Run: 2026-09-03-01M1KBQTAY35WJCJ0KVT2EB51E

Run Details

Duration:
57.0s
Cost:
$0.018472
Provider:
Parasail

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
The rain had turned Camden High Street into a black mirror. Detective Harlow Quinn stood outside a shuttered vape shop, water sliding off her jaw. She had followed Tomás Herrera from The Raven’s Nest, keeping a half-block back as he threaded through Soho and jumped a night bus. Now he passed under the railway bridge, his rucksack hugged to his chest, the Saint Christopher medallion swinging at his collarbone. A kebab shop’s window threw light across the pavement. Herrera glanced into it and saw her. He ran. “Police! Herrera, stop!” Her voice cut the rain. He shouldered past a man closing a flower stall, scattering cellophane. She sprinted after him. He cut left into an alley beside a vinyl shop. Her boots punched through puddles. A wheelie bin crashed onto its side. She hurdled it, caught the sharp reek of cardamom and wet garbage. The alley narrowed between brick walls, then opened onto a service road behind a row of restaurants. She keyed her radio while running. “Dispatch, Quinn. Foot pursuit, Camden High Street, male, olive skin, dark curly hair. Suspect is Tomás Herrera. Requesting units.” The radio coughed static. Somewhere above, a train rattled along the elevated line. Herrera kicked through a chain-link gate and vanished behind construction hoarding. She followed, ducking under a loose panel. The hoarding opened onto a dead-end courtyard stacked with pallets and corroded piping. No exit except a black iron door set into a brick retaining wall. He fumbled at the collar of his jacket and pulled a pale token from the cord beside his medallion. The token slid into a slot in the iron plate. The door swung inward with a sound like a gasp. She was ten strides behind. “Herrera!” He disappeared into the dark. The door hung open. She stopped at the threshold. Rain hammered the hoarding behind her. The doorway exhaled warm air that smelled of wax, copper, and crushed herbs. Steps descended into a gloom broken by a single flickering bulb. Her baton came off her belt. She extended it with a snap and thumbed her radio again. “Quinn to any unit, I’m entering a service door behind the old builders’ yard off Castlehaven Road. Send backup.” No voice came back. The static had a texture, like small teeth. She stepped inside. The stairwell walls were tiled in the old Underground style, cracks running through the white glaze. Water dripped somewhere far below. Herrera’s footsteps echoed ahead. She took the stairs at pace, one hand on the rail, weapon tight. The bulb’s light died behind her, and the dark came up to meet every step. At the bottom, the passage opened onto a disused platform. The Veil Market sprawled across the tracks. Stalls made from pallets, church pews, and iron bedframes crowded the space. Lanterns burned with green flame. Smoke curled around jars of preserved things and cages draped in black cloth. Herrera shoved through a knot of patrons near a stall hung with copper bells. The bells chimed. He did not look back. She moved to follow, but a voice stopped her. “Bone for the crossing, love.” A man sat at a card table beside the last step. A bowl of knuckle-bones rested by his elbow. His eyes were too wet in the green light. “I’m police.” He spread his hands. “Don’t spend down here.” Her radio let out a low whine and fell silent. She looked into the market. Hooded figures moved between stalls. A vendor poured lightning from a steel flask into a jar. Another stitched silver thread through what looked like human skin. The air pressed against her chest. Herrera’s back appeared beyond a stack of leather-bound ledgers, then slipped behind a curtain of beads. She had no backup. No bone token. No sense of the law in this place. She rolled her left wrist, tightened the worn leather watch strap, and stepped past the table. The knuckle-bones rattled in the bowl as she passed.
created_at"2026-09-03T10:06:26.155Z" 9/3/2026, 10:06:26 AM
model"deepseek/deepseek-v4-pro-20260813"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency606
moderation_latency(null)
generation_time56909
tokens_prompt1104
tokens_completion4828
native_tokens_prompt1082
native_tokens_completion4304
native_tokens_completion_images(null)
native_tokens_reasoning3827
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"stop"
service_tier(null)
usage0.01847208
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.19.0; linux; x64))"
http_referer(null)
request_id"req-1788429986-ieX354gHaRN9s2jNhfnD"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1788429986-pNU42hfWRm1mDm9eoypQ"
upstream_id"bda5d665acec4b6ab0352a20d9e9dd0b"
provider_responses
0
endpoint_id"487a0ef9-ddaa-4d3d-b882-7912daa08555"
id"bda5d665acec4b6ab0352a20d9e9dd0b"
is_byokfalse
latency606
model_permaslug"deepseek/deepseek-v4-pro-20260813"
provider_name"Parasail"
status200
total_cost0.01847208
cache_discount(null)
