Run: 2026-02-19-01KHTX3KS92EDBF6SJGRZPAR66

Run Details

Duration:
22.5s
Cost:
$0.010607
Provider:
Amazon Bedrock

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
Rain drummed a steady rhythm against the pavement outside The Raven’s Nest, the kind of persistent London drizzle that seeped into coats and moods alike. Inside, the bar glowed in amber pockets beneath low-hanging brass lamps. Jazz hummed from a vintage record player behind the counter — Chet Baker, late ‘50s, something melancholy and slow. Silas stood behind the bar, polishing a tumbler with a cloth, his signet ring catching the dim light each time he turned his wrist. His limp was more pronounced tonight, a remnant of Prague and bad decisions layered in frost and gunfire. The door creaked open. A man stepped in, shaking water from a long wool coat. He looked too sharp for Soho on a Tuesday — charcoal suit, polished brogues, a trench folded over one arm like it weighed nothing. His hair, once shaggy and sun-bleached, was now cropped close, greying at the temples. He scanned the room with an agent’s precision, not a tourist’s curiosity. Silas didn’t look up. “Took you long enough.” The man froze. Then, slowly, he smiled — a thing not meant for strangers. “You still serving whiskey neat or did you go artisanal on me?” “Only the cheap stuff for liars,” Silas said. “The good stuff’s reserved for ghosts.” The man approached. Set his trench on the stool beside him. “I’m not a ghost.” “You’re close.” They looked at each other, really looked, for the first time in twelve years. Silas saw the lines around the man’s eyes — not from laughter anymore, but calculation. The easy warmth in his posture had been replaced by containment, like he was bracing for impact. Silas set the tumbler down. Poured two fingers of Oban. Pushed one across the bar. The man picked it up. Sniffed. “Still the same?” “Still better than you deserve.” He laughed, but it didn’t land. “Always knew how to make a reunion sting.” “You disappeared,” Silas said. “No call. No letter. Just a burned apartment and a bullet in the wall where your head used to be.” “That wasn’t my head,” the man said quietly. “It was Kostić’s.” Silas exhaled through his nose. “So you vanished into the wind. Left me to clean up the mess. Again.” “You didn’t have to,” the man said. “You could’ve walked away.” “And let them come after you? After *us*?” Silas leaned against the bar, fingers curling around the edge. “You were reckless. Always were. Thought you could outsmart a black cell with charm and a forged passport.” “I survived.” “At what cost?” The man — Elias Voss — didn’t answer. He swirled the whiskey, watching the slow spiral of liquid cling to glass. “I heard you got out. Retired. Became a bartender.” “I became a curator,” Silas corrected. “For people who need to disappear. Or be found.” “You always were good at holding secrets.” “And you were terrible at keeping them.” Elias glanced at the bookshelf behind the bar — floor-to-ceiling, leather-bound, a little too symmetrical. “Still got the back room?” Silas didn’t reply. Didn’t need to. A figure appeared at the top of the narrow staircase that led to the flats above. Light from the landing haloed her — black hair falling flat against her collar, blue eyes scanning the room not with curiosity, but appraisal. She wore a damp navy tracksuit, courier bag slung over one shoulder, the Golden Empress logo stitched above the breast. Elias turned. His breath caught, just slightly. She didn’t smile. “Silas. Food’s here.” Silas nodded. “Aurora. Come down. You remember Elias?” Rory paused. Her gaze landed on him like a blade testing stone. Then she descended, slow, deliberate. “Yeah. I remember.” Elias stood. “Rory.” “Evan.” Her voice was flat. “Haven’t heard that name in years.” He flinched — not dramatically, just a tightening around the eyes. “I go by Elias now.” “Do you.” She set a brown paper bag on the bar. “Yu-Fei said extra dumplings. On the house.” Silas reached for the bag. Rory didn’t move. She stared at Elias like she was recalibrating the past. He looked different — older, yes, but also hollowed out, as if someone had taken the boy who screamed at her in kitchens, who left fingerprints like bruises on her arms, and sanded him down to something almost civil. “You look well,” he said. “I am.” Silence. Long enough for the music to bleed through. “You two know each other?” Silas asked, though he already knew. Elias didn’t take his eyes off her. “We were… close.” Rory snorted. “Is that what you’re calling it now?” “I didn’t know you worked for Silas.” “I don’t.” She pulled off her gloves. The crescent scar on her wrist caught the light — white, thin, a secret the sleeve usually hid. “I live upstairs. Deliver food. That’s it.” Elias stared at the scar. Rory followed his gaze. “Still got yours,” she said. “On your ribs. From when I kicked the boxcutter into the sink.” He touched his side instinctively. “Yeah.” “You ever think about it?” she asked. “Or did you just erase it all and move on?” “I didn’t move on,” he said. “I ran.” “And left me to clean up *your* mess.” “I was trying to keep you safe.” “By vanishing?” She stepped closer. “You told me you loved me one night. The next, your flat’s a crime scene and I’m getting death threats from men who think I know where you hid the files.” “I didn’t have a choice.” “You always had a choice,” she said. “You chose yourself.” Silas placed a hand on the bar — not heavy, just present. A boundary. Elias looked down. “I tried to contact you. After Prague. After the op collapsed. But you were gone. Cardiff. Then London. Off-grid.” “I didn’t go off-grid,” Rory said. “I just stopped being yours.” He reached into his coat. Pulled out an envelope. Worn at the edges. “I kept this,” he said. “All these years.” She didn’t take it. “What is it?” “The postcard you sent. From Tenby. With the seagull shitting on the lighthouse. You wrote, *‘Wish you were here to ruin the view.’