Run: 2026-03-11-01KKFD4J5ND4T59XPGD6H490VG

Run Details

Duration:
1m 20s
Cost:
$0.000951
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 hammered the pavement like gravel thrown by an angry beast. Harlow Quinn moved fast. Her boots slapped against the wet asphalt. Water ran from her undercut hair in streams. She did not stop to wipe her brow. Her windpipe burned cold. A shadow passed on her left. She turned to face it. The silhouette stood still. Harlow adjusted her grip on the grip of her baton. "Come out." The figure stepped sideways. Long coat flapped in the gale. "Drop it." The voice came from behind a brick wall. "Not without a word." Harlow pushed the brickwork back. "Then speak." The suspect stood within the alley. A scarred arm extended toward her. "Going the right way." "Where." "Down." The suspect pointed at the subway entrance. The sign above it hummed green. "She will try it." "I don't have time." "The cost will be high." Harlow bolted toward the station. Water poured from her jacket lining. She shoved the ticket kiosk open. The card swiped against the metal. The lights inside flickered. The air grew thick with smell. Mold and old coins cloyed the nostril. She stepped inside. The station floor vanished into darkness. The rails gleamed below. She pulled her badge out. The metal clicked. She pressed it against the desk. "License check." "Show your papers." Harlow stepped over the barrier. "Move." The man at the desk hid the paper bag. He smiled without feeling. She followed the path deeper. The walls curve inward. They were covered with photos. Black and white images of faces. Unknown men stared back. Harlow walked with the noise in her head. The rain followed her steps. A voice called out from the shadows. "Police." Tomás Herrera stepped from the wall. He wore a trench coat heavy with rain. The medallion on his chest caught the low light. Gold. "Put the weapon down." "Where is the suspect." "In here." Tomás pointed to the left. Corridor ended. "Turn back." "No." She fired the stun baton. It sparked against the floor. "Quinn stop." Tomás walked forward. His olive skin dark with sweat. He held the baton loose. "That man." The word floated out. "He dies in this place." "I know." "Then why." "Why not." Harlow stepped onto the platforms. She felt the hum of the rails. The ground shook. "Who else." "The market." Tomás looked at the ceiling. Cracks showed the vault. "Go with me." "To where." "The Veil Market." "Underground." He shoved the medallion closer. "Listen." She listened. A low growl came from the far end. "Warmth." "They say the cold does not reach here." Harlow lowered the weapon. She felt the fatigue in her legs. "The token." Tomás moved to the bookshelf. He pulled one letter out. "The market takes entrance." "What." "Bone token." Harlow scanned the wall. She saw the glint. It glinted like a coin. "Give it." "I have none." "The suspect has one." Harlow looked at the room again. She saw the movement. She stepped forward. "There." The shadow near the window. "It waits." "Keep it back." Tomás opened the bookshelf. A black hole opened inside. "I'll leave my badge." "No." Harlow walked closer. Her heart beat against her ribs. The floor felt wet. She could smell the ozone. "Go down." "What is that place." "Buy and sell." "Magic." "Alchemy." Harlow stepped across the threshold. The light changed. Steam rose from a puddle. She saw the door behind her. It closed. She spun. Glass shards clinked. "You wrong me." "Go down there." She raised the baton. The metal hummed. She looked straight ahead. Men in robes stood near the tunnel. They turned faces away. She lowered the weapon. She moved toward them. The air grew thicker. "Where is he." "They wait." Tomás pressed his scarred arm against his side. The knife scar throbbed. "I will find him." "You know the price." "What price." "Your own choice." Harlow looked at the man. She felt the cold air hit her back. She looked toward the tunnel. The ground sloped steeply. "Walking." "There." The noise came from deeper inside. She moved past him. She pushed the glass door. It promised nothing. She stepped inside. The darkness swallowed her. She heard the sound of rain on the roof. She looked up. Damp surfaces reflected the light. She pulled her coat tight. Her hand held the weapon. She felt the metal cold. She looked at the wall. It sang no sound. She moved forward. She heard the steps. Her boots echoed. The market breathed. She stopped. "Quinn." Tomás stood inside. He blocked the path. "The vendor." "He is not here." "Then." "Then we wait." Harlow cold fingers brushed the collar. The watch ticked. It slowed. She breathed hard. Her chest heaved. "I need to." "To do what." "Find." She pushed him aside. He did not move. She pushed harder. He stepped back. She entered. The door slammed behind. She heard the lock click. She stepped into the aisle. The darkness waited.
