Run: 2026-10-08-01M4DAHHBJ97TS26TSNKK4059Y

Run Details

Duration:
25.1s
Cost:
$0.002268
Provider:
Claude Platform on AWS

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 above the door of the Raven's Nest stuttered the way it always had, the second letter flickering so the sign read RAVEN'S NES. Rory ducked beneath it with Dean Street's rain still dripping off her hood and the Golden Empress delivery bag hanging heavy from one shoulder. Ten hours of soaked cardboard had softened the plastic handles to rag. Silas glanced up from the taps and lifted two fingers from the bar, the nod he reserved for people who paid rent above his cellar. Then his gaze slid past her to the far end of the counter, and it stayed there a moment too long. Rory followed it. A woman sat hunched over a short glass of something clear, a cream wool coat folded across the stool beside her. Her hair had been cropped into a sharp bob the colour of wet sand. Rory knew the set of those shoulders before she knew the face. Eva had never once in her life sat with her back to a room. "Don't," Rory said. Silas set a whisky in front of a man in a pinstriped suit. "I haven't said a word." "You were about to." "I was about to offer you a towel." He nodded at the bag. "Get that off the floor before someone trips on it." She crossed the room the long way, past the wall of yellowed maps and the black-and-white photographs of men nobody had bothered to name, and stopped beside the stool. The bag thumped against her hip. "Eva." Eva turned, and something in her face shut like a door and then, reluctantly, opened again. "Rory." She looked her up and down. "Christ. You look like you've been dragged out of the Taff." "I've been out in it since six. Is that gin?" "Soda water. Gin's for people with somewhere to be in the morning." Eva lifted her left hand from the glass. A thin band of gold caught the green light from the window. "I've got a nine o'clock with a man called Hallam about a block of flats in Walthamstow. Forty-two units. He wants them to look like they were built by someone who cared." "And were they?" "Built by a man who cared about his margins." Eva's mouth twitched, but it didn't reach her eyes. "You'd be good at that. Telling him no in a way that sounds like yes." Rory took the stool beside her. It was too low, and her knees came up awkwardly. She put the bag on the floor. Her thumb found the thin crescent scar on the inside of her left wrist, the way it always did when she sat down somewhere she hadn't planned to be. Eva watched the movement. "You still do that." "Do what?" "Rub that thing like it's a rosary." Eva turned her glass a quarter-turn on its mat. "Ring's new, by the way. Eight months. He's an accountant. He's kind, and he's dull as dishwater, and I love him so much it makes me want to lie down on the pavement." "Congratulations." "Gwen's three. Tom's seven months. You'd know that if you'd picked up." The words landed flat on the bar between them. Rory looked at the wall of maps instead, at the thin red line of a coastal road in Brittany that had been faded for decades. "I know," she said. "You don't know. You've never seen a picture of him. I sent you four." Eva's voice stayed level, which was worse than if it had risen. "I rang you the night Mum died. Three times. You sent lilies." "I know." "I hate lilies." "I know that too." "Do you?" Eva picked up the glass and didn't drink from it. "Because I've been thinking about it all day, and I'm not sure I ever told you that. Maybe I just assumed you'd remember, like you remember everything else about me, right up until it's inconvenient." Silas appeared on the other side of the bar. He moved with the careful weight he always carried in his left leg, and the silver signet on his right hand tapped the wood once as he set down a pint of bitter in front of Rory. She hadn't ordered it. She hadn't needed to. "On the house," he said. "Eva, your cab's booked for half nine. I'll ring them back if you want more time." "I don't want more time." Eva didn't look at him. She looked at Rory. "I want to know whether you remember what you said at the station." Rory's hand stopped on the glass. The condensation cold against her palm. "I said I'd send for you," she said. "You said the minute you had a bed that wasn't a sofa." Eva's fingers curled around the stem of her glass. "You had a sofa for six years, Rory. I know, because I came up on the train twice to see it and you had the same mug on the same arm both times. Then I stopped coming, and you stopped writing, and then you were the one who sent lilies." "It wasn't like that." "Then what was it like?" The neon above the door flickered again, and for a second the letters disappeared entirely, leaving the room lit only by the bottles behind the bar and the amber glow of the whisky in the pinstriped man's glass. Rory opened her mouth, closed it, and reached for the pint instead.
created_at"2026-10-08T08:37:10.65Z" 10/8/2026, 8:37:10 AM
model"anthropic/claude-haiku-5.5-20261007"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency21881
moderation_latency(null)
generation_time25046
tokens_prompt1063
tokens_completion1219
native_tokens_prompt1550
native_tokens_completion4226
native_tokens_completion_images(null)
native_tokens_reasoning2563
native_tokens_cached0
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"end_turn"
service_tier"default"
usage0.002268
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.21.0; linux; x64))"
http_referer(null)
request_id"req-1791448630-V8F7nWiyCTjJdpXuonAP"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1791448630-PEqymRFm7Aw5zO5DbLsA"
upstream_id"msg_011CfpTyxQeKUj4EJDwasptq"
provider_responses
0
endpoint_id"b6cdf493-3a61-441f-a134-e7944fddb980"
id"msg_011CfpTyxQeKUj4EJDwasptq"
is_byokfalse
latency799
model_permaslug"anthropic/claude-haiku-5.5-20261007"
provider_name"Claude Platform on AWS"
status200
total_cost0.002268
cache_discount(null)
upstream_inference_cost0
provider_name"Claude Platform on AWS"
response_cache_source_id(null)
data_region"global"
workspace_id"97e315e5-d303-487d-83c1-83180e8a13d4"