*” Her throat worked. Once. Then she looked away. “I thought about you,” he said. “Every damn day.” “Good,” she said quietly. “You should.” Silas picked up the envelope, slid it to the side. “She’s not part of this anymore, Elias. Whatever you’re here for — it stays away from her.” Elias finally looked at Silas. “They’re reviving the Prague file. Reopening the inquiry. Someone’s naming names.” “You’re not safe.” “I never was.” Rory moved then — turned on her heel. “I’m going upstairs. The dumplings are getting cold.” “Aurora—” Elias began. She stopped. But didn’t turn. “I’m sorry,” he said. “For everything.” She exhaled. A long, slow release. “Apologies don’t heal wrists,” she said. “Or trust. Or time.” Then she climbed the stairs without looking back. The door closed softly. Elias stared at the space where she’d stood. “She called me Evan.” Silas poured another drink. “She calls no one by their old names.”
created_at"2026-02-19T12:13:30.287Z" 2/19/2026, 12:13:30 PM
model"writer/palmyra-x5-20250428"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency429
moderation_latency92
generation_time22288
tokens_prompt1094
tokens_completion1973
native_tokens_prompt1009
native_tokens_completion1667
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"
usage0.0106074
router(null)
provider_responses
0
endpoint_id"c684c4e7-1b77-4ca5-9516-7ecc66e2c455"
is_byokfalse
latency429
model_permaslug"writer/palmyra-x5-20250428"
provider_name"Amazon Bedrock"
status200
api_type"completions"
id"gen-1771503210-2hIvt1gn5WEbKe81jMmz"
upstream_id(null)
total_cost0.0106074
cache_discount(null)
upstream_inference_cost0
provider_name"Amazon Bedrock"

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags23
adverbTagCount2
adverbTags
0"the man said quietly [quietly]"
1"she said quietly [quietly]"
dialogueSentences80
tagDensity0.288
leniency0.575
rawRatio0.087
effectiveRatio0.05
82.85% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1166
totalAiIsmAdverbs4
found
0
adverb"slowly"
count1
1
adverb"really"
count1
2
adverb"slightly"
count1
3
adverb"softly"
count1
highlights
0"slowly"
1"really"
2"slightly"
3"softly"
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)
78.56% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1166
totalAiIsms5
found
0
word"scanned"
count1
1
word"warmth"
count1
2
word"charm"
count1
3
word"scanning"
count1
4
word"silence"
count1
highlights
0"scanned"
1"warmth"
2"charm"
3"scanning"
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
emotionTells0
narrationSentences98
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount0
hedgeCount0
narrationSentences98
filterMatches(empty)
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences155
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
maxSentenceWordsSeen38
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans3
markdownWords10
totalWords1173
ratio0.009
matches
0"us"
1"your"
2"‘Wish you were here to ruin the view.’"
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions24
unquotedAttributions0
matches(empty)
16.67% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions47
wordCount690
uniqueNames16
maxNameDensity2.46
worstName"Silas"
maxWindowNameDensity4.5
worstWindowName"Silas"
discoveredNames
Raven1
Nest1
London1
Chet1
Baker1
Silas17
Prague1
Soho1
Tuesday1
Oban1
Elias11
Voss1
Golden1
Empress1
Silence1
Rory6
persons
0"Chet"
1"Baker"
2"Silas"
3"Elias"
4"Voss"
5"Rory"
places
0"Raven"
1"London"
2"Prague"
3"Soho"
globalScore0.268
windowScore0.167
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences36
glossingSentenceCount0
matches(empty)
29.50% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches2
per1kWords1.705
wordCount1173
matches
0"not from laughter anymore, but calculation"
1"not with curiosity, but appraisal"
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences155
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs74
mean15.85
std16.57
cv1.045
sampleLengths
097
165
28
326
414
515
62
761
89
95
1014
1124
1211
1319
1411
1536
162
173
1830
1915
207
217
2220
236
2460
257
266
278
2820
293
3011
3116
3218
3357
345
352
369
3711
3810
399
407
4132
425
4321
446
4517
468
478
487
4936
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount1
totalSentences98
matches
0"been replaced"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount2
totalVerbs134
matches
0"was bracing"
1"was recalibrating"
0.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount13
semicolonCount0
flaggedSentences12
totalSentences155
ratio0.077
matches
0"Jazz hummed from a vintage record player behind the counter — Chet Baker, late ‘50s, something melancholy and slow."