upstream_inference_cost0
provider_name"Parasail"
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
totalTags0
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount660
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)
69.70% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount660
totalAiIsms4
found
0
word"gloom"
count1
1
word"footsteps"
count1
2
word"echoed"
count1
3
word"sense of"
count1
highlights
0"gloom"
1"footsteps"
2"echoed"
3"sense of"
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
narrationSentences67
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount0
narrationSentences67
filterMatches
0"watch"
hedgeMatches(empty)
94.13% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences74
gibberishSentences1
adjustedGibberishSentences1
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount1
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen24
ratio0.014
matches
0"“Dispatch, Quinn. Foot pursuit, Camden High Street, male, olive skin, dark curly hair. Suspect is Tomás Herrera. Requesting units.”"
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords660
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions1
unquotedAttributions0
matches(empty)
100.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions20
wordCount607
uniqueNames15
maxNameDensity0.99
worstName"Herrera"
maxWindowNameDensity1.5
worstWindowName"Herrera"
discoveredNames
Camden1
High1
Street1
Harlow1
Quinn1
Tomás1
Herrera6
Raven1
Nest1
Soho1
Saint1
Christopher1
Underground1
Veil1
Market1
persons
0"Harlow"
1"Quinn"
2"Tomás"
3"Herrera"
4"Nest"
5"Saint"
6"Christopher"
places
0"Camden"
1"High"
2"Street"
3"Raven"
4"Soho"
globalScore1
windowScore1
41.30% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences46
glossingSentenceCount2
matches
0"looked like human skin"
1"appeared beyond a stack of leather-bound ledgers, then slipped behind a curtain of beads"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount660
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences74
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs32
mean20.63
std17.73
cv0.86
sampleLengths
069
116
22
33
420
551
66
719
813
944
1039
115
121
139
1435
1517
1619
1712
183
1953
2047
2122
229
235
2428
252
268
2747
2816
2915
3016
319
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount1
totalSentences67
matches
0"were tiled"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs108
matches(empty)
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences74
ratio0
matches(empty)
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount613
adjectiveStacks0
stackExamples(empty)
adverbCount8
adverbRatio0.013050570962479609
lyAdverbCount0
lyAdverbRatio0
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences74
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences74
mean8.92
std4.94
cv0.554
sampleLengths
011
114
223
321
49
57
62
73
85
911
104
1110
125
137
1412
1517
166
1719
184
199
2011
217
2213
2313
2419
2510
2610
275
281
295
304
315
326
3313
3411
356
3611
3719
384
398
403
4116
425
434
4413
4515
4610
477
4812
495
54.50% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats3
diversityRatio0.35135135135135137
totalSentences74
uniqueOpeners26
50.51% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount1
totalSentences66
matches
0"Somewhere above, a train rattled"
ratio0.015
68.48% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount25
totalSentences66
matches
0"She had followed Tomás Herrera"
1"Her voice cut the rain."
2"He shouldered past a man"
3"She sprinted after him."
4"He cut left into an"
5"Her boots punched through puddles."
6"She hurdled it, caught the"
7"She keyed her radio while"
8"She followed, ducking under a"
9"He fumbled at the collar"
10"She was ten strides behind."
11"He disappeared into the dark."
12"She stopped at the threshold."
13"Her baton came off her"
14"She extended it with a"
15"She stepped inside."
16"She took the stairs at"
17"He did not look back."
18"She moved to follow, but"
19"His eyes were too wet"
ratio0.379
28.18% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount57
totalSentences66
matches
0"The rain had turned Camden"
1"Detective Harlow Quinn stood outside"
2"She had followed Tomás Herrera"
3"A kebab shop’s window threw"
4"Herrera glanced into it and"
5"Her voice cut the rain."
6"He shouldered past a man"
7"She sprinted after him."
8"He cut left into an"
9"Her boots punched through puddles."
10"A wheelie bin crashed onto"
11"She hurdled it, caught the"
12"The alley narrowed between brick"
13"She keyed her radio while"
14"The radio coughed static."
15"Herrera kicked through a chain-link"
16"She followed, ducking under a"
17"The hoarding opened onto a"
18"He fumbled at the collar"
19"The token slid into a"
ratio0.864
75.76% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount1
totalSentences66
matches
0"Now he passed under the"
ratio0.015
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences31
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
89.4188%