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags13
adverbTagCount1
adverbTags
0"Eva's fingers curled around [around]"
dialogueSentences37
tagDensity0.351
leniency0.703
rawRatio0.077
effectiveRatio0.054
94.49% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount908
totalAiIsmAdverbs1
found
0
adverb"reluctantly"
count1
highlights
0"reluctantly"
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)
88.99% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount908
totalAiIsms2
found
0
word"weight"
count1
1
word"flickered"
count1
highlights
0"weight"
1"flickered"
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
narrationSentences44
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount0
hedgeCount0
narrationSentences44
filterMatches(empty)
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences68
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen50
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords908
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions12
unquotedAttributions0
matches(empty)
50.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions30
wordCount539
uniqueNames10
maxNameDensity1.86
worstName"Eva"
maxWindowNameDensity3.5
worstWindowName"Eva"
discoveredNames
Raven1
Nest1
Dean1
Street1
Golden1
Empress1
Silas3
Eva10
Rory10
Brittany1
persons
0"Raven"
1"Nest"
2"Silas"
3"Eva"
4"Rory"
5"Brittany"
places
0"Dean"
1"Street"
globalScore0.572
windowScore0.5
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences33
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount908
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences68
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs37
mean24.54
std22.06
cv0.899
sampleLengths
062
146
23
361
43
518
64
723
835
91
1034
1110
1264
133
1433
1552
168
172
1849
191
2012
2134
224
2338
242
253
264
2747
2854
2921
3027
3112
328
3371
344
355
3650
89.31% Passive voice overuse
Target: ≤2% passive sentences
passiveCount2
totalSentences44
matches
0"been cropped"
1"been faded"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs87
matches(empty)
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences68
ratio0
matches(empty)
99.48% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount542
adjectiveStacks0
stackExamples(empty)
adverbCount22
adverbRatio0.04059040590405904
lyAdverbCount4
lyAdverbRatio0.007380073800738007
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences68
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences68
mean13.35
std10.56
cv0.791
sampleLengths
026
124
212
325
421
53
621
714
812
914
103
1113
125
134
1413
1510
1629
176
181
1916
207
2111
2210
2320
2412
2532
263
2718
2815
296
3010
317
3229
334
344
352
3616
3733
381
3912
409
4125
424
4326
4412
452
463
474
4812
4935
54.90% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats6
diversityRatio0.38235294117647056
totalSentences68
uniqueOpeners26
83.33% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount1
totalSentences40
matches
0"Then his gaze slid past"
ratio0.025
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount11
totalSentences40
matches
0"Her hair had been cropped"
1"He nodded at the bag"
2"She crossed the room the"
3"She looked her up and"
4"It was too low, and"
5"She put the bag on"
6"Her thumb found the thin"
7"He moved with the careful"
8"She hadn't ordered it."
9"She hadn't needed to."
10"She looked at Rory."
ratio0.275
0.00% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount38
totalSentences40
matches
0"The green neon above the"
1"Rory ducked beneath it with"
2"Silas glanced up from the"
3"Rory followed it."
4"A woman sat hunched over"
5"Her hair had been cropped"
6"Rory knew the set of"
7"Eva had never once in"
8"Silas set a whisky in"
9"He nodded at the bag"
10"She crossed the room the"
11"The bag thumped against her"
12"Eva turned, and something in"
13"She looked her up and"
14"Eva lifted her left hand"
15"A thin band of gold"
16"Eva's mouth twitched, but it"
17"Rory took the stool beside"
18"It was too low, and"
19"She put the bag on"
ratio0.95
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences40
matches(empty)
ratio0
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences19
technicalSentenceCount0
matches(empty)
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags13
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags4
fancyCount0
fancyTags(empty)
dialogueSentences37
tagDensity0.108
leniency0.216
rawRatio0
effectiveRatio0
88.6838%