash that seemed to capture the weight of their shared past. The bar, with its maps and photographs, held its breath, the secret room behind the bookshelf waiting for a story that might never be told.
created_at"2026-02-19T12:14:36.829Z" 2/19/2026, 12:14:36 PM
model"openrouter/aurora-alpha"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency1178
moderation_latency(null)
generation_time5048
tokens_prompt1094
tokens_completion2320
native_tokens_prompt957
native_tokens_completion1918
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
router(null)
provider_responses(null)
api_type"completions"
id"gen-1771503276-Zut8p8CgOs887ztwsROd"
upstream_id"gen-1771503276-Zut8p8CgOs887ztwsROd"
total_cost0
cache_discount(null)
upstream_inference_cost0
provider_name"Stealth"

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags31
adverbTagCount0
adverbTags(empty)
dialogueSentences44
tagDensity0.705
leniency1
rawRatio0
effectiveRatio0
93.46% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1528
totalAiIsmAdverbs2
found
0
adverb"softly"
count1
1
adverb"very"
count1
highlights
0"softly"
1"very"
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)
0.00% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1528
totalAiIsms36
found
0
word"flickered"
count4
1
word"echoing"
count2
2
word"scanned"
count1
3
word"familiar"
count1
4
word"weight"
count4
5
word"glinting"
count1
6
word"reminder"
count4
7
word"echo"
count4
8
word"pulse"
count3
9
word"tracing"
count3
10
word"traced"
count1
11
word"flicker"
count1
12
word"dancing"
count1
13
word"unreadable"
count1
14
word"unspoken"
count1
15
word"whisper"
count1
16
word"navigating"
count1
17
word"silence"
count1
18
word"practiced ease"
count1
highlights
0"flickered"
1"echoing"
2"scanned"
3"familiar"
4"weight"
5"glinting"
6"reminder"
7"echo"
8"pulse"
9"tracing"
10"traced"
11"flicker"
12"dancing"
13"unreadable"
14"unspoken"
15"whisper"
16"navigating"
17"silence"
18"practiced ease"
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
narrationSentences92
matches(empty)
49.69% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount0
hedgeCount6
narrationSentences92
filterMatches(empty)
hedgeMatches
0"seemed to"
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences105
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
maxSentenceWordsSeen31
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1528
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions34
unquotedAttributions0
matches(empty)
100.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions15
wordCount1134
uniqueNames8
maxNameDensity0.62
worstName"Aurora"
maxWindowNameDensity1.5
worstWindowName"Aurora"
discoveredNames
Carter1
Blackwood1
Silas2
Cheung1
Golden1
Empress1
Evan1
Aurora7
persons
0"Carter"
1"Blackwood"
2"Silas"
3"Cheung"
4"Evan"
5"Aurora"
places(empty)
globalScore1
windowScore1
0.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences77
glossingSentenceCount7
matches
0"maps that seemed to pulse with forgotten missions"
1"quite reach his eyes"
2"cry that seemed to echo their unspoken words"
3"line that seemed to hide more than it revealed"
4"pulse that seemed to echo the heartbeat of the city outside"
5"hum that seemed to vibrate through the bar’s floorboards"
6"flash that seemed to capture the weight of their shared past"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1528
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences105
matches(empty)
53.62% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs45
mean33.96
std11.47
cv0.338
sampleLengths
056
163
253
374
428
535
626
731
832
949
1043
1138
1240
1330
1415
1526
1642
1726
1825
1919
2040
2138
2235
2332
2429
2544
2627
2734
2823
2924
3024
3136
3239
3331
3432
3528
3634
3731
3830
3927
4022
4126
4225
4321
4445
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount0
totalSentences92
matches(empty)
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs186
matches(empty)
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences105
ratio0
matches(empty)
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount1134
adjectiveStacks0
stackExamples(empty)
adverbCount24
adverbRatio0.021164021164021163
lyAdverbCount3
lyAdverbRatio0.0026455026455026454
