Run: 2026-09-03-01M1KS1Q1R89N3FPPEG2WKM7Z9

Run Details

Duration:
20.7s
Cost:
$0.003359
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 green neon above The Raven's Nest and turned Soho into a smeared photograph. The sign buzzed, threw sick light across wet pavement. Detective Harlow Quinn stepped out with her coat collar up, water beading on the worn leather watch on her left wrist. Salt-and-pepper hair stuck to her temple. She scanned the street and saw him. Tomás Herrera broke from the doorway across the lane, Saint Christopher medallion catching the neon as he ran. Olive skin darkened by rain. Short curly dark brown hair plastered to his forehead. The scar ran along his left forearm, pale in the low light. Quinn moved. “Herrera!” He did not look back. He knew the alley behind the bar, the service doors, the narrow cut through Chinatown that spilled onto Wardour Street. Quinn kept three lengths behind, boots slipping on film of oil and water. Her breathing stayed even, military precision in every step. A bus hissed past, sprayed the curb. Herrera vaulted a stack of crates outside a closed restaurant. Quinn ducked under the bus’s tail and cut across. The chase carried them past black-and-white photographs taped to brick, past old maps curling on shop shutters. The walls of The Raven’s Nest were covered with old maps and black-and-white photographs, but outside the street was just rain and noise. Herrera turned down a side street slick with reflections. He was fast, lighter than he looked. Quinn’s sharp jaw tightened. “You can’t keep running.” He laughed without slowing. “Then don’t follow.” Quinn closed the gap at a crossing. Red light. He sprinted through. She followed, shoulder checking a cyclist. The city compressed. Camden rose ahead, the high street crowded with late drinkers under awnings. Herrera veered off the main drag, down a service stair behind a pub. Quinn followed, hand on her belt. Metal stairs sang under her boots. Cold air rose from below. A faint smell of damp concrete and old oil. Herrera paused at the bottom and looked back once. Warm brown eyes met hers. He lifted his left forearm, showed the scar, then turned toward a narrow arch cut into the wall. The arch led to a tunnel mouth. Graffiti covered the entrance. A low thrum came from inside, not traffic, not trains. Water dripped somewhere deep. Quinn stopped at the top of the stair. Rain continued above, distant and thin here. “Come back up.” Herrera stood in the dark mouth. His voice carried back. “You don’t want in.” “I want you.” He shook his head. “This isn’t police business.” Quinn studied the arch. No sign, no light. A rusted iron gate hung half open. Beyond, a corridor of bare bulb and shadow. She thought of DS Morris three years ago, gone under unexplained circumstances she still could not file. She thought of eighteen years of decorated service and the file on the clique that kept thickening. “You’re running medical for them.” “Off the books,” Herrera said. “You know that.” “Off the books is a crime.” He stepped further into the dark. The medallion glinted once. “You think I’m selling pills. I’m keeping people alive.” “You’re keeping them hidden.” Silence except for dripping. Quinn’s watch caught a glint. She had been on this street twenty minutes. The rain had soaked through her cuffs. Her coat weighed heavy. Herrera turned his back and walked deeper. The corridor narrowed. The thrum grew louder, a low marketplace hum. “Quinn.” She followed the sound. The tunnel opened into a cavernous space that could only be an abandoned Tube station beneath Camden. Columns rose under a vaulted ceiling. Stalls lined the platforms, draped in canvas and string lights. Figures moved between them, some with skin that shone wrong in the light, some with eyes that reflected too much. The Veil Market. Bone tokens hung on a chain at the gate. A woman in a coat that seemed stitched from shadow stood guard, hand outstretched. Herrera stopped at the threshold. He did not offer her a token. He waited. Quinn stood at the mouth of the stair, rain at her back, market before her. The air changed here, colder and sweet with alchemical tang. Enchanted goods glinted under glass. Information was sold on slips of paper. The woman at the gate looked at Quinn. “You need a token.” Quinn’s hand stayed at her side. She could pull back, call for backup, set a perimeter. She could wait for the market to move locations every full moon and lose it. Herrera spoke from inside. “You should go.” Quinn stared at the gate, at the market, at the man who ran from her into an unfamiliar and potentially dangerous territory. Rain ran down her face. She lifted her chin. “Let me through.”