created_at"2026-03-11T21:34:09.09Z" 3/11/2026, 9:34:09 PM
model"qwen/qwen3.5-9b-20260310"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency205
moderation_latency(null)
generation_time79655
tokens_prompt1140
tokens_completion5873
native_tokens_prompt1065
native_tokens_completion5628
native_tokens_completion_images(null)
native_tokens_reasoning4511
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"
usage0.0009507
router(null)
provider_responses
0
endpoint_id"00d506d9-a5e9-4382-a2b9-d54732365594"
id"oagLryA-6Ng1vN-9dadae7ae2b76c69"
is_byokfalse
latency205
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-1773264849-jw83FvCazfVdcI5x1QJ2"
upstream_id"oagLryA-6Ng1vN-9dadae7ae2b76c69"
total_cost0.0009507
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
totalTags0
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount824
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)
63.59% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount824
totalAiIsms6
found
0
word"flickered"
count1
1
word"warmth"
count1
2
word"scanned"
count1
3
word"glint"
count1
4
word"throbbed"
count1
5
word"echoed"
count1
highlights
0"flickered"
1"warmth"
2"scanned"
3"glint"
4"throbbed"
5"echoed"
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
narrationSentences135
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount0
hedgeCount1
narrationSentences135
filterMatches(empty)
hedgeMatches
0"tended to"
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences204
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
maxSentenceWordsSeen11
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords824
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions2
unquotedAttributions0
matches(empty)
42.80% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions24
wordCount653
uniqueNames4
maxNameDensity2.14
worstName"Harlow"
maxWindowNameDensity3.5
worstWindowName"Harlow"
discoveredNames
Quinn1
Herrera1
Harlow14
Tomás8
persons
0"Quinn"
1"Herrera"
2"Harlow"
3"Tomás"
places(empty)
globalScore0.428
windowScore0.5
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences39
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount824
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences204
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs17
mean48.47
std25.2
cv0.52
sampleLengths
042
16
29
312
431
544
640
751
837
964
1050
1156
12106
1366
1475
1558
1677
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount0
totalSentences135
matches(empty)
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs138
matches(empty)
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences204
ratio0
matches(empty)
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount653
adjectiveStacks0
stackExamples(empty)
adverbCount9
adverbRatio0.013782542113323124
lyAdverbCount1
lyAdverbRatio0.0015313935681470138
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences204
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences204
mean4.04
std1.98
cv0.49
sampleLengths
011
14
27
38
48
54
66
75
84
910
102
114
126
132
148
154
165
172
186
196
204
211
221
237
246
254
264
275
285
296
306
316
324
336
347
353
366
374
385
393
406
412
423
435
441
459
464
475
484
495
43.63% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats13
diversityRatio0.29411764705882354
totalSentences204
uniqueOpeners60
0.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount0
totalSentences127
matches(empty)
ratio0
40.47% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount57
totalSentences127
matches
0"Her boots slapped against the"
1"She did not stop to"
2"Her windpipe burned cold."
3"She turned to face it."
4"She shoved the ticket kiosk"
5"She stepped inside."
6"She pulled her badge out."
7"She pressed it against the"
8"He smiled without feeling."
9"She followed the path deeper."
10"They were covered with photos."
11"He wore a trench coat"
12"She fired the stun baton."
13"It sparked against the floor."
14"His olive skin dark with"
15"He held the baton loose."
16"She felt the hum of"
17"He shoved the medallion closer."
18"She felt the fatigue in"
19"He pulled one letter out."
ratio0.449
0.00% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount122
totalSentences127
matches
0"Harlow Quinn moved fast."
1"Her boots slapped against the"
2"Water ran from her undercut"
3"She did not stop to"
4"Her windpipe burned cold."
5"A shadow passed on her"
6"She turned to face it."
7"The silhouette stood still."
8"Harlow adjusted her grip on"
9"The figure stepped sideways."
10"The voice came from behind"
11"Harlow pushed the brickwork back."
12"The suspect stood within the"
13"A scarred arm extended toward"
14"The suspect pointed at the"
15"The sign above it hummed"
16"Harlow bolted toward the station."
17"Water poured from her jacket"
18"She shoved the ticket kiosk"
19"The card swiped against the"
ratio0.961
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences127
matches(empty)
ratio0
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences2
technicalSentenceCount0
matches(empty)
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags0
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags0
83.0165%