1"He looked too sharp for Soho on a Tuesday — charcoal suit, polished brogues, a trench folded over one arm like it weighed nothing."
2"Then, slowly, he smiled — a thing not meant for strangers."
3"Silas saw the lines around the man’s eyes — not from laughter anymore, but calculation."
4"The man — Elias Voss — didn’t answer."
5"Elias glanced at the bookshelf behind the bar — floor-to-ceiling, leather-bound, a little too symmetrical."
6"Light from the landing haloed her — black hair falling flat against her collar, blue eyes scanning the room not with curiosity, but appraisal."
7"He flinched — not dramatically, just a tightening around the eyes."
8"He looked different — older, yes, but also hollowed out, as if someone had taken the boy who screamed at her in kitchens, who left fingerprints like bruises on her arms, and sanded him down to something almost civil."
9"The crescent scar on her wrist caught the light — white, thin, a secret the sleeve usually hid."
10"Silas placed a hand on the bar — not heavy, just present."
11"Rory moved then — turned on her heel."
95.33% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount397
adjectiveStacks0
stackExamples(empty)
adverbCount18
adverbRatio0.04534005037783375
lyAdverbCount3
lyAdverbRatio0.007556675062972292
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences155
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences155
mean7.57
std6.28
cv0.83
sampleLengths
025
111
219
324
418
54
611
724
814
912
104
114
123
1311
1412
158
166
173
188
194
202
2114
2215
2317
245
255
265
275
281
293
305
316
328
334
3420
358
363
375
3814
397
404
4118
4218
432
443
458
4613
479
486
499
52.69% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats10
diversityRatio0.3548387096774194
totalSentences155
uniqueOpeners55
100.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount4
totalSentences73
matches
0"Then, slowly, he smiled —"
1"Then she descended, slow, deliberate."
2"Then she looked away."
3"Then she climbed the stairs"
ratio0.055
93.97% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount23
totalSentences73
matches
0"His limp was more pronounced"
1"He looked too sharp for"
2"His hair, once shaggy and"
3"He scanned the room with"
4"They looked at each other,"
5"He laughed, but it didn’t"
6"He swirled the whiskey, watching"
7"She wore a damp navy"
8"His breath caught, just slightly."
9"She didn’t smile."
10"Her gaze landed on him"
11"Her voice was flat"
12"He flinched — not dramatically,"
13"She set a brown paper"
14"She stared at Elias like"
15"He looked different — older,"
16"She pulled off her gloves"
17"He touched his side instinctively."
18"She stepped closer"
19"He reached into his coat."
ratio0.315
55.89% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount59
totalSentences73
matches
0"Rain drummed a steady rhythm"
1"Jazz hummed from a vintage"
2"Silas stood behind the bar,"
3"His limp was more pronounced"
4"The door creaked open."
5"A man stepped in, shaking"
6"He looked too sharp for"
7"His hair, once shaggy and"
8"He scanned the room with"
9"Silas didn’t look up."
10"The man froze."
11"The man approached."
12"They looked at each other,"
13"Silas saw the lines around"
14"The easy warmth in his"
15"Silas set the tumbler down."
16"The man picked it up."
17"He laughed, but it didn’t"
18"the man said quietly"
19"Silas exhaled through his nose."
ratio0.808
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences73
matches(empty)
ratio0
83.33% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences24
technicalSentenceCount2
matches
0"Rain drummed a steady rhythm against the pavement outside The Raven’s Nest, the kind of persistent London drizzle that seeped into coats and moods alike."
1"He looked different — older, yes, but also hollowed out, as if someone had taken the boy who screamed at her in kitchens, who left fingerprints like bruises on …"
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags23
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags17
fancyCount1
fancyTags
0"Silas corrected (correct)"
dialogueSentences80
tagDensity0.213
leniency0.425
rawRatio0.059
effectiveRatio0.025
82.9594%