Run: 2026-03-11-01KKFFHP8WJ17NGV25Y2CA8FGC

Run Details

Duration:
1m 59s
Cost:
$0.001378
Provider:
Together

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="4416" name="Detective Harlow Quinn" aliases="Quinn, Detective Quinn, Harlow" pronouns="she/her" species="Human" storyRole="Antagonist"> <eyeColor>brown</eyeColor> <hair>closely cropped salt-and-pepper</hair> <height>5'9"</height> <age>41</age> <jawline>sharp jaw</jawline> <watch>worn leather watch on her left wrist</watch> <bearing>military precision</bearing> <description>A Metropolitan Police detective with 18 years of decorated service who suspects the clique is involved in criminal activity.</description> <backstory>She lost her partner, DS Morris, during a case three years ago under unexplained circumstances that had supernatural origins she doesn't yet understand.</backstory> </character> <character id="4417" name="Tomás Herrera" aliases="Tommy, Tomás, Herrera" pronouns="he/him" species="Human" storyRole="Support"> <eyeColor>warm brown</eyeColor> <hair>short curly dark brown</hair> <height>5'10"</height> <age>29</age> <skinTone>olive skin</skinTone> <scar>scar running along his left forearm from a knife attack</scar> <medallion>Saint Christopher medallion around his neck</medallion> <birthplace>Seville, Spain</birthplace> <description>A former paramedic who provides off-the-books medical care for the clique.</description> <backstory>Born in Seville, Spain. He moved to London to work for the NHS but lost his license after administering unauthorized treatments to supernatural patients.</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> <location id="856" name="The Veil Market" aliases="Veil Market, the Market, underground market" realm="Earth"> <currentLocation>abandoned Tube station beneath Camden</currentLocation> <entryRequirement>bone token</entryRequirement> <schedule>moves locations every full moon</schedule> <description>A hidden supernatural black market that sells enchanted goods, banned alchemical substances, and information.</description> </location> </codex> Continue the story using the following instructions: <instructions> Write a fully fleshed out scene of at least 1000 words in the thriller genre. A detective is pursuing a suspect through rain-soaked city streets at night. The chase takes them from the street level down into an underground market. The detective must decide whether to follow the suspect into unfamiliar and potentially dangerous territory. 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 lashed against the pavement. The asphalt drank up the water until it darkened into a mirror. Harlow Quinn walked fast. Her boots splashed through puddles. She held her coat close to her body. Rainwater dripped from her jacket hem. She caught the edge of the streetlight. The wind stung her eyes. Salt and pepper hair fell over her forehead. She shook her head to clear the vision. Her jawline set tight under the fedora. She checked her watch. Leather strap felt tight against the wrist. The second hand moved. The tick tick sounded inside her ear. The signal was the phone. Two blocks south. She ran toward the cut. The subway entrance sat beneath an old station. The metal door stood half open. The shadows pooled inside. She hit the ground. The concrete felt damp. She stepped over the threshold. The air changed. It smelled of diesel and wet concrete. Harlow dropped her bag. The leather thud against the wall. She pushed the heavy metal handle. It groaned. She pushed harder. The door swung inward. She walked down the staircase. Water dripped from the pipes above. At the bottom, she saw the figure. Tomás Herrera turned to face her. His warm brown eyes met her gaze. He looked tired. Water steamed off his skin. "I tracked you here," Harlow said. Her voice echoed in the large space. Tomás wiped his brow with the back of his hand. The scar on his left forearm tore the old skin. "I didn't mean for this." "You led them." Harlow stepped closer. The fluorescent lights buzzed overhead. The wire broke one by one. The space darkened around them. "I needed you here." Tomás held out his hand. He showed the medallion on his neck. The Saint Christopher pendant moved in the air. "This isn't a game." Harlow reached for her gun. The metal felt cold in the dark. "There is a body." "A partner is missing." "I found the piece." "Where?" Tomás moved his arm. The scar gestured toward the walls. The stone walls vibrated with the hum of the earth. Harlow looked at the page. The map stretched across the tunnel. The old London grid appeared. "This is the Veil Market." "You know this." "I know the rules." "You tell me your rules." Tomás stepped onto the tracks. Rails gleamed under the dim light. "Go back." "No." Harlow planted her feet. The weight of her coat pulled down. She raised the gun. Her finger stayed on the trigger. "I want the mistake corrected." "You removed me from the list." "I am still in." "Then I go down." Harlow moved forward. She stepped over the ladder. The air got heavier. She saw the tracks. The rails disappeared into the dark. Tomás stood still. He didn't want to move. The rain stopped her heart. She stopped for a second. "Don't think you're invincible." "Think what you want." "Why the token?" Harlow held the token up. She used the token to open the panel. It gave the green light. "It is my license." "You have no license." "I have the blood." Harlow swallowed. She stepped through the light. The light hung above the platform. She walked down. The stairs went deeper. Sounds of traffic came from far away. A train whistle blew. She put her boot on the final step. The floor shuddered. She looked at Tomás. She waited. The silence stretched long. The dog barked. Harlow pulled the cord. The lights flickered down. She was in the dark now.
created_at"2026-03-11T22:16:16.425Z" 3/11/2026, 10:16:16 PM
model"qwen/qwen3.5-9b-20260310"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency4173
moderation_latency(null)
generation_time118779
tokens_prompt1140
tokens_completion8827
native_tokens_prompt1065
native_tokens_completion8480
native_tokens_completion_images(null)
native_tokens_reasoning7936
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"
usage0.0013785
router(null)
provider_responses
0
endpoint_id"00d506d9-a5e9-4382-a2b9-d54732365594"
id"oagZpLf-3pDw3Z-9dadec2ed00d66f5"
is_byokfalse
latency4173
model_permaslug"qwen/qwen3.5-9b-20260310"
provider_name"Together"
status200
user_agent"langchainjs-openai/1.0.0 ((node/v24.14.0; linux; x64))"
http_referer(null)
api_type"completions"
id"gen-1773267376-v1QWQXUr8ztBktYShlNW"
upstream_id"oagZpLf-3pDw3Z-9dadec2ed00d66f5"
total_cost0.0013785
cache_discount(null)
upstream_inference_cost0
provider_name"Together"