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences105
echoCount0
echoWords(empty)
86.14% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences105
mean14.55
std5.32
cv0.365
sampleLengths
018
121
217
314
421
528
613
720
820
910
1023
1112
1229
1314
1414
1518
1617
1713
1813
1912
2019
2112
2215
235
2422
2510
2617
2711
2819
2913
3022
318
328
3310
3430
3514
3616
3715
388
3913
405
419
429
4324
4411
4515
4614
4711
4819
4915
42.38% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats8
diversityRatio0.18095238095238095
totalSentences105
uniqueOpeners19
0.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount0
totalSentences85
matches(empty)
ratio0
0.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount56
totalSentences85
matches
0"She pushed the door open,"
1"Her bright blue eyes scanned"
2"He wore the silver signet"
3"She had not seen Silas"
4"She crossed the floor, each"
5"she said, the name slipping"
6"He lifted his brow, the"
7"he replied, his voice low,"
8"She lowered her bag onto"
9"she observed, glancing at the"
10"He set his glass down,"
11"he said, his fingers tracing"
12"she said, the words matter"
13"He chuckled, a dry sound"
14"he said, his tone a"
15"She watched the flicker of"
16"He lifted his ringed hand,"
17"He stared at the photograph,"
18"he said, his voice low"
19"She lifted her glass, the"
ratio0.659
0.00% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount82
totalSentences85
matches
0"The green neon flickered above"
1"A photograph of a black‑and‑white"
2"She pushed the door open,"
3"Aurora Carter slipped past a"
4"Her bright blue eyes scanned"
5"Silas Blackwood lifted his glass,"
6"The limp in his left"
7"He wore the silver signet"
8"Aurora paused, the weight of"
9"She had not seen Silas"
10"She crossed the floor, each"
11"she said, the name slipping"
12"He lifted his brow, the"
13"he replied, his voice low,"
14"The bar’s chatter dimmed around"
15"A lone saxophone moaned from"
16"She lowered her bag onto"
17"she observed, glancing at the"
18"He set his glass down,"
19"he said, his fingers tracing"
ratio0.965
58.82% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount1
totalSentences85
matches
0"Now, the delivery bag slung"
ratio0.012
32.02% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences58
technicalSentenceCount9
matches
0"The limp in his left leg shifted his weight, a subtle tremor that belied the steady confidence of his posture."
1"He lifted his brow, the corners of his mouth twitching in a half‑smile that didn’t reach his eyes."
2"The saxophone’s solo rose, a mournful cry that seemed to echo their unspoken words."
3"The saxophone faded, leaving a lingering note that hung like a question in the air."
4"She nodded, the scar on her wrist a silent reminder of a childhood accident that had marked her forever."
5"The bar’s neon sign flickered again, a green pulse that seemed to echo the heartbeat of the city outside."
6"The saxophone’s final note lingered, a low hum that seemed to vibrate through the bar’s floorboards."
7"The green neon sign flickered once more, a brief flash that seemed to capture the weight of their shared past."
8"The bar, with its maps and photographs, held its breath, the secret room behind the bookshelf waiting for a story that might never be told."
0.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags31
uselessAdditionCount15
matches
0"he said, his fingers tracing the rim of the glass"
1"he said, his tone a blend of admiration and melancholy"
2"he said, his voice low"
3"she said, her tone steady"
4"he said, his eyes narrowing"
5"she said, her voice a whisper"
6"he said, his voice soft"
7"he said, his voice steady"
8"he said, his tone a mixture of surprise and resignation"
9"she said, her voice steady"
10"she repeated, the words a promise and a warning"
11"she asked, the question hanging like a thread"
12"he said, his voice low"
13"he said, his voice a mixture of hope and caution"
14"she agreed, the words a promise, a question"
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags31
fancyCount3
fancyTags
0"she observed (observe)"
1"she repeated (repeat)"
2"she agreed (agree)"
dialogueSentences44
tagDensity0.705
leniency1
rawRatio0.097
effectiveRatio0.097
70.5375%