created_at"2026-09-03T13:59:01.951Z" 9/3/2026, 1:59:01 PM
model"meta/muse-glimmer-30b-20260810"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency241
moderation_latency(null)
generation_time20591
tokens_prompt1104
tokens_completion2646
native_tokens_prompt1005
native_tokens_completion2210
native_tokens_completion_images(null)
native_tokens_reasoning1430
native_tokens_cached992
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"stop"
service_tier(null)
usage0.00335923
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.19.0; linux; x64))"
http_referer(null)
request_id"req-1788443941-x0j1WGCeJhQ65zr9bSD4"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1788443941-923MehJVY1J58CTuceqS"
upstream_id"oyofgWr-7ArivV-a35545cd7fc2f4d9"
provider_responses
0
endpoint_id"e6c588fa-aef0-4e1b-bb7f-78185dd5b6da"
id"oyofgWr-7ArivV-a35545cd7fc2f4d9"
is_byokfalse
latency241
model_permaslug"meta/muse-glimmer-30b-20260810"
provider_name"Together"
status200
total_cost0.00335923
cache_discount0.00030752
upstream_inference_cost0
provider_name"Together"
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
totalTags1
adverbTagCount0
adverbTags(empty)
dialogueSentences17
tagDensity0.059
leniency0.118
rawRatio0
effectiveRatio0
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount786
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)
80.92% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount786
totalAiIsms3
found
0
word"scanned"
count1
1
word"silence"
count1
2
word"glint"
count1
highlights
0"scanned"
1"silence"
2"glint"
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
narrationSentences86
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount2
hedgeCount0
narrationSentences86
filterMatches
0"watch"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences102
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen25
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords786
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions1
unquotedAttributions0
matches(empty)
53.18% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions44
wordCount723
uniqueNames17
maxNameDensity1.94
worstName"Quinn"
maxWindowNameDensity3
worstWindowName"Quinn"
discoveredNames
Raven2
Nest2
Soho1
Harlow1
Quinn14
Herrera10
Saint1
Christopher1
Chinatown1
Wardour1
Street1
Morris1
Tube1
Camden2
Veil1
Market1
Rain3
persons
0"Raven"
1"Harlow"
2"Quinn"
3"Herrera"
4"Saint"
5"Christopher"
6"Morris"
7"Rain"
places
0"Soho"
1"Chinatown"
2"Wardour"
3"Street"
4"Market"
globalScore0.532
windowScore0.667
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences56
glossingSentenceCount1
matches
0"seemed stitched from shadow stood guard, hand outstretched"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount786
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences102
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs46
mean17.09
std17.31
cv1.013
sampleLengths
059
144
22
31
447
526
640
720
84
94
103
1118
1234
1352
1425
1515
163
1710
184
193
204
214
2257
235
248
256
2610
279
284
294
3024
3118
321
3357
343
3523
3614
3737
388
394
4031
414
423
4327
444
453
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount1
totalSentences86
matches
0"was sold"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs127
matches(empty)
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences102
ratio0
matches(empty)
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount729
adjectiveStacks0
stackExamples(empty)
adverbCount13
adverbRatio0.01783264746227709
lyAdverbCount3
lyAdverbRatio0.00411522633744856
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences102
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences102
mean7.71
std5.05
cv0.655
sampleLengths
016
19
221
36
47
518
65
79
812
92
101
115
1220
1313
149
157
1610
179
1817
1923
209
217
224
234
244
253
267
272
283
296
303
3112
3213
336
346
355
369
379
385
3918
407
414
4210
434
448
457
463
476
484
494
53.59% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats7
diversityRatio0.3627450980392157
totalSentences102
uniqueOpeners37
0.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount0
totalSentences82
matches(empty)
ratio0
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount21
totalSentences82
matches
0"She scanned the street and"
1"He did not look back."
2"He knew the alley behind"
3"Her breathing stayed even, military"
4"He was fast, lighter than"
5"He laughed without slowing."
6"He sprinted through."
7"She followed, shoulder checking a"
8"He lifted his left forearm,"
9"His voice carried back."
10"He shook his head."
11"She thought of DS Morris"
12"She thought of eighteen years"
13"He stepped further into the"
14"She had been on this"
15"Her coat weighed heavy."
16"She followed the sound."
17"He did not offer her"
18"She could pull back, call"
19"She could wait for the"
ratio0.256
8.78% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount74
totalSentences82
matches
0"The sign buzzed, threw sick"
1"Detective Harlow Quinn stepped out"
2"Salt-and-pepper hair stuck to her"
3"She scanned the street and"
4"Tomás Herrera broke from the"
5"Olive skin darkened by rain."
6"The scar ran along his"
7"He did not look back."
8"He knew the alley behind"
9"Quinn kept three lengths behind,"
10"Her breathing stayed even, military"
11"A bus hissed past, sprayed"
12"Herrera vaulted a stack of"
13"Quinn ducked under the bus’s"
14"The chase carried them past"
15"The walls of The Raven’s"
16"Herrera turned down a side"
17"He was fast, lighter than"
18"Quinn’s sharp jaw tightened."
19"He laughed without slowing."
ratio0.902
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences82
matches(empty)
ratio0
23.81% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences24
technicalSentenceCount4
matches
0"He knew the alley behind the bar, the service doors, the narrow cut through Chinatown that spilled onto Wardour Street."
1"She thought of eighteen years of decorated service and the file on the clique that kept thickening."
2"The tunnel opened into a cavernous space that could only be an abandoned Tube station beneath Camden."
3"Quinn stared at the gate, at the market, at the man who ran from her into an unfamiliar and potentially dangerous territory."
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags1
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags1
fancyCount0
fancyTags(empty)
dialogueSentences17
tagDensity0.059
leniency0.118
rawRatio0
effectiveRatio0
84.0094%