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags6
adverbTagCount0
adverbTags(empty)
dialogueSentences25
tagDensity0.24
leniency0.48
rawRatio0
effectiveRatio0
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount585
totalAiIsmAdverbs0
found(empty)
highlights(empty)
100.00% AI-ism character names
Target: 0 AI-default names (17 tracked, −20% each)
codexExemptions(empty)
found(empty)
100.00% AI-ism location names
Target: 0 AI-default location names (33 tracked, −20% each)
codexExemptions(empty)
found(empty)
57.26% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount585
totalAiIsms5
found
0
word"echoed"
count1
1
word"vibrated"
count1
2
word"weight"
count1
3
word"silence"
count1
4
word"flickered"
count1
highlights
0"echoed"
1"vibrated"
2"weight"
3"silence"
4"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
narrationSentences92
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount0
narrationSentences92
filterMatches
0"watch"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences111
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
maxSentenceWordsSeen12
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords585
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions3
unquotedAttributions0
matches(empty)
37.76% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions23
wordCount490
uniqueNames7
maxNameDensity2.24
worstName"Harlow"
maxWindowNameDensity3.5
worstWindowName"Harlow"
discoveredNames
Quinn1
Herrera1
Saint1
Christopher1
London1
Tomás7
Harlow11
persons
0"Quinn"
1"Herrera"
2"Saint"
3"Christopher"
4"Tomás"
5"Harlow"
places
0"London"
globalScore0.378
windowScore0.5
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences37
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount585
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences111
matches(empty)
48.23% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs6
mean97.5
std31.08
cv0.319
sampleLengths
075
1112
288
3160
481
569
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
totalVerbs95
matches(empty)
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences111
ratio0
matches(empty)
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount490
adjectiveStacks0
stackExamples(empty)
adverbCount3
adverbRatio0.006122448979591836
lyAdverbCount0
lyAdverbRatio0
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences111
echoCount0
echoWords(empty)
85.13% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences111
mean5.27
std1.91
cv0.363
sampleLengths
05
112
24
35
48
56
67
75
88
98
107
114
127
134
147
155
163
175
188
196
204
214
224
235
243
257
264
276
286
292
303
314
325
336
347
356
367
373
385
396
407
4110
4210
435
446
455
466
475
489
497
40.09% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats11
diversityRatio0.26126126126126126
totalSentences111
uniqueOpeners29
0.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount0
totalSentences88
matches(empty)
ratio0
83.64% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount30
totalSentences88
matches
0"Her boots splashed through puddles."
1"She held her coat close"
2"She caught the edge of"
3"She shook her head to"
4"Her jawline set tight under"
5"She checked her watch."
6"She ran toward the cut."
7"She hit the ground."
8"She stepped over the threshold."
9"It smelled of diesel and"
10"She pushed the heavy metal"
11"She pushed harder."
12"She walked down the staircase."
13"His warm brown eyes met"
14"He looked tired."
15"Her voice echoed in the"
16"He showed the medallion on"
17"She raised the gun."
18"Her finger stayed on the"
19"She stepped over the ladder."
ratio0.341
0.00% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount86
totalSentences88
matches
0"Rain lashed against the pavement."
1"The asphalt drank up the"
2"Harlow Quinn walked fast."
3"Her boots splashed through puddles."
4"She held her coat close"
5"Rainwater dripped from her jacket"
6"She caught the edge of"
7"The wind stung her eyes."
8"Salt and pepper hair fell"
9"She shook her head to"
10"Her jawline set tight under"
11"She checked her watch."
12"Leather strap felt tight against"
13"The second hand moved."
14"The tick tick sounded inside"
15"The signal was the phone."
16"She ran toward the cut."
17"The subway entrance sat beneath"
18"The metal door stood half"
19"The shadows pooled inside."
ratio0.977
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences88
matches(empty)
ratio0
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences4
technicalSentenceCount0
matches(empty)
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags6
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags1
fancyCount0
fancyTags(empty)
dialogueSentences25
tagDensity0.04
leniency0.08
rawRatio0
effectiveRatio0
81